In the era of big data, neuroimaging and algorithmic analyses have propelled brain science research and brain mapping. Acupuncture, widely recognized as an effective surface stimulation therapy, has demonstrated therapeutic efficacy for various brain conditions such as stroke and depression. However, the mechanisms linking acupuncture to brain function and its modulatory effects on brain activity require systematic exploration. Additionally, there is an urgent need to scientifically reinterpret traditional meridian theory and enhance its clinical applicability. Therefore, we propose the initiative of constructing a "brain mapping atlas of meridian, collateral and body surface stimulation" to explore the patterns linking the therapeutic effects of stimulating the twelve meridians, eight extraordinary vessels, divergent channels, collateral channels, sinew channels, and skin regions to brain function. This initiative aims to provide a scientific interpretation of traditional Chinese medicine meridian theory and enhance its practical applicability. This paper begins by reviewing the current state of brain mapping. It then summarizes existing research on the relationship between acupuncture and the brain, highlighting the necessity of constructing this atlas. The paper further analyzes the methodologies and technical challenges involved. Finally, the potential applications of the brain mapping atlas of meridian, collateral and body surface stimulation, and its main significance in advancing traditional meridian theory to keep pace with the times are prospected.
Humans ; Acupuncture Therapy ; Meridians ; Big Data ; Brain/physiology* ; Brain Mapping

The correlation between meridians and zangfu organs is one of the core contents of the theory of zangfu organs and meridians, which has significant research value and clinical application potential. In this paper, the research literature on correlation between meridians and zangfu organs in the past five years is sorted out and summarized, and it is found that more clinical application basis is added in meridian-diagnosis, and a new situation of high-quality evidence-based medicine is opened in the aspect of meridian-treatment. In terms of internal connection and biological mechanism, the neurobiological characteristics and regulatory mechanism represented by "heart meridian-heart" are illustrated. The research model of the relationship between the meridians-zangfu organs and the brain, which combines the functional connection of the brain network in clinic and the basic neural circuit mechanism under the premise of the "effect law", is clearly proposed.
Meridians ; Humans ; Brain/physiology*

Electroencephalography (EEG) and magnetic resonance imaging (MRI), as neuroimaging technologies, provided objective and visualized technical tools for analyzing the brain effect mechanisms of acupuncture and moxibustion from the perspectives of brain structure, function, metabolism, and hemodynamics. The advancement of artificial intelligence (AI) algorithms can compensate for issues such as the large and scattered nature of neuroimaging data, inconsistent quality, and high heterogeneity of image information. The integration of AI with neuroimaging can facilitate individualized, intelligent, and precise prediction of acupuncture and moxibustion effects, enable intelligent classification of differential acupuncture responses, and identify brain activation patterns. This paper focuses on EEG and MRI, analyzing how machine learning and deep learning optimize multimodal neuroimaging data and their applications in the study of acupuncture and moxibustion brain effects mechanisms. Furthermore, it highlights current research gaps and limitations to provide insights for future studies on acupuncture brain effects mechanisms.
Humans ; Acupuncture Therapy ; Brain/physiology* ; Moxibustion ; Neuroimaging/methods* ; Artificial Intelligence ; Magnetic Resonance Imaging ; Electroencephalography

Gliomas are the most common primary neuroepithelial tumors of the central nervous system in adults, of which glioblastoma is the deadliest subtype. Apart from the intrinsically indestructible characteristics of glioma (stem) cells, accumulating evidence suggests that the tumor microenvironment also plays a vital role in the refractoriness of glioblastoma. The primary functions of platelets are to stop bleeding and regulate thrombosis under physiological conditions. Furthermore, platelets are also active elements that participate in a variety of processes of tumor development, including tumor growth, invasion, and chemoresistance. Glioma cells recruit and activate resting platelets to become tumor-educated platelets (TEPs), which in turn can promote the proliferation, invasion, stemness, and chemoresistance of glioma cells. TEPs can be used to obtain genetic information about gliomas, which is helpful for early diagnosis and monitoring of therapeutic effects. Platelet membranes are intriguing biomimetic materials for developing efficacious drug carriers to enhance antiglioma activity. Herein, we review the recent research referring to the contribution of platelets to the malignant characteristics of gliomas and focusing on the molecular mechanisms mediating the interaction between TEPs and glioma (stem) cells, as well as present the challenges and opportunities in targeting platelets for glioma therapy.
Humans ; Glioma/metabolism* ; Blood Platelets/physiology* ; Brain Neoplasms/pathology* ; Tumor Microenvironment

Inflammatory bowel disease (IBD) is an idiopathic intestinal inflammatory condition with chronic and relapsing manifestations and is characterized by a disturbance in the interplay between the intestinal microbiota, the gut, and the brain. The microbiota-gut-brain axis involves interactions among the nervous system, the neuroendocrine system, the gut microbiota, and the host immune system. Increasing published data indicate that psychological stress exacerbates the severity of IBD due to its negative effects on the microbiota-gut-brain axis, including alterations in the stress response of the hypothalamic-pituitary-adrenal (HPA) axis, the balance between the sympathetic nervous system and vagus nerves, the homeostasis of the intestinal flora and metabolites, and normal intestinal immunity and permeability. Although the current evidence is insufficient, psychotropic agents, psychotherapies, and interventions targeting the microbiota-gut-brain axis show the potential to improve symptoms and quality of life in IBD patients. Therefore, further studies that translate recent findings into therapeutic approaches that improve both physical and psychological well-being are needed.
Humans ; Inflammatory Bowel Diseases/metabolism* ; Stress, Psychological/microbiology* ; Gastrointestinal Microbiome/physiology* ; Brain/metabolism* ; Hypothalamo-Hypophyseal System ; Pituitary-Adrenal System ; Animals

Brain science is the frontier of modern science, and new advances have been made in brain-like designs and brain-computer interfaces to simulate or develop brain functions. However, given that the brain is hermetically sealed within the skull, exploration and deciphering of the brain structure and functions are limited. Growing evidence suggests that the gut is not just a digestive organ. It not only provides essential nutrients and electrolytes for brain neurodevelopment and the maintenance of brain function, but it also transmits external environmental and intestinal wall signals from the intestinal lumen to the central nervous system through multiple pathways to regulate brain activity, function, and structure. A variety of gut-brain interaction pathways have been identified, including neural pathways, neuroimmune signaling, endocrine pathways, and biochemical messengers produced by gut microbes. Gut microbes interact with food and the gut to modulate gut-brain communication. The gut's important role and potential in neurodevelopment, maintenance of normal function, and disease development make it an increasingly important area of research in brain science and neuropsychiatric disorders. The gut's unique role in brain functions and its accessibility for research (compared to direct brain studies) establish it as a critical gate to understanding the mysteries of brain science. Crucially, intestinal nutrients and microbes provide two unique keys to unlock this gate-enabling neural regulation and novel treatments for neuropsychiatric diseases.
Humans ; Brain/physiology* ; Animals ; Gastrointestinal Microbiome/physiology* ; Gastrointestinal Tract/microbiology*

Brain cancer remains among the most lethal malignancies worldwide, with approximately 321,476 new cases and 248,305 deaths reported globally in 2022. The treatment of malignant brain tumors presents substantial clinical challenges, primarily due to their resistance to standard therapeutic approaches. Despite decades of intensive research, effective treatment strategies for brain cancer are still lacking. Nuclear receptors (NRs), a superfamily of ligand-activated transcription factors, regulate a broad range of physiological processes including metabolism, immunity, stress response, reproduction, and cellular differentiation. Increasing evidence highlights the involvement of NRs in oncogenesis, with several members demonstrating altered expression and function in brain tumors. Aberrations in NR signaling, encompassing receptors such as androgen receptors, estrogen receptors, estrogen-related receptors, glucocorticoid receptors, NR subfamily 4 group A, NR subfamily 1 group D member 2, NR subfamily 5 group A member 2, NR subfamily 2 group C member 2, liver X receptors, peroxisome-proliferator activated receptors, progesterone receptors, retinoic acid receptors, NR subfamily 2 group E member 1, thyroid hormone receptors, vitamin D receptors, and retinoid X receptors, have been implicated in promoting hallmark malignant phenotypes, including enhanced survival, proliferation, invasion, migration, metastasis, and resistance to therapy. This review aims to explore the roles of key NRs in brain cancer, with an emphasis on their prognostic significance, and to evaluate the therapeutic potential of targeting these receptors using selective agonists or antagonists.
Humans ; Brain Neoplasms/drug therapy* ; Receptors, Cytoplasmic and Nuclear/metabolism* ; Animals ; Signal Transduction/physiology*

This paper proposes a motor imagery recognition algorithm based on feature fusion and transfer adaptive boosting (TrAdaboost) to address the issue of low accuracy in motor imagery (MI) recognition across subjects, thereby increasing the reliability of MI-based brain-computer interfaces (BCI) for cross-individual use. Using the autoregressive model, power spectral density and discrete wavelet transform, time-frequency domain features of MI can be obtained, while the filter bank common spatial pattern is used to extract spatial domain features, and multi-scale dispersion entropy is employed to extract nonlinear features. The IV-2a dataset from the 4 ^th International BCI Competition was used for the binary classification task, with the pattern recognition model constructed by combining the improved TrAdaboost integrated learning algorithm with support vector machine (SVM), k nearest neighbor (KNN), and mind evolutionary algorithm-based back propagation (MEA-BP) neural network. The results show that the SVM-based TrAdaboost integrated learning algorithm has the best performance when 30% of the target domain instance data is migrated, with an average classification accuracy of 86.17%, a Kappa value of 0.723 3, and an AUC value of 0.849 8. These results suggest that the algorithm can be used to recognize MI signals across individuals, providing a new way to improve the generalization capability of BCI recognition models.
Brain-Computer Interfaces ; Humans ; Support Vector Machine ; Algorithms ; Neural Networks, Computer ; Imagination/physiology* ; Pattern Recognition, Automated/methods* ; Electroencephalography ; Wavelet Analysis

Motor imagery (MI) is a mental process that can be recognized by electroencephalography (EEG) without actual movement. It has significant research value and application potential in the field of brain-computer interface (BCI) technology. To address the challenges posed by the non-stationary nature and low signal-to-noise ratio of MI-EEG signals, this study proposed a Riemannian spatial filtering and domain adaptation (RSFDA) method for improving the accuracy and efficiency of cross-session MI-BCI classification tasks. The approach addressed the issue of inconsistent data distribution between source and target domains through a multi-module collaborative framework, which enhanced the generalization capability of cross-session MI-EEG classification models. Comparative experiments were conducted on three public datasets to evaluate RSFDA against eight existing methods in terms of classification accuracy and computational efficiency. The experimental results demonstrated that RSFDA achieved an average classification accuracy of 79.37%, outperforming the state-of-the-art deep learning method Tensor-CSPNet (76.46%) by 2.91% ( P < 0.01). Furthermore, the proposed method showed significantly lower computational costs, requiring only approximately 3 minutes of average training time compared to Tensor-CSPNet's 25 minutes, representing a reduction of 22 minutes. These findings indicate that the RSFDA method demonstrates superior performance in cross-session MI-EEG classification tasks by effectively balancing accuracy and efficiency. However, its applicability in complex transfer learning scenarios remains to be further investigated.
Electroencephalography/methods* ; Brain-Computer Interfaces ; Humans ; Imagination/physiology* ; Signal Processing, Computer-Assisted ; Movement/physiology* ; Signal-To-Noise Ratio ; Deep Learning ; Algorithms

Transcranial temporal interference stimulation (tTIS) is a novel non-invasive transcranial electrical stimulation technique that achieves deep brain stimulation through multiple electrodes applying electric fields of different frequencies. Current studies on the mechanism of tTIS effects are primarily based on rodents, but experimental outcomes are often significantly influenced by electrode configurations. To enhance the performance of tTIS within the limited cranial space of rodents, we proposed various electrode configurations for tTIS and conducted finite element simulations using a realistic mouse model. Results demonstrated that ventral-dorsal, four-channel bipolar, and two-channel configurations performed best in terms of focality, diffusion of activated brain regions, and scalp impact, respectively. Compared to traditional transcranial direct current stimulation (tDCS), these configurations improved by 94.83%, 50.59%, and 3 514.58% in the respective evaluation metrics. This study provides a reference for selecting electrode configurations in future tTIS research on rodents.
Animals ; Transcranial Direct Current Stimulation/instrumentation* ; Electrodes ; Mice ; Computer Simulation ; Finite Element Analysis ; Brain/physiology*