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40-Hz temporally interfering electrical stimulation over the temporal lobe induced antidepressantlike effects in chronic unpredictable mild stress rats

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IEEE Transactions on Neural Systems and Rehabilitation Engineering 2025年 33卷 1796-1804页

作者： Guo, Wanting He, Yuchen Song, Xizi Heng, Deyu Zhang, Xiaochen Ke, Yufeng Liu, Shuang Ming, Dong Tianjin University Academy of Medical Engineering and Translational Medicine China Haihe Laboratory of Brain-computer Interaction and Human-Machine Integration China Tianjin Key Laboratory of Brain Science and Neuroengineering Tianjin China Haihe Laboratory of Brain-computer Interaction and Human-Machine Integration Tianjin 300072 China

Temporally interfering (TI) electrical stimulation provides a promising noninvasive and focused stimulation for neuropsychiatric disorders. However, the feasible stimulation strategy and potential effects require further study. Our previous studies have identified gamma oscillatory abnormalities of temporal regions in depressed patients and rats. We accordingly aim to develop an effective TI antidepressant strategy. The stimulation strategy was firstly determined by modeling and simulation, and verified by c-Fos immunofluorescence staining. 32 rats were randomized into control (n=8) and depression (n=24) groups induced by chronic unpredictable mild stress (CUS), which were exposed to stimulation for 5 days, 20 mins per day. The behavioral and electrophysiology experiments were performed to examine the antidepressant-like effects of TI, using transcranial alternating current stimulation (tACS) as a positive control. In the electrophysiology experiment, local field potential (LFP) signals were recorded from bilateral primary auditory cortex (A1) before and after stimulation. We found that TI activated more c-Fos-positive cells in A1 target than tACS, exhibiting better stimulation focality. Both TI and tACS significantly ameliorated depression-like behaviors compared to sham group, and TI made more improvements. Furthermore, TI largely restored the gamma deficits by increasing gamma power and phase locking value (PLV) compared with tACS. And the gamma-band deficits were found remarkably correlated with depression-like behaviors. Overall, TI ameliorated depression-like behaviors in CUS rats, which may be associated with the restoration of aberrant gamma oscillations. With the advantages of both spatial targeting and noninvasive character, TI holds great promise for the clinical application of depression. © 2001-2011 IEEE.

关键词： Depression gamma oscillation primary auditory cortex temporally interfering electrical stimulation transcranial alternating current stimulation

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Effects of general anesthetics on the activity of SST+ interneurons in hippocampal CA1 region of mice 24

Effects of general anesthetics on the activity of SST+ inter...

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11th International Conference on Biomedical and Bioinformatics Engineering, ICBBE 2024

作者： Zhao, Meiling Sun, Shufan Wang, Ling Ren, Jing Mo, Weiyi Yang, Jiajia Medical School Tianjin University Tianjin China Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration Tianjin China

ISBN: (纸本)9798400718274

Although different general anesthetics induce similar physiological states, their effects on neuronal activity are quite different, which is closely related to brain function such as memory and cognition. Hippocampus serves a critical function in memory and cognition, where somatostatin-expressing (SST+) interneurons are the main source of inhibitory synapses on excitatory neurons. However, how the activity of this subpopulation of neurons changes in response to different anesthetics has not been clearly explored. Through switching different anesthetic strategies and using chronic in vivo two-photon imaging recordings, we monitored the effects of isoflurane (Iso), medetomidine/midazolam/fentanyl (MMF), and ketamine/xylazine (Keta/Xyl) on the calcium activity of SST+ interneurons in hippocampal CA1 region of adult mice. Compared to the awake state, all three anesthetics greatly reduced the amplitude of calcium activity in SST+ interneurons and induced different activity patterns. The correlation during anesthesia with Iso was most similar to the awake state, whereas MMF or Keta/Xyl resulted in neuronal de-correlation and had different recovery efficiencies. In conclusion, our results suggest that there are unique effects of the three anesthetics on hippocampal calcium dynamics and correlated activity. Our findings may contribute to the evaluation and development of anesthesia strategies in biological research and clinical areas. Copyright © 2024 held by the owner/author(s). Publication rights licensed to ACM.

关键词： Neurons

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VTA-NAc neural pathways involved in the mechanism of depression-like behavior induced by chronic sleep deprivation in mice 24

VTA-NAc neural pathways involved in the mechanism of depress...

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11th International Conference on Biomedical and Bioinformatics Engineering, ICBBE 2024

作者： Li, Yaqing Mo, Weiyi Ren, Jing Sun, Tianyi Zheng, Chengguaang Wang, Ling Yang, Jiajia Ming, Dong Medical School Tianjin University Tianjin China ZhejiangLab Zhejiang Hangzhou China Tianjin Key Laboratory of Brain Science and Neuroengineering Tianjin China Haihe Laboratory of Brian-Computer Interaction and Human-Machine Integration Tianjin China

ISBN: (纸本)9798400718274

Sleep plays a crucial role in individual physical and mental health. Insufficient sleep leads to inattention, memory loss, cognitive dysfunction and emotional disorders. The mesolimbic pathway, ventral tegmental area (VTA) to nucleus accumbens (NAc) dopaminergic neural pathway has been shown to be associated with sleep-wake behavior and depression-like behavior. In this study, we investigated the relation between chronic sleep deprivation (CSD)-induced depression-like behaviors and the activity of VTA-NAc dopaminergic pathway. CSD caused weight loss and depression-like behaviors in the mice, including anhedonia and helplessness. CSD prominently reduced the change of mice' s DA signal when moving freely. Additionally, NAc DA release became less noticeable in rewarding event and retreat behavior after exposing to CSD. In conclusion, our findings indicated that VTA-NAc dopaminergic neural pathway is directly related to depressive-like behavior caused by chronic sleep deprivation. This study provides a theoretical basis for the in-depth understanding of the physiological function of sleep, and provides a potential target for clinical research on improving or treating sleep disorder-related depression. Copyright © 2024 held by the owner/author(s). Publication rights licensed to ACM.

关键词： Sleep research

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Sex-specific patterns in social visual attention among individuals with autistic traits

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BMC Psychiatry 2025年第1期25卷 1-10页

作者： Zhang, Ludan Guan, Xin Xue, Huiqin Liu, Xiaoya Zhang, Bo Liu, Shuang Ming, Dong Academy of Medical Engineering and Translational Medicine Tianjin University Tianjin China Precision Medicine Laboratory Children’s Hospital Tianjin University Tianjin China Tianjin Key Laboratory of Brain Science and Neuroengineering Tianjin China State Key Laboratory of Advanced Medical Materials and Devices Tianjin China Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration Tianjin China

Background: Autism is a neurodevelopmental condition more prevalent in males, with sex differences emerging in both prevalence and core symptoms. However, most studies investigating behavioral and cognitive features of autism tend to include more male samples, leading to a male-biased understanding. The sex imbalance limits the specificity of these features, especially in female individuals with autism. Hence, it is necessary to explore sex-related differences in behavioral–cognitive traits linked to autism in the general population. Methods: In this study, we designed a dynamic emotion-discrimination task to investigate sex differences in attention to emotional stimuli among the general population with autistic traits. Behavioral and eye movement data were recorded during the task, and the Autism-Spectrum Quotient (AQ) was used to assess autistic traits. Qualitative and quantitative methods were used to analyze gaze patterns in male and female groups. Additionally, correlation analyses were conducted to examine the relationship between AQ scores and proportion of fixation time in both groups. Results: Significant sex differences in attention to the eye regions of faces were observed, with females focusing more on the eyes than males. Correlation analyses revealed that, in males, lower eye-looking was associated with higher levels of autistic traits, whereas no such association was found in females. Conclusions: Overall, these results reveal that attention patterns to emotional faces differed between females and males, and autistic traits predicted the trend of eye-looking in males. These findings suggest that sex-related stratification in social attention should be considered in clinical contexts. © The Author(s) 2025.

关键词： Autistic traits Emotional faces Eye-tracking Sex differences Social attention

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In Vivo Bioelectronic Nose Based on a Bioengineered Rat for the Explosive Odors with Benzene Ring Detection and Identification 24

In Vivo Bioelectronic Nose Based on a Bioengineered Rat for ...

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11th International Conference on Biomedical and Bioinformatics Engineering, ICBBE 2024

作者： Ma, Jing Wang, Yimeng Yang, Jun Sun, Biao Yang, Qing Zheng, Chenguang Academy of Medical Engineering and Translational Medicine Medical College Tianjin University Tianjin China College of Precision Instruments & Optoelectronics Engineering Tianjin University Tianjin China School of Electrical and Information Engineering Tianjin University Tianjin China Tianjin Key Laboratory of Brain Science and Neuroengineering Tianjin China Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration Tianjin China

ISBN: (纸本)9798400718274

Accidents caused by explosives occur frequently, which seriously threaten people's lives and health, so it is urgent to develop new technologies for sensitively and rapidly detecting trace explosives. In this study, a bioengineered rat with the olfactory receptor (OR3) overexpression in the olfactory epithelium (OE) was successfully developed, and the unique features of three representative explosives (NT, DNT, and TNT) were conducted by recording electrophysiological-responsive signals from the olfactory bulb (OB) with implanted multichannel microelectrodes during awake-state-independent sniffing behavior induced by explosives and non-explosives. These three explosives were regarded as goal odors, while citral and air were no-goal odors. The analysis of local field potential (LFP) power changes revealed that, goal, and no-goals could be distinguished in both the vector group and the OR3 group at concentrations as low as 10-12 mol/L, and the classification performance of the OR3 group was superior to that of the vector group overall. Our findings suggest that OR3 bioengineered rats can reliably and accurately identify trace explosives, which provides a novel approach for detecting and identifying explosives with promising applications in odor discrimination in complex environments. Copyright © 2024 held by the owner/author(s). Publication rights licensed to ACM.

关键词： Electronic nose

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An EEG Method to Identify Image Preference With an Explicit/Implicit Task Brain-computer Interface

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IEEE Transactions on Affective Computing 2025年

作者： Li, Yulei Li, Shuyi Qi, Hongzhi Tianjin University Academy of Medical Engineering and Translational Medicine Tianjin300072 China Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration Tianjin300092 China Tianjin Key Laboratory of Brain Science and Neuroengineering Tianjin300072 China

Accurately determining an individual's preference for images remains a major challenge in the field of emotional research. This study proposes a novel paradigm for identifying individual image preferences using electroencephalography (EEG) signals and brain-computer interface (BCI). The paradigm involves both explicit and implicit tasks, where participants perform a typical event-related potential-based brain-computer interface(ERP-BCI) operation and their subjective image preferences are identified, respectively. Two experiments with a total of 27 participants demonstrate that event-related potential (ERP) signals during explicit BCI tasks are significantly influenced by target image preferences, enabling high-accuracy image preference recognition. Online experiments selecting positive and negative preference images from a candidate pool show top-1 accuracy approaching 100% and top-3 accuracy exceeding 90%. These results indicate the effectiveness of the proposed EEG-based image preference recognition paradigm, laying the groundwork for preference analysis applications. © 2010-2012 IEEE.

关键词： Brain mapping

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Cross-session motor imagery-electroencephalography decoding with Riemannian spatial filtering and domain adaptation

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Shengwu Yixue Gongchengxue Zazhi/Journal of Biomedical Engineering 2025年第2期42卷 272-279页

作者： Pan, Lincong Sun, Xinwei Wang, Kun Cao, Yupei Xu, Minpeng Ming, Dong Academy of Medical Engineering and Translational Medicine Tianjin University Tianjin300072 China School of Precision Instruments and Opto-Electronic Engineering Tianjin University Tianjin300072 China Haihe Laboratory of Brain-computer Interaction and Human-machine Integration Tianjin300392 China

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 © 2025 West China Hospital, Sichuan Institute of Biomedical Engineering. All rights reserved.

关键词： Brain computer interface

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Using non-invasive brain stimulation to modulate performance in visuomotor rotation adaptation: A scoping review

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Cortex;a journal devoted to the study of the nervous system and behavior 2025年 187卷 144-158页

作者： Long Chen Yipeng Liu Zhongpeng Wang Lei Zhang Shengcui Cheng Dong Ming Academy of Medical Engineering and Translational Medicine Tianjin University Tianjin China Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration Tianjin China. Electronic address: cagor@***. Academy of Medical Engineering and Translational Medicine Tianjin University Tianjin China. Electronic address: ***@***. Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration Tianjin China. Electronic address: tunerl_wzp1@***. Academy of Medical Engineering and Translational Medicine Tianjin University Tianjin China. Academy of Medical Engineering and Translational Medicine Tianjin University Tianjin China. Electronic address: richardming@***.

As research on the visuomotor rotation (VMR) adaptation expands its scope from behavioral science to encompass neuropsychological perspectives, an increasing number of studies have employed non-invasive brain stimulation (NIBS) techniques to explore the specific contributions of different neural structures to VMR adaptation. Despite early studies suggesting that cerebellar stimulation influenced the rate of adaptation and that stimulating primary motor cortex led to an enhanced retention of newly learned adaptation, subsequent studies could not always achieve consistent results. To probe this inconsistency, we systematically comb through past studies and extract numerous details, including paradigm designs, context settings, and modulation protocols in this scoping review. In summary, the paradigm design primarily serves two purposes: to dissociate implicit and explicit adaptation and to assess the retention of motor memory, whilst context settings such as apparatus, movement-related parameters and the information provided for subjects may complicate the modulated neuropsychological processes. We also conclude key NIBS parameters such as target regions and timing in stimulation protocols. Furthermore, we recognize the potential of neurophysiological biomarkers to support future VMR studies that incorporate NIBS and advocate for the use of several newly emerging NIBS techniques to enrich the field.

关键词： Methodology Motor learning Non-invasive brain stimulation Sensorimotor integration Visuomotor adaptation

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Enhancing motor imagery EEG classification with a Riemannian geometry-based spatial filtering (RSF) method

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Neural Networks 2025年 188卷 107511页

作者： Pan, Lincong Wang, Kun Huang, Yongzhi Sun, Xinwei Meng, Jiayuan Yi, Weibo Xu, Minpeng Jung, Tzyy-Ping Ming, Dong Academy of Medical Engineering and Translational Medicine Tianjin University Tianjin 300072 China School of Precision Instruments and Optoelectronics Engineering Tianjin University Tianjin 300072 China Haihe Laboratory of Brain-computer Interaction and Human-machine Integration Tianjin 300392 China Tianjin Key Laboratory of Brain Science and Neuroengineering Tianjin 300072 China Beijing Machine and Equipment Institute Beijing 100192 China Swartz Center for Computational Neuroscience University of California San DiegoCA92093 United States

Motor imagery (MI) refers to the mental simulation of movements without physical execution, and it can be captured using electroencephalography (EEG). This area has garnered significant research interest due to its substantial potential in brain-computer interface (BCI) applications, especially for individuals with physical disabilities. However, accurate classification of MI EEG signals remains a major challenge due to their non-stationary nature, low signal-to-noise ratio, and sensitivity to both external and physiological noise. Traditional classification methods, such as common spatial pattern (CSP), often assume that the data is stationary and Gaussian, which limits their applicability in real-world scenarios where these assumptions do not hold. These challenges highlight the need for more robust methods to improve classification accuracy in MI-BCI systems. To address these issues, this study introduces a Riemannian geometry-based spatial filtering (RSF) method that projects EEG signals into a lower-dimensional subspace, maximizing the Riemannian distance between covariance matrices from different classes. By leveraging the inherent geometric properties of EEG data, RSF enhances the discriminative power of the features while maintaining robustness against noise. The performance of RSF was evaluated in combination with ten commonly used MI decoding algorithms, including CSP with linear discriminant analysis (CSP-LDA), Filter Bank CSP (FBCSP), Minimum Distance to Riemannian Mean (MDM), Tangent Space Mapping (TSM), EEGNet, ShallowConvNet (sCNN), DeepConvNet (dCNN), FBCNet, Graph-CSPNet, and LMDA-Net, using six publicly available MI-BCI datasets. The results demonstrate that RSF significantly improves classification accuracy and reduces computational time, particularly for deep learning models with high computational complexity. These findings underscore the potential of RSF as an effective spatial filtering approach for MI EEG classification, providing new insight

关键词： Covariance matrix

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TMNRED, A Chinese Language EEG Dataset for Fuzzy Semantic Target Identification in Natural Reading Environments

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Scientific Data 2025年第1期12卷 1-14页

作者： Bai, Yanru Tang, Qi Zhao, Ran Liu, Hongxing Zhang, Shuming Guo, Mingkun Guo, Minghan Wang, Junjie Wang, Changjian Xing, Mu Ni, Guangjian Ming, Dong Academy of Medical Engineering and Translational Medicine Tianjin University Tianjin 300072 China Tianjin Key Laboratory of Brain Science and Neuroengineering Tianjin 300072 China Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration Tianjin 300392 China National University of Defense Technology Hunan Changsha 410000 China

Semantic understanding is central to advanced cognitive functions, and the mechanisms by which the brain processes language information are still being explored. Existing EEG datasets often lack natural reading data specific to Chinese, limiting research on Chinese semantic decoding and natural language processing. This study aims to construct a Chinese natural reading EEG dataset, TMNRED, for semantic target identification in natural reading environments. TMNRED was collected from 30 participants reading sentences sourced from public internet resources and media reports. Each participant underwent 400–450 trials in a single day, resulting in a dataset with over 10 hours of continuous EEG data and more than 4000 trials. This dataset provides valuable physiological data for studying Chinese semantics and developing more accurate Chinese natural language processing models. © The Author(s) 2025.

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