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检索条件"机构=Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration"

共 55 条记录，以下是21-30 订阅

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Astrocytic TRPA1 as a target in reversing social avoidance by low-intensity focused ultrasound stimulation in mice 46

Astrocytic TRPA1 as a target in reversing social avoidance b...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Wei, Ganjiang Wang, Ling Zhu, Jingnan Wang, Xiao Zang, Yuran Yang, Jiajia Zheng, Chenguang Tianjin University Academy of Medical Engineering and Translational Medicine Medical College 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)9798350371499

Social avoidance is a prominent clinical feature of multiple neuropsychiatric disorders. Increasing evidence showed that the medial prefrontal cortex (mPFC) regulates social avoidance with suppression of excitatory neurons. Our previous study found that the low-intensity focused ultrasound (LIFUS), as a novel noninvasive neuromodulation technique, could alleviate the social avoidance of social defeat stress (SDS) model mice by increasing the mPFC excitation. However, the underlying target of LIFUS on mPFC neurons in social defeated mice remains unclear. Here we injected AAV-shRNA to knock down astrocytic TRPA1 in the mPFC, and investigated whether astrocytic TRPA1 played a crucial role in LIFUS modulation. We found that the social avoidance of SDS mice with TRPA1 knocked down was not affected by LIFUS. Furthermore, LIFUS didn't induce enhanced expression of membrane NMDAR2A and NMDAR2B in SDS mice with TRPA1 knocked down, compared with that in mice infected with the control virus. It is believed that LIFUS can act on astrocytic TRPA1 to improve social avoidance and hence synaptic function. © 2024 IEEE.

关键词： Ultrasonics

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Firing Pattern of Cells in the Hippocampus and Basolateral Amygdala during Novelty Recognition 46

Firing Pattern of Cells in the Hippocampus and Basolateral A...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Ren, Xiaoxin Wang, Yimeng Wang, Ling Yang, Jiajia Zheng, Chenguang Tianjin University Academy of Medical Engineering and Translational Medicine Medical College 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)9798350371499

Novelty recognition is essential for exploring and collecting unknown but interesting information, in which multiple brain regions related to cognitive memory are involved. Dorsal hippocampus (dHPC) is revealed to be closely associated with spatial memory and basolateral amygdala (BLA) is reported recently to be related to state-dependent encoding of exploratory behavior. However, how the firing pattern of cells in these two brain regions responds to novelty dynamically remains unclear. In this study, we observed that the representations of cells in BLA exhibited shift towards novelty, whereas dHPC cells maintained strong stability after the introduction of novelty, which are both engaged in the execution of novel recognition. Our study may provide new evidence for underlying the internal mechanisms of perception of novelty in the brain. © 2024 IEEE.

关键词： brain

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The Pattern of CA1 c-Fos Expressing Place Cells Correlates with Learning Progression 46

The Pattern of CA1 c-Fos Expressing Place Cells Correlates w...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Wang, Ning Zhang, Anqi Yang, Jiajia Wang, Ling Zheng, Chenguang Tianjin University Academy of Medical Engineering and Translational Medicine Medical College 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)9798350371499

Spatial memory supported by the hippocampus is a critical cognitive function in daily life. It helps us to navigate to salient goal locations. Hippocampal place cells stably represent the spatial location, while c-Fos-expressing cells (engram cells) contain rich information about the environment, contributing to the encoding and retrieving of memories. However, the role of cFos as a gateway to a more profound comprehension of the mechanisms underlying the process of goal-oriented spatial memory remained poorly understood. In this study, we labeled rats' c-Fos+ neurons by Channelrhodopsin-2 during memory encoding of a specific goal location. A subset of place cells whether they expressed c-Fos was identified optogenetically. As the rats learned the new goal locations, the spatial correlation between task periods remained stable for the c-Fos- place cell, while increased for the c-Fos+ place cell. This finding shed light on the processing of goal-oriented spatial memories by the hippocampal network involved in c-Fos. C-Fos- place cells consistently maintained a stable representation of the locations, while c-Fos+ place cells exhibited significant flexibility of the goal. © 2024 IEEE.

关键词： Signal encoding

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Riemannian Geometry-Based Spatial Filtering (RSF) Method for Motor Imagery EEG Classification 24

Riemannian Geometry-Based Spatial Filtering (RSF) Method for...

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9th International Conference on Biomedical Signal and Image Processing, ICBIP 2024

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

ISBN: (纸本)9798400717970

Motor imagery (MI) is a mental process without actual movement, which can be recognized by electroencephalogram (EEG). Effective pre-processing and feature extraction methods are essential for improving the performance of MI-EEG classification. This paper proposes a novel Riemannian geometry-based spatial filtering (RSF) method, which projects the MI-EEG signals onto a lower-dimensional subspace that maximizes the Riemannian distance between the covariance matrices of different classes. The paper evaluates the performance of RSF on a public dataset (Pan2023) and applies it to several common classification algorithms, such as common spatial pattern (CSP), filter bank CSP (FBCSP), tangent space linear discriminant analysis (TS-LDA), ShallowNet, DeepNet, EEGNet and Graph-CSPNet. The results show that RSF can significantly improve the classification accuracy of these algorithms, and reduce the subsequent computation time cost, especially for those neural network algorithms with complex structures. These results indicate that RSF is an efficient spatial filtering method for MI-EEG classification, and provides a new perspective and method for EEG-based applications. © 2024 Copyright held by the owner/author(s).

关键词： Covariance matrix

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Study on the Temporal Patterns of CA1 Pyramidal Neuron Activity in Mice Hippocampus under Simulated Spaceflight Composite Environment 46

Study on the Temporal Patterns of CA1 Pyramidal Neuron Activ...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Sun, Shufan Ren, Jing Zhao, Meiling Wang, Ling Zheng, Chenguang Yang, Jiajia Ming, Dong Academy of Medical Engineering and Translational Medicine Tianjin University Brain-Computer Interaction and Human-Machine Fusion Haihe Laboratory Tianjin University Tianjin Key Laboratory of Brain Science and Neural Engineering Tianjin University Tianjin 300072 China

ISBN: (纸本)9798350371499

With the gradual realization of manned spaceflight goals, the physical and mental health of astronauts has become a core concern. Numerous studies in recent years have indicated that the aerospace special environment (ASE) can lead to alterations in astronaut cognitive function. However, the adaptive changes in neuronal activity underlying these alterations remain unclear. This study utilized animal models and two-photon imaging technology to investigate the adaptive changes in the activity characteristics and synchronicity of pyramidal neurons in the CA1 region of the mice hippocampus under simulated spaceflight composite environment (SSCE). The results indicate that, with prolonged modeling time, the number of active pyramidal neurons in the CA1 region gradually decreases. Significant reductions in both the frequency and amplitude of neuronal calcium transients occur, stabilizing at lower levels. The calcium transient decay constant extends, and significant decorrelation in neuronal calcium activity is observed. Thus, we posit that these changes may constitute crucial factors leading to the alterations in individual cognitive function induced by the aerospace special environment. © 2024 IEEE.

关键词： Mammals

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Improving EEG-Based Cross-Subject Mental Workload Classification Performance with Euclidean-Aligned Periodic and Aperiodic Features

Improving EEG-Based Cross-Subject Mental Workload Classifica...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Tao Wang Yufeng Ke Feng He Dong Ming Academy of Medical Engineering and Translational Medicine Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration Tianjin China

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Enhancing the cross-subject classification performance of EEG-based mental workload (MWL) monitoring models poses a significant challenge. Traditional methods require gathering calibration data for new users to prevent performance decline. However, the calibration data collection process is time-consuming and labor-intensive. In this study, we proposed a novel cross-subject MWL classification model that does not require calibration data. Specifically, we used periodic and aperiodic components obtained through EEG spectrum decomposition as features, replacing the commonly used power spectral density (PSD) features. These features are then aligned across subjects using a modified Euclidean alignment method. Our results show that the aligned periodic and aperiodic combined features achieve the highest classification accuracy (0.791±0.077), significantly surpassing raw PSD features without alignment (0.731±0.086, p<0.05). Moreover, we found a significantly negative correlation between inter-subject distances calculated from periodic features in resting-state data and inter-subject pairwise classification accuracy (r=-0.472, p<0.001). This finding suggests a promising approach to leverage resting-state data for selecting source subjects that closely match the target subjects.

关键词： Accuracy Correlation Data collection brain modeling Electroencephalography Data models Calibration Engineering in medicine and biology Monitoring

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Low intensity focused ultrasound stimulation targeted on M1 ameliorates neuroinflammation in hemi-parkinsonian rats 46

Low intensity focused ultrasound stimulation targeted on M1 ...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Li, Chunchan Sun, Tianyi Liang, Rong Yang, Zihui Yang, Weifan Li, Wanzhe Yin, Yiwei Zhang, Guanglu Wang, Ling Yang, Jiajia He, Feng Ming, Dong Academy of Medical Engineering and Translational Medicine Tianjin University Brain-Computer Interaction and Human-Machine Fusion Haihe Laboratory Tianjin University Tianjin Key Laboratory of Brain Science and Neural Engineering Tianjin University Tianjin 300072 China

ISBN: (纸本)9798350371499

Objective: Low intensity focused stimulation (LIFUS) has been proved to improve motor function in Parkinson's disease (PD) animal modules. The aim of this study is to investigate whether LIFUS target on the primary motor cortex (M1) can improve motor deficit in the PD rats. Methods: The PD rat model was induced by injection of 6-hydroxydopamine (6-OHDA) in the medial forebrain bundle (MFB). Two weeks after the injection, LIFUS was used on PD rats for two weeks. Behavioral tests were performed including open field test and rotarod test to examine the motor ability of the rats. The activity of microglia and astrocyte were tested to evaluate the inflammation level in the brain. The tyrosine hydroxylase (TH) staining was done to detect the recovery of dopaminergic (DA) neurons in the substantia nigra (SN) and DA fibers in the striatum (STR). Results: LIFUS treatment decreased the resting time in OFT(p © 2024 IEEE.

关键词： Neurodegenerative diseases

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Transcriptomic Study of Neural Regulation in the Medial Prefrontal Cortex of Depressive Mice with Low-Intensity Focused Ultrasound 46

Transcriptomic Study of Neural Regulation in the Medial Pref...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Cai, Qiuquan Meng, Lianghui Wang, Ling Ren, Jing Yang, Jiajia Ming, Dong Academy of Medical Engineering and Translational Medicine Tianjin University Tianjin 300072 China Brain-Computer Interaction and Human-Machine Fusion Haihe Laboratory Tianjin University Tianjin 300072 China Tianjin Key Laboratory of Brain Science and Neural Engineering Tianjin University Tianjin 300072 China

ISBN: (纸本)9798350371499

Exploring new effective treatments for depression holds important social significance and clinical value. Low-intensity focused ultrasound stimulation (LIFUS) has been proven to have significant neuroprotective effects on depression. However, the specific genes regulated by LIFUS in depressive mice remain unclear. We established a depression mice model using chronic restraint stress (CRS) and applied LIFUS to the medial prefrontal cortex (mPFC) following CRS. We explored the impact of modeling and treatment on gene expression changes through transcriptomics, revealing that the therapeutic effect of LIFUS may be associated with the improvement of the activity of calcium signaling pathway and synaptic plasticity. The study provides preclinical evidence and a theoretical basis for applying LIFUS for depression treatment. © 2024 IEEE.

关键词： Mammals

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Interpretable SincNet-Based Spatiotemporal Neural Network for Seizure Prediction

Interpretable SincNet-Based Spatiotemporal Neural Network fo...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Baolian Shan Haiqing Yu Hanzhe Jiang Yongzhi Huang Minpeng Xu 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

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Spatiotemporal convolutional neural networks (CNNs) have emerged as potent tools for seizure prediction (SP) using electroencephalogram (EEG) signals, probing spatiotemporal biomarkers in epileptic brains. Nevertheless, it poses significant challenges for clinical practice due to the poor interpretability of learned features and the numerous trainable parameters in existing CNNs. To improve the interpretability and performance, this study proposed an interpretable SincNet-based architecture for spatiotemporal CNNs, encompassing EEGNet-8,2, ShallowConvNet, DeepConvNet, and EEGWaveNet, enabling direct visualization of the bandpass temporal filter range using a sinc-convolution layer. Furthermore, we also constructed a visualization analysis method to demonstrate the crucial spatiotemporal features learned by the proposed optimal CNN. Results on the CHB-MIT dataset revealed that both ShallowConvNet and EEGWaveNet had significantly improved performance with more lightweight parameters. Notably, the architecture enabled ShallowConvNet to achieve an average accuracy of 87.2%, sensitivity of 88.3%, weighted F1-score of 87.1%, and AUC of 92.7% for 21 epilepsy patients. Besides, the visualization outcomes underscored the ability of the optimal model to extract statistically significant spatiospectral energy differences within high-frequency EEG bands for SP classification tasks.

关键词： Band-pass filters Visualization Sensitivity Accuracy Epilepsy Motors Feature extraction Electroencephalography Spatiotemporal phenomena Convolutional neural networks

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Transcutaneous auricular vagus nerve stimulation does not modulate working memory capacity but alters pupillary responses in the change detection task

Transcutaneous auricular vagus nerve stimulation does not mo...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Jingxin Chen Yufeng Ke Guangjian Ni 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

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Transcutaneous vagus nerve stimulation (taVNS) offers an effective, non-invasive alternative to implantable vagus nerve stimulation and it is considered to be a promising cognitive modulation tool. However, at present, the effect of taVNS on working memory is not clear, Simultaneously, the potential pupillary responses stemming from taVNS require more empirical inquiry. Herein, we investigated the influence of taVNS on working memory capacity and its link to pupillary responses during the change detection task. A sham-controlled, randomized, crossover-designed experiment was applied to 16 participants. Within each session, participants received a Sham or Active taVNS stimulation for 12 minutes and then achieved 3 blocks of change detection task. Each trial exceeds for 5s. The pupil and behavior responses were recorded during the task. We hypothesized that Active taVNS can improve the performance of the change detection task and influence the pupil corresponding to different numbers of target stimuli. For the results, we observed no significant modulation of working memory capacity by taVNS but did note distinct alterations in pupillary response (mean amplitude and extremes) during specified intervals in the change detection task. These findings point to an underexplored avenue of research into the neural or psychological processes affected by taVNS and provides a new insight for taVNS to modulate working memory capacity.

关键词： Memory management Modulation Psychology Pupils Engineering in medicine and biology

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