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16th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2024

作者： Jin, Fuli Wang, Yinghui Shang, Zhigang School of Electrical and Information Engineering Zhengzhou University Zhengzhou450001 China Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology Zhengzhou450001 China

ISBN: (纸本)9798400717666

Decision-making is a complex cognitive process vital for the survival and adaptive behavior of species, and the neural mechanisms behind this behavior have been the focus of extensive *** striatum is a key region in the brain that plays a crucial role in the decision-making process, making it an ideal candidate for investigating the neural correlates of learning and *** study aims to explore the changes in the striatum and its local field potentials (LFPs) during the learning of decision-making, providing potential insights into the role of the striatum in decision-making in *** study simultaneously collected behavior data and striatal LFPs from 4 pigeons during a three-armed bandit *** pigeons' learning process, behavioral accuracy, reward probabilities, and"win-stay-lose-shift" characteristics were *** power changes in six different frequency bands of striatal LFPs between the early and late stages of learning were *** pigeons' learning process significantly modulated the power in the Beta frequency band, indicating its crucial role in ***, the power of the Theta, Alpha, and Beta bands correlated with choices suggesting a high reward probability, emphasizing the relationship between reward probability and the modulation of power in the *** study sheds light on the neural processes underlying decision-making in pigeons, demonstrating the modulation of LFP power in the striatum and its relationship to reward *** findings contribute to our understanding of decision-making processes in animals. © 2024 Copyright held by the owner/author(s).

关键词： Decision making

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Two-step Thompson Sampling for Multi-Armed Bandit Problem 43

Two-step Thompson Sampling for Multi-Armed Bandit Problem

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43rd Chinese Control Conference, CCC 2024

作者： Shang, Zhigang Yang, Lifang Li, Mengmeng Zhengzhou University School of Electrical and Information Engineering Zhengzhou450001 China Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology Zhengzhou450001 China

ISBN: (纸本)9789887581581

An important feature of sequential decision-making under uncertain conditions is to strike a balance between exploration (obtaining information about the value of actions) and utilization (selecting the best action based on existing knowledge). The multi-armed bandit is a classic task for balancing their relationship. As the agent has learnt the relationship between two options in a 2-armed bandit task, it will no longer explore but instead use them directly. Inspired by the research, an algorithm based on two-step Thompson sampling (T-TS) is proposed to solve multi-armed bandit problem. First, posterior Beta distributions for the reward of each arm and the probability of the superior arm were established respectively. In the first-step TS, Thompson sampling was used to extract the maximum value from the posterior distribution of probability for the superior arm, determining it as the selected arm. In the two-step TS, Thompson sampling was used to sample from the distributions of the reward. During the updating, the posterior distribution of the probability for the superior arm was updated based on observations including actions and reward, and the distribution of the reward was updated based on the reward feedback. We performed the comparative experiments to solve the static multi-bandit tasks with 10, 20, 40, and 80 arms respectively by the state-of-the-art B-UCB algorithm, Thompson sampling and the proposed T-TS. The results shown that our proposed T-TS can learn the superior action more quickly with the best robustness. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Importance sampling

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Superpixel-Based Hierarchical Graph Convolution for Enhanced Interpretability in Semantic Segmentation

Superpixel-Based Hierarchical Graph Convolution for Enhanced...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Dong, Yimeng Liu, Guangyao Yin, Yankai Wu, Mengxuan Duan, Feng Nankai University Tianjin Key Laboratory of Interventional Brain-Computer Interface and Intelligent Rehabilitation China School of Software Tiangong University China University of Texas at Rio Grande Valley Department of Communication Sciences and Disorders United States Nankai University Tianjin Key Laboratory of Interventional Brain-Computer Interface and Intelligent Rehabilitation Tianjin China

ISBN: (纸本)9781665481090

Despite the success of pixel-based black-box models in most semantic segmentation algorithms for autonomous driving technology, identifying the causes of recognition errors remains challenging. To address this issue, we propose a hierarchical graph convolutional semantic segmentation method based on superpixels. This approach employs a superpixel segmentation algorithm to convert the original image into graph-structured data with rich semantic information, which is then updated with a graph neural network that utilizes spatial relationships. Graph pooling aggregates results, while graph unpooling restores richer node information, leading to final semantic segmentation. The proposed method captures extensive node information and enhances the interpretability of semantic segmentation by demonstrating the process from pixels to superpixels, aggregated results, and ultimately semantic segmentation. Experimental results demonstrate that compared to GraphSAGE and TAGCN, our method improves the mean Intersection over Union by over 10% on the VOC2012 and Cityscapes datasets. This research provides a more interpretable and efficient approach to semantic segmentation in autonomous driving applications. © 2024 IEEE.

关键词： Semantic Segmentation

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Decomposition frequency optimization in wavelet-based template matching algorithms to manage P300 latency jitter 46

Decomposition frequency optimization in wavelet-based templa...

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

作者： Quattrociocchi, Ilaria Caracci, Valentina Riccio, Angela Galiotta, Valentina D'Ippolito, Mariagrazia Cincotti, Febo Toppi, Jlenia Astolfi, Laura Sapienza University of Rome Department of Computer Control and Management Engineering Italy Fondazione Santa Lucia Irccs Neuroelectrical Imaging and Brain Computer Interface Laboratory Rome Italy

ISBN: (纸本)9798350371499

Event-Related Potentials (ERPs) are modifications of the brain activity in response to external sensory stimulation. P300 is a positive ERP component that occurs 300 ms after the presentation of a rare stimulus and indicates conscious perception of an unexpected change in sensory stimulation. Since the amplitude of ERPs is comparable to that of background electroencephalography, the most widespread approach to render ERPs correctly detectable is time-domain averaging. ERPs are physiologically affected by variations in latency, referred to as latency jitter. The most promising techniques to address latency jitter are cross-correlation template matching algorithms, which estimate single-trial latencies and resynchronize them according to a template that best describes the ERP component. Adaptive Wavelet Filtering (AWF) is an algorithm applied in the wavelet domain to provide the optimal compromise of time-frequency resolution in detecting ERPs. The choice of an appropriate decomposition frequency is crucial in the application of AWF, as it is essential for identifying the correct template and estimating single-trial latencies. In this study, we investigated the influence of frequency on the performance of AWF to optimize it. The algorithm was tested on simulated data with varying latency shifts and signal-to-noise ratios as well as for data recorded from 11 healthy subjects during an auditory oddball paradigm. Results on both simulated and real EEG data showed how frequency decomposition of 3 Hz is the most appropriate for P300 waveform detection. © 2024 IEEE.

关键词： Template matching

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Active Learning for High-Quality Sawtooth Wave Dataset Generation in Sleep Analysis 6

Active Learning for High-Quality Sawtooth Wave Dataset Gener...

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6th International Conference on Frontier Technologies of Information and computer, ICFTIC 2024

作者： Chen, Jinghuang Bao, Xiaoyu Ye, Yuntao Huang, Qiyun School of Automation Science and Engineering South China University of Technology Guangzhou China Research Center for Brain-Computer Interface Pazhou Laboratory Guangzhou China

ISBN: (纸本)9798331541750

Sawtooth Waves (STW) that occur during Rapid Eye Movement (REM) sleep are closely associated with memory consolidation and the regulation of brain functions. However, due to challenges in data acquisition and the high cost of manual annotation, there is currently an absence of a publicly massive STW annotated dataset. This study focuses on constructing a high-quality STW dataset, comprising 4912 samples from 200 participants, and developing classification algorithms for STW detection. We utilized three prevalent algorithms-Support Vector Machine (SVM), Multilayer Perceptron (MLP), and Convolutional neural Network (CNN)-to assess the dataset's quality. The dataset achieved a maximum classification accuracy of 95.62% with the CNN, confirming the gold standard of STW dataset. Finally, we studied age and gender difference in physiological characteristics of STW, including average frequency of STW, peak-to-peak amplitude(PTP), root mean square(RMS) and spectrum power. This study created a public STW dataset and a STW detection model, laying the groundwork for analyzing the mechanisms of STW events. © 2024 IEEE.

关键词： Convolutional neural networks

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Developmental Impairments of Synaptic Refinement in the Thalamus of a Mouse Model of Fragile X Syndrome

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Neuroscience Bulletin 2024年第4期40卷 439-450页

作者： Xiaotong Wu Yali Liu Xiaomeng Wang Lu Zheng Libiao Pan Hao Wang Department of Neurosurgery of Second Affiliated Hospital and School of Brain Science and Brain Medicine Key Laboratory for Biomedical Engineering of Education MinistryZhejiang University School of MedicineHangzhou310058China Nanhu Brain-computer Interface Institute Hangzhou311100China NHC and CAMS Key Laboratory of Medical Neurobiology MOE Frontier Science Center for Brain Research and Brain Machine IntegrationKey Laboratory of Precise Treatment and Clinical Translational Research of Neurological DiseasesSchool of Brain Science and Brain MedicineZhejiang UniversityHangzhou310058China Lingang Laboratory Shanghai200031China

While somatosensory over-reactivity is a common feature of autism spectrum disorders such as fragile X syndrome(FXS),the thalamic mechanisms underlying this remain ***,we found that the developmental elimination of synapses formed between the principal nucleus of V(PrV)and the ventral posterior medial nucleus(VPm)of the somatosensory system was delayed in fragile X mental retardation 1 gene knockout(Fmr1 KO)mice,while the developmental strengthening of these synapses was *** showed excessive VGluT2 puncta in mutants at P12–13,but not at P7–8 or P15–16,confirming a delay in somatic pruning of PrV-VPm *** synaptic function was associated with a reduction in the frequency of quantal AMPA events,as well as developmental deficits in presynaptic vesicle size and *** results uncovered the developmental impairment of thalamic relay synapses in Fmr1 KO mice and suggest that a thalamic contribution to the somatosensory over-reactivity in FXS should be considered.

关键词： Fragile X syndrome Synaptic refinement VPm Sensory over-reactivity

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neural Circuitry Involving Substance P in Male Sexual Behavior

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Neuroscience Bulletin 2024年第4期40卷 544-546页

作者： Xinrong Wang Junqiang Zheng Han Xu Department of Neurobiology and Department of Neurology of the Second Affiliated Hospital and School of Brain Science and Brain Medicine Zhejiang University School of MedicineHangzhou310058China Nanhu Brain-Computer Interface Institute Hangzhou311100China Liangzhu Laboratory MOE Frontier Science Center for Brain Science and Brain-machine IntegrationState Key Laboratory of Brain-Machine IntelligenceZhejiang UniversityHangzhou311121China NHC and CAMS Key Laboratory of Medical Neurobiology Zhejiang UniversityHangzhou310058China Lingang Laboratory Shanghai200031China

Male sexual behavior is an innate social behavior crucial for reproduction[1].Previous studies have identified several brain regions crucial for the control of both sexual and aggressive behaviors in ***,molecularly specified neural circuits that specifically control male sexual behavior remain *** with the inherently rewarding nature of sexual behavior,previous research has implicated the role of the dopamine system in regulating sexual desire[2].However,the interaction between reward and copulation at the circuit level remains largely ***,it is unclear if the associated neural pathways are specific in modulating sexual reward.

关键词： behavior neural specified

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Preference detection of the humanoid robot face based on EEG and eye movement

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neural Computing and Applications 2024年第19期36卷 11603-11621页

作者： Wang, Pengchao Mu, Wei Zhan, Gege Wang, Aiping Song, Zuoting Fang, Tao Zhang, Xueze Wang, Junkongshuai Niu, Lan Bin, Jianxiong Zhang, Lihua Jia, Jie Kang, Xiaoyang Laboratory for Neural Interface and Brain Computer Interface Engineering Research Center of AI and Robotics Ministry of Education Shanghai Engineering Research Center of AI and Robotics MOE Frontiers Center for Brain Science State Key Laboratory of Medical Neurobiology Institute of AI and Robotics Academy for Engineering and Technology Fudan University Shanghai200433 China Ji Hua Laboratory Guangdong Province Foshan528200 China Department of Rehabilitation Medicine Huashan Hospital Fudan University Shanghai200040 China Yiwu Research Institute of Fudan University Zhejiang Yiwu322000 China Research Center for Intelligent Sensing Zhejiang Lab Hangzhou311121 China

The face of a humanoid robot can affect the user experience, and the detection of face preference is particularly important. Preference detection belongs to a branch of emotion recognition that has received much attention from researchers. Most of the previous preference detection studies have been conducted based on a single modality. In this paper, we detect face preferences of humanoid robots based on electroencephalogram (EEG) signals and eye movement signals for single modality, canonical correlation analysis fusion modality, and bimodal deep autoencoder (BDAE) fusion modality, respectively. We validated the theory of frontal asymmetry by analyzing the preference patterns of EEG and found that participants had higher alpha wave energy for preference faces. In addition, hidden preferences extracted by EEG signals were better classified than preferences from participants' subjective feedback, and also, the classification performance of eye movement data was improved. Finally, experimental results showed that BDAE multimodal fusion using frontal alpha and beta power spectral densities and eye movement information as features performed best, with the highest average accuracy of 83.13% for the SVM and 71.09% for the KNN. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Electroencephalography

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Role of the Thalamic Reticular Nucleus in Social Memory

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Neuroscience Bulletin 2025年第2期41卷 355-358页

作者： Xue Liu Jianing Zhu Junqiang Zheng Han Xu Department of Psychiatry of the Second Affiliated Hospital and School of Brain Science and Brain Medicine Zhejiang University School of MedicineHangzhou310058China Nanhu Brain-computer Interface Institute Hangzhou311100China College of Life Sciences Zhejiang UniversityHangzhou310058China Liangzhu Laboratory MOE Frontier Science Center for Brain Science and Brain-machine IntegrationState Key Laboratory of Brain-machine IntelligenceZhejiang UniversityHangzhou311121China NHC and CAMS Key Laboratory of Medical Neurobiology Zhejiang UniversityHangzhou310058China Lingang Laboratory Shanghai200031China

Social behaviors are crucial for gregarious animals,including *** order to exhibit appropriate behaviors in a complex social context,such as mating,aggression,avoidance,and cooperation,individuals need to remember their previous experiences with other members and accurately recognize them when they meet *** ability is called“social memory”[1].Many psychiatric disorders in humans,such as autism spectrum disorder,attention deficit hyperactivity disorder,and schizophrenia,are characterized by social memory *** with these disorders,along with corresponding animal models,often show defects associated with the thalamic reticular nucleus(TRN).The TRN,a thin layer of neurons surrounding the thalamus,mainly regulates and coordinates the transfer of information between the cortex and the thalamus,playing a role in higher brain functions such as consciousness,attention,and sensory ***,whether the TRN is involved in social memory remains unknown.

关键词： exhibit appropriate behaviors social behaviors mating social memory thalamic reticular nucleus gregarious animals autism spectrum disorderattention deficit hyperactivity disorderand psychiatric disorders

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Sex-Differential neural Circuits and Behavioral Responses for Empathy

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Neuroscience Bulletin 2025年第1期41卷 192-194页

作者： Jingkai Fan Xinrong Wang Han Xu Department of Psychiatry of the Second Affiliated Hospital and School of Brain Science and Brain Medicine Zhejiang University School of MedicineHangzhou310058China Nanhu Brain-computer Interface Institute Hangzhou311100China Liangzhu Laboratory MOE Frontier Science Center for Brain Science and Brain-machine IntegrationState Key Laboratory of Brain-machine IntelligenceZhejiang UniversityHangzhou311121China NHC and CAMS Key Laboratory of Medical Neurobiology Zhejiang UniversityHangzhou310058China Lingang Laboratory Shanghai200031China

Empathy is one of the most important abilities for social *** a world that is largely socially constructed,when encountering altered affective states of others,particularly negative states,individuals often exhibit evolutionarily conserved empathic behaviors,such as mirroring,consolation,and helping[l,2].Appropriate empathic behaviors can foster the consolidation of social *** studies have suggested that both male and female rodents show some empathic behaviors when facing affective conspecifics[1].However,the role of sex in different empathic behaviors remains largely ***,there is a need to probe whether animals show sex-dependent empathic behavior and which neural circuits modulate these distinct behaviors.

关键词： mirror largely behavior

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