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China's new ethical guidelines for the use of brain-computer interfaces

国家科学评论（英文版） 2024年第4期11卷 1-2页

作者： Mu-ming Poo Institute of Neuroscience CAS Center for Excellence in Brain Science and Intelligence TechnologyChina

While the world is bewildered by the dazzling advances of gen-erative artificial intelligence and struggling to find consensual guidelines for its governance,the rapid pace of research on the brain-computer interface(BCI)also calls for governance on its development and *** early February,China's Min-istry of science and technology(MoST)announced the'Guide-lines for Research Ethics in brain-computer Interface'[1]based on recommendations of the National Research Ethics *** content is largely in line with an earlier announcement in October 2023 by the Psychiatry Society of China[2]on'Ethics Governance of brain-Computer Interface Research in Mental Disorders'.Both guidelines are formulated on the principles of the World Medical Association Declaration of Helsinki on'Eth-ical Principles for Medical Research Involving Human Subjects'in 2008.

关键词： china brain-computer ethical guidelines interfaces

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Large language models and brain-inspired general intelligence

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National science Review 2023年第10期10卷 6-7页

作者： Bo Xu Mu-ming Poo Institute of Automation Chinese Academy of Sciences CAS Center for Excellence for Brain Science and Intelligence Technology

The emergence of large language models(LLMs) such as ChatGPT/GPT-4 and their stunning performance in generative tasks heralds the beginning of a new era of artificial general intelligence(AGI).The LLMs have shown amazing generalization ability in natural language processing,computer vision and other generative tasks [1].These models point to a feasible approach for developing *** a large extent,they have passed the classical Turing test and their capability is still growing without an upper bound identified.

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Editorial of non-human primate research

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National science Review 2023年第11期10卷 6-7页

作者： Mu-ming Poo CAS Center for Excellence for Brain Science and Intelligence Technology

The progress of biology and medicine over the past century has been greatly facilitated by research based on animal models that could be used for experimentation. Small animal models such as the nematode worm C. elegans and the fruit fly Drosophila played crucial roles in the development of genetics, embryology, and cell biology. The mouse has become the quintessential animal model in the past few decades, largely due to development of mouse lines that have acquired genetic homogeneity via inbreeding over many generations, and many transgenic mouse lines carrying modified genetic makeup are also available. Mouse lines mimicking a variety of human diseases caused by genetic mutations are widely used for studying pathogenic mechanisms and for testing the efficacy of therapeutic treatments prior to human clinical trials.

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Tuning Synaptic Connections Instead of Weights by Genetic Algorithm in Spiking Policy Network

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Machine intelligence Research 2024年第5期21卷 906-918页

作者： Duzhen Zhang Tielin Zhang Shuncheng Jia Qingyu Wang Bo Xu School of Artificial Intelligence University of Chinese Academy of SciencesBeijing100049China Institute of Automation Chinese Academy of Sciences(CAS)Beijing100190China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences(CAS)Shanghai200031China

Learning from interaction is the primary way that biological agents acquire knowledge about their environment and *** deep reinforcement learning(DRL)explores a computational approach to learning from interaction and has made significant progress in solving various ***,despite its power,DRL still falls short of biological agents in terms of energy *** the underlying mechanisms are not fully understood,we believe that the integration of spiking communication between neurons and biologically-plausible synaptic plasticity plays a prominent role in achieving greater energy *** this biological intuition,we optimized a spiking policy network(SPN)using a genetic algorithm as an energy-efficient alternative to *** SPN mimics the sensorimotor neuron pathway of insects and communicates through event-based *** by biological research showing that the brain forms memories by creating new synaptic connections and rewiring these connections based on new experiences,we tuned the synaptic connections instead of weights in the SPN to solve given *** results on several robotic control tasks demonstrate that our method can achieve the same level of performance as mainstream DRL methods while exhibiting significantly higher energy efficiency.

关键词： Spiking neural networks genetic evolution bio-inspired learning agent&cognitive architectures robotic control

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Whole-brain Mapping of Inputs and Outputs of Specific Orbitofrontal Cortical Neurons in Mice

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Neuroscience Bulletin 2024年第11期40卷 1681-1698页

作者： Yijie Zhang Wen Zhang Lizhao Wang Dechen Liu Taorong Xie Ziwei Le Xiangning Li Hui Gong Xiao-Hong Xu Min Xu Haishan Yao Institute of Neuroscience State Key Laboratory of NeuroscienceCAS Center for Excellence in Brain Science and Intelligence TechnologyChinese Academy of SciencesShanghai200031China University of Chinese Academy of Sciences Beijing100049China HUST-Suzhou Institute for Brainsmatics JITRISuzhou215123China CAS Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of SciencesShanghai200031China Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology Shanghai201210China Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology Shanghai200031China

The orbitofrontal cortex(ORB),a region crucial for stimulus-reward association,decision-making,and flexible behaviors,extensively connects with other brain ***,brain-wide inputs to projection-defined ORB neurons and the distribution of inhibitory neurons postsynaptic to neurons in specific ORB subregions remain poorly *** we mapped the inputs of five types of projection-specific ORB neurons and ORB outputs to two types of inhibitory *** found that different projection-defined ORB neurons received inputs from similar cortical and thalamic regions,albeit with quantitative variations,particularly in somatomotor areas and medial groups of the dorsal *** counting parvalbumin(PV)or somatostatin(SST)interneurons innervated by neurons in specific ORB subregions,we found a higher fraction of PV neurons in sensory cortices and a higher fraction of SST neurons in subcortical regions targeted by medial ORB *** results provide insights into understanding and investigating the function of specific ORB neurons.

关键词： Orbitofrontal cortex Projection specific Rabies virus retrograde tracing Anterograde transsynaptic virus tracing Inhibitory neurons

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Recent developments in multifunctional neural probes for simultaneous neural recording and modulation

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Microsystems & Nanoengineering 2023年第1期9卷 23-35页

作者： Hongbian Li Jinfen Wang Ying Fang CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety CAS Center for Excellence in NanoscienceNational Center for Nanoscience and TechnologyBeijing100190China CAS Center for Excellence in Brain Science and Intelligence Technology Institute of NeuroscienceChinese Academy of SciencesShanghai200031China

Neural probes are among the most widely applied tools for studying neural circuit functions and treating neurological *** the complexity of the nervous system,it is highly desirable to monitor and modulate neural activities simultaneously at the cellular *** this review,we provide an overview of recent developments in multifunctional neural probes that allow simultaneous neural activity recording and modulation through different modalities,including chemical,electrical,and optical *** will focus on the material and structural design of multifunctional neural probes and their interfaces with neural ***,future challenges and prospects of multifunctional neural probes will be discussed.

关键词： neural recording simultaneous

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China's new ethical guidelines for the use of brain±computer interfaces

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National science Review 2024年第4期 7-8页

作者： Mu-ming Poo Institute of Neuroscience CAS Center for Excellence in Brain Science and Intelligence Technology NSR

While the world is bewildered by the dazzling advances of generative artificial intelligence and struggling to find consensual guidelines for its governance, the rapid pace of research on the brain–computer interface (BCI) also calls for governance on its development and application. In early February, China’s Ministry of science and technology (Mo ST) announced the ‘Guidelines for Research Ethics in brain-computer Interface’[1] based on recommendations of the National Research Ethics Committee. Its content is largely in line with an earlier announcement in October 2023 by the Psychiatry Society of China [2] on ‘Ethics Governance of brain-Computer Interface Research in Mental Disorders’. Both guidelines are formulated on the principles of the World Medical Association Declaration of Helsinki on ‘Ethical Principles for Medical Research Involving Human Subjects’in 2008.

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Exemplar-Based Continual Learning via Contrastive Learning

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial intelligence 2024年第7期5卷 3313-3324页

作者： Chen, Shuai Zhang, Mingyi Zhang, Junge Huang, Kaiqi School of Artificial Intelligence Beijing100049 China Institute of Automation Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai200031 China

Despite the impressive performance of deep learning models, they suffer from catastrophic forgetting, which refers to a significant decline in overall performance when trained with new classes added incrementally. The primary reason for this phenomenon is the overlapping or confusion between the feature space representations of old and new classes. In this study, we examine this issue and propose a model that can mitigate the problem by learning more transferable features. We employ contrastive learning, a recent breakthrough in deep learning, which can learn visual representations better than the task-specific supervision method. Specifically, we introduce an exemplar-based continual learning (CL) method using contrastive learning to learn a task-agnostic and continuously improved feature expression. However, the class imbalance between old and new samples in CL can affect the final learned features. To address this issue, we propose two approaches. First, we use a novel exemplar-based method, called determinantal point processes experience replay (DPPER), to improve buffer diversity during memory update. Second, we propose an old sample compensation weight (CW) to resist the corruption of the old model caused by new task learning during memory retrieval. Our experimental results on benchmark datasets demonstrate that our approach outperforms state-of-the-art methods in terms of comparable performance. © 2020 IEEE.

关键词： Supervised learning

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The Neural Mechanism of Knowledge Assembly in the Human brain Inspires Artificial intelligence Algorithm

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Neuroscience Bulletin 2024年第2期40卷 280-282页

作者： Xiang Ji Wentao Jiang Xiaoru Zhang Ming Song Shan Yu Tianzi Jiang University of the Chinese Academy of Sciences Beijing 100049China Brainnetome Center Institute of AutomationThe Chinese Academy of SciencesBeijing 100190China Laboratory of Brain Atlas and Brain-inspired Intelligence Institute of AutomationThe Chinese Academy of SciencesBeijing 100190China CAS Center for Excellence in Brain Science and Intelligence Technology The Chinese Academy of SciencesBeijing 100190China Research Center for Augmented Intelligence Zhejiang LabHangzhou 311100China

When new information enters the brain,a human's prior knowledge of the world can change rapidly through a process referred to as"knowledge assembly".Recently,Nelli et *** the neural correlates of knowledge assembly in the human brain using functional ***,inspired by the neural mechanism,the authors developed an artificial neural network algorithm to permit rapid knowledge assembly,improving the flexibility of the system[1].Once again,this research demonstrates that studying how the brain works can lead to better computational algorithms.

关键词： neural knowledge artificial

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The Insular Cortex:An Interface Between Sensation,Emotion and Cognition

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Neuroscience Bulletin 2024年第11期40卷 1763-1773页

作者： Ruohan Zhang Hanfei Deng Xiong Xiao Institute of Neuroscience Key Laboratory of Brain Cognition and Brain-inspired Intelligence TechnologyCAS Center for Excellence in Brain Science and Intelligence TechnologyChinese Academy of SciencesShanghai200031China University of Chinese Academy of Sciences Shanghai200031China State Key Laboratory of Medical Neurobiology MOE Frontiers Center for Brain Science and Institutes of Brain ScienceFudan UniversityShanghai200032China

The insula is a complex brain region central to the orchestration of taste perception,interoception,emotion,and *** research has shed light on the intricate connections between the insula and other brain regions,revealing the crucial role of this area in integrating sensory,emotional,and cognitive *** unique anatomical position and extensive connectivity allow the insula to serve as a critical hub in the functional network of the *** summarize its role in interoceptive and exteroceptive sensory processing,illustrating insular function as a bridge connecting internal and external *** on recent research,we delineate the insular involvement in emotional processes,highlighting its implications in psychiatric conditions,such as anxiety,depression,and *** further discuss the insular contributions to cognition,focusing on its significant roles in time perception and ***,the evidence underscores the insular function as a dynamic interface that synthesizes diverse inputs into coherent subjective experiences and decision-making *** this review,we hope to highlight the importance of the insula as an interface between sensation,emotion,and cognition,and to inspire further research into this fascinating brain region.

关键词： Insular cortex Interoception Emotion Reward-Timing Decision making

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