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IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Ryohei Terada Hiroaki Hirai Kosei Sasaki Hirokazu Kuga Keisuke Furukawa Kazuhiro Matsui Atsushi Nishikawa Hermano Igo Krebs Department of Mechanical Science and Bioengineering Graduate School of Engineering Science Osaka University Toyonaka Japan Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge USA Department of Neurology University of Maryland School of Medicine Baltimore USA Department of Physical Medicine and Rehabilitation Fujita Health University Nagoya Japan Department of System Design Engineering Keio University Tokyo Japan The Wolfson School of Engineering Loughborough University Loughborough UK Programme Bioengineering Applied Science and Intelligent Systems University Campus Bio-Medico of Rome Rome Italy Healthcare Engineering Innovation Center (HEIC) Khalifa University of Science and Technology Abu Dhabi UAE Department of Mechanical Science and Bioengineering Osaka University Toyonaka Japan

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Background and Aim: A push-off event is a significant gait phase that contributes to initiating the swing leg and propelling the body forward. This study aims to explore a method for estimating push-off initiation, focusing on pelvic and saddle-seat motion peculiar to saddle-seat-type body-weight-supported (BWS) treadmill walking. Methods: The pelvic/saddle-seat rotation and ground reaction force during saddle-seat-type BWS treadmill walking were measured using an IMU sensor and a force plate in the treadmill, respectively. The hypothesis posits that the transverse rotational displacement of the pelvis and saddle seat aids in estimating push-off initiation. Results: The analysis results show that (1) the timing estimated from transverse pelvic rotation moderately agreed with push-off initiation timing (Spearman's rank correlation coefficient $\rho=0.59, \mathrm{p} < 0.01)$ , and (2) the timing estimated from transverse saddle rotation strongly agreed with push-off initiation timing $(\rho=0.67,\mathrm{p} < 0.01)$ . Conclusions: The utilization of a single IMU sensor requires a minimal setup for identifying push-off initiation, which contributes to reducing time, effort, and costs in clinical settings. This preliminary study using intact subjects should be a meaningful first step in the research for gait rehabilitation with saddle-seat-type BWS.

关键词： Legged locomotion Training Force measurement Force Focusing Propulsion Robot sensing systems Timing Pelvis Rotation measurement

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Clinical utility of Epstein-Barr virus DNA and other liquid biopsy markers in nasopharyngeal carcinoma

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Cancer Communications 2020年第11期40卷 564-585页

作者： Rong Tan Sean Kean Ann Phua Yoke Lim Soong Lynette Lin Ean Oon Kian Sing Chan Sasidharan Swarnalatha Lucky Jamie Mong Min Han Tan Chwee Ming Lim Yong Loo Lin School of Medicine National University of SingaporeSingapore 117599Singapore Department of Radiation Oncology National Cancer CenterSingapore 169608Singapore Department of Molecular Pathology Singapore General HospitalSingapore 169608Singapore Institute of Bioengineering and Nanotechnology Singapore 138669Singapore Department of Otorhinolaryngology-Head and Neck Surgery Singapore General HospitalSingapore 169608Singapore Lucence Diagnostics Singapore 159552Singapore Surgery Academic Clinical Programme Duke-NUS Graduate Medical SchoolSingapore 169857Singapore

Nasopharyngeal carcinoma(NPC)is a malignant epithelial tumor ubiquitously associated with the Epstein-Barr virus(EBV),which is highly prevalent in South China,Southeast Asia,and North *** being a highly radio-sensitive and treatable cancer,a majority of NPC patients are diagnosed in their advanced stage,and locoregional and distant relapses following definitive treatment contribute largely to cancer-specific mortality among these *** that EBV-driven NPC is the predominant variant seen in endemic regions,various EBV detection methods have been developed and are utilized in screening,prognostication,and post-treatment surveillance of NPC *** the Immunoglobulin A(IgA)serology assay is the most extensively studied EBV detection method,the detection of plasma EBV DNA released during replication or cellular apoptosis has shown superior outcomes in endemic population screening,prognostication,and detection of distant ***,there is emerging evidence on the use of circulating tumor cells,microRNAs,DNA hypermethylation,and combination assays in various clinical ***,this paper provides a comprehensive overview of the relevant studies using various EBV detection techniques in the management of ***,the recent advances,clinical evidence,and challenges associated with the clinical application of EBV liquid biopsies in population screening,prognostication,and surveillance of NPC are presented.

关键词： circulating tumor cells EBV DNA Epstein-Barr virus microRNA nasopharyngeal carcinoma prognosis screening serology surveillance

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Changing the public perception of human embryology ( vol 25, pg 1717, 2023)

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NATURE CELL BIOLOGY 2023年第12期25卷 1884-1884页

作者： Rivron, Nicolas C. Martinez-Arias, Alfonso Sermon, Karen Mummery, Christine Scholer, Hans R. Wells, James Nichols, Jenny Hadjantonakis, Anna-Katerina Lancaster, Madeline A. Moris, Naomi Fu, Jianping Sturmey, Roger G. Niakan, Kathy Rossant, Janet Kato, Kazuto Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA) Vienna BioCenter (VBC) Vienna Austria Systems Bioengineering MELIS Universidad Pompeu Fabra and Catalan Institution for Research and Advanced Studies (ICREA) Barcelona Spain Research Group Reproduction and Genetics Vrije Universiteit Brussel Brussels Belgium European Society for Human Reproduction and Embryology (ESHRE) Strombeek-Bever Belgium Leiden University Medical Center Leiden the Netherlands Max Planck Institute for Molecular Biomedicine Münster Germany Center for Stem Cell and Organoid Medicine Cincinnati Children’s Hospital Medical Center Cincinnati OH USA Division of Developmental Biology Cincinnati Children’s Hospital Medical Center Cincinnati OH USA MRC Human Genetics Unit Institute of Genetics and Cancer The University of Edinburgh Crewe Road Edinburgh UK Developmental Biology Program Sloan Kettering Institute Memorial Sloan Kettering Cancer Center New York NY USA MRC Laboratory of Molecular Biology Cambridge UK The Francis Crick Institute London UK Department of Mechanical Engineering University of Michigan Ann Arbor MI USA Department of Biomedical Engineering University of Michigan Ann Arbor MI USA Department of Cell & Developmental Biology University of Michigan Medical School Ann Arbor MI USA Biomedical Institute for Multimorbidity Hull York Medical School University of Hull Hull UK Cambridge Reproduction University of Cambridge Cambridge UK The Centre for Trophoblast Research Department of Physiology Development and Neuroscience University of Cambridge Cambridge UK Human Embryo and Stem Cell Laboratory The Francis Crick Institute London UK Wellcome Trust–Medical Research Council Stem Cell Institute University of Cambridge Jeffrey Cheah Biomedical Centre Cambridge UK Epigenetics Programme Babraham Institute Cambridge UK The Hospital for Sick Children Toronto ON Canada Department of Biomedical Ethics and Public Policy Graduate School of Medicin

Human embryology is flourishing thanks to an impetus provided by embryo models formed from stem cells. These scientific advances require meticulous experimental work and a refined ethical framework, but also sensible ... 详细信息

关键词： Embryology Embryonic stem cells

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Alteration in Foot Strike Pattern While Running with Elastic Insoles: Case Study on the Effects of Long-term Training

Alteration in Foot Strike Pattern While Running with Elastic...

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IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Ryo Fujihara Kohei Kozasa Hiroaki Hirai Hermano Igo Krebs Graduate School of Engineering Science Osaka University Toyonaka Japan Programme Bioengineering & Biosciences University Campus Bio-Medico of Rome Rome Italy

ISBN: (纸本)9781538681848

Motor adaptation is a form of motor learning that involves changes in the control of movements that occur as a consequence of optimization in repeated task exposure or practice. A good example of this can be found in human running. It is thought that humans run in accordance with the presence or absence and shape of shoes. Three foot strike patterns exist in running, classified according to which portion of the sole first connects with the ground: RFS (rear-foot-strike; heel connection), MFS (mid-foot-strike, simultaneous heel and toe connections), and FFS (fore-foot-strike; toe, or ball connection). RFS is often seen in runners wearing shoes, whereas FFS is commonly seen during routine barefoot running. This study examined how humans adapt to assistive footwear (environmental exposure)s throughout approximately one month of running training. We found that the shape and stiffness of a modified insole affected the foot, functioning as a spring during running. As training continued, the subject adapted to the structure of the footwear by altering his foot strike pattern while reducing his heart rate. The foot strike pattern changed from heel contact to contact from the side of the toe or arch, and the pattern of the ground reaction force changed from that of RFS to that of FFS or MFS. These results indicate that the change in foot compliance while landing and during grounding affects the foot strike pattern to improve the efficiency and capability of running through long-term training.

关键词： Foot Training Footwear Radio frequency Heart rate Force Kinematics

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Alteration in Foot Strike Pattern while Running with Elastic Insoles: Case Study on the Effects of Long-term Training 7

Alteration in Foot Strike Pattern while Running with Elastic...

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7th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, BIOROB 2018

作者： Fujihara, Ryo Kozasa, Kohei Hirai, Hiroaki Krebs, Hermano Igo Osaka University Graduate School of Engineering Science Toyonaka Japan Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge United States Department of Neurology University of Maryland School of Medicine Baltimore United States Department of Physical Medicine and Rehabilitation Fujita Health University Nagoya Japan Institute of Neuroscience Newcastle University Newcastle-upon-Tyne United Kingdom Wolfson School of Engineering Loughborough University Loughborough United Kingdom Programme Bioengineering and Biosciences University Campus Bio-Medico of Rome Rome Italy Department of Mechanical Science and Bioengineering Osaka University Osaka Japan

ISBN: (纸本)9781538681831

Motor adaptation is a form of motor learning that involves changes in the control of movements that occur as a consequence of optimization in repeated task exposure or practice. A good example of this can be found in human running. It is thought that humans run in accordance with the presence or absence and shape of shoes. Three foot strike patterns exist in running, classified according to which portion of the sole first connects with the ground: RFS (rear-foot-strike;heel connection), MFS (mid-foot-strike, simultaneous heel and toe connections), and FFS (fore-foot-strike;toe, or ball connection). RFS is often seen in runners wearing shoes, whereas FFS is commonly seen during routine barefoot running. This study examined how humans adapt to assistive footwear (environmental exposure)s throughout approximately one month of running training. We found that the shape and stiffness of a modified insole affected the foot, functioning as a spring during running. As training continued, the subject adapted to the structure of the footwear by altering his foot strike pattern while reducing his heart rate. The foot strike pattern changed from heel contact to contact from the side of the toe or arch, and the pattern of the ground reaction force changed from that of RFS to that of FFS or MFS. These results indicate that the change in foot compliance while landing and during grounding affects the foot strike pattern to improve the efficiency and capability of running through long-term training. © 2018 IEEE.

关键词： Biophysics

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Considering discrepancy when calibrating a mechanistic electrophysiology model

arXiv

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arXiv 2020年

作者： Lei, Chon Lok Ghosh, Sanmitra Whittaker, Dominic G. Aboelkassem, Yasser Beattie, Kylie A. Cantwell, Chris D. Delhaas, Tammo Houston, Charles Novaes, Gustavo Montes Panfilov, Alexander V. Pathmanathan, Pras Riabiz, Marina Weber dos Santos, Rodrigo Worden, Keith Mirams, Gary R. Wilkinson, Richard D. Computational Biology & Health Informatics Dept. of Computer Science University of Oxford United Kingdom MRC Biostatistics Unit University of Cambridge United Kingdom Centre for Mathematical Medicine & Biology School of Mathematical Sciences University of Nottingham United Kingdom Department of Bioengineering University of California San Diego United States Systems Modeling and Translational Biology GlaxoSmithKline R&D Stevenage United Kingdom ElectroCardioMaths Programme Centre for Cardiac Engineering Imperial College London United Kingdom CARIM School for Cardiovascular Diseases Maastricht University Netherlands Graduate Program in Computational Modeling Universidade Federal de Juiz de Fora Brazil Department of Physics and Astronomy Ghent University Belgium Laboratory of Computational Biology and Medicine Ural Federal University Ekaterinburg Russia U.S. Food and Drug Administration Center for Devices and Radiological Health Office of Science and Engineering Laboratories United States Department of Biomedical Engineering King’s College London Alan Turing Institute United Kingdom Dynamics Research Group Department of Mechanical Engineering University of Sheffield United Kingdom School of Mathematics and Statistics University of Sheffield United Kingdom

Uncertainty quantification (UQ) is a vital step in using mathematical models and simulations to take decisions. The field of cardiac simulation has begun to explore and adopt UQ methods to characterise uncertainty in model inputs and how that propagates through to outputs or predictions. In this perspective piece we draw attention to an important and under-addressed source of uncertainty in our predictions — that of uncertainty in the model structure or the equations themselves. The difference between imperfect models and reality is termed model discrepancy, and we are often uncertain as to the size and consequences of this discrepancy. Here we provide two examples of the consequences of discrepancy when calibrating models at the ion channel and action potential scales. Furthermore, we attempt to account for this discrepancy when calibrating and validating an ion channel model using different methods, based on modelling the discrepancy using Gaussian processes (GPs) and autoregressive-moving-average (ARMA) models, then highlight the advantages and shortcomings of each approach. Finally, suggestions and lines of enquiry for future work are provided. Copyright © 2020, The Authors. All rights reserved.

关键词： Uncertainty analysis

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Technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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A mechanistic model of connector hubs, modularity, and cognition

arXiv

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arXiv 2018年

作者： Bertolero, Maxwell A. Yeo, B. T. Thomas Bassett, Danielle S. D'Esposito, Mark Helen Wills Neuroscience Institute Department of Psychology University of California BerkeleyCA94720-3190 United States Department of Bioengineering School of Engineering and Applied Sciences University of Pennsylvania PhiladelphiaPA19104 United States Electrical and Computer Engineering ASTAR-NUS Clinical Imaging Research Centre Singapore Institute for Neurotechnology & Memory Networks Programme National University of Singapore Singapore119077 Singapore NUS Graduate School for Integrative Sciences and Engineering National University of Singapore Singapore Department of Electrical & Systems Engineering School of Engineering and Applied Sciences University of Pennsylvania PhiladelphiaPA19104 United States Department of Physics & Astronomy College of Arts and Sciences University of Pennsylvania PhiladelphiaPA19104 United States Department of Neurology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA19104 United States

The human brain network is modular-comprised of communities of tightly interconnected nodes1. This network contains local hubs, which have many connections within their own communities, and connector hubs, which have connections diversely distributed across communities2,3. A mechanistic understanding of these hubs and how they support cognition has not been demonstrated. Here, we leveraged individual differences in hub connectivity and cognition. We show that a model of hub connectivity accurately predicts the cognitive performance of 476 individuals in four distinct tasks. Moreover, there is a general optimal network structure for cognitive performance- individuals with diversely connected hubs and consequent modular brain networks exhibit increased cognitive performance, regardless of the task. Critically, we find evidence consistent with a mechanistic model in which connector hubs tune the connectivity of their neighbors to be more modular while allowing for task appropriate information integration across communities, which increases global modularity and cognitive performance. Copyright © 2018, The Authors. All rights reserved.

关键词： Structural optimization

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The repertoire of mutational signatures in human cancer (vol 578, pg 94, 2020)

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NATURE 2023年第7948期614卷 E41-E41页

作者： Alexandrov, Ludmil B. Kim, Jaegil Haradhvala, Nicholas J. Huang, Mi Ni Ng, Alvin Wei Tian Wu, Yang Boot, Arnoud Covington, Kyle R. Gordenin, Dmitry A. Bergstrom, Erik N. Islam, S. M. Ashiqul Lopez-Bigas, Nuria Klimczak, Leszek J. McPherson, John R. Morganella, Sandro Sabarinathan, Radhakrishnan Wheeler, David A. Mustonen, Ville Getz, Gad Rozen, Steven G. Stratton, Michael R. Department of Cellular and Molecular Medicine Department of Bioengineering Moores Cancer Center University of California San Diego CA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Cellular and Molecular Medicine and Department of Bioengineering University of California San Diego La Jolla CA USA UC San Diego Moores Cancer Center San Diego CA USA University of California San Diego San Diego CA USA Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Massachusetts General Hospital Boston MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama Japan Computational Biology Program Ontario Institute for Cancer Research Toronto ON Canada Programme in Cancer & Stem Cell Biology Duke-NUS Medical School Singapore Singapore Centre for Computational Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Centre for Computational Biology Duke-NUS Medical School Singapore Singapore SingHealth Duke-NUS Institute of Precision Medicine National Heart Centre Singapore Singapore Singapore Cancer Science Institute of Singapore National University of Singapore Singapore Singapore Institute of Molecular and Cell Biology Singapore Singapore Laboratory of Cancer Epigenome Division of Medical Science National Cancer Centre Singapore Singapore Singapore Duke-NUS Medical School Singapore Singapore Human Genome Sequencing Center Baylor College of Medicine Houston TX USA Dan L. Duncan Cancer Center Baylor College of Medicine Houston TX USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Genome Integrity and Structural Biology Laboratory National Ins

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Modeling distinct sources of neural variability driving neuroprosthetic control

Modeling distinct sources of neural variability driving neur...

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

作者： Preeya Khanna Vivek R. Athalye Suraj Gowda Rui M. Costa Jose M. Carmena UC Berkeley-UCSF Graduate Group in Bioengineering University of California Berkeley CA USA Champalimaud Neuroscience Programme Instituto Gulbenkian de Ciência Oeiras Portugal Department of Electrical Engineering and Computer Sciences University of California Berkeley Berkeley CA USA Department of Electrical Engineering and Computer Sciences University of California Berkeley CA USA

Many closed-loop, continuous-control brain-machine interface (BMI) architectures rely on decoding via a linear readout of noisy population neural activity. However, recent work has found that decomposing neural population activity into correlated and uncorrelated variability reveals that improvements in cursor control coincide with the emergence of correlated neural variability. In order to address how correlated and uncorrelated neural variability arises and contributes to BMI cursor control, we simulate a neural population receiving combinations of shared inputs affecting all cells and private inputs affecting only individual cells. When simulating BMI cursor-control with different populations, we find that correlated activity generates faster, straighter cursor trajectories, yet sometimes at the cost of inaccuracies. We also find that correlated variability can be generated from either shared inputs or quickly updated private inputs. Overall, our results suggest a role for both correlated and uncorrelated neural activity in cursor control, and potential mechanisms by which correlated activity may emerge.

关键词： Sociology Statistics Decoding Trajectory Neurons Calibration Data models

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