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arXiv 2024年

作者： Ferreira, Fabio S. Ashburner, John Bouzigues, Arabella Suksasilp, Chatrin Russell, Lucy L. Foster, Phoebe H. Ferry-Bolder, Eve van Swieten, John C. Jiskoot, Lize C. Seelaar, Harro Sanchez-Valle, Raquel Laforce, Robert Graff, Caroline Galimberti, Daniela Vandenberghe, Rik de Mendonça, Alexandre Tiraboschi, Pietro Santana, Isabel Gerhard, Alexander Levin, Johannes Sorbi, Sandro Otto, Markus Pasquier, Florence Ducharme, Simon Butler, Chris R. Le Ber, Isabelle Finger, Elizabeth Tartaglia, Maria Carmela Masellis, Mario Rowe, James B. Synofzik, Matthis Moreno, Fermin Borroni, Barbara Kaski, Samuel Rohrer, Jonathan D. Mourão-Miranda, Janaina Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom Max Planck University College London Centre for Computational Psychiatry and Ageing Research University College London United Kingdom Wellcome Centre for Human Neuroimaging University College London London United Kingdom Dementia Research Centre Department of Neurodegenerative Disease UCL Queen Square Institute of Neurology London United Kingdom Institute of Cognitive Neuroscience University College London London United Kingdom Department of Neurology Erasmus Medical Centre Rotterdam Netherlands Alzheimer's Disease and Other Cognitive Disorders Unit Neurology Service Hospital Clinic Institut d'Investigacions Biomediques August Pi I Sunyer University of Barcelona Barcelona Spain Clinique Interdisciplinaire de Memoire Departement des Sciences Neurologiques CHU de Quebec Faculte de Medecine Universite Laval QC Canada Department of Neurobiology Care Sciences and Society Center for Alzheimer Research Division of Neurogeriatrics Bioclinicum Karolinska Institutet Solna Sweden Fondazione Ca Granda IRCCS Ospedale Policlinico Milan Italy Laboratory for Cognitive Neurology Department of Neurosciences KU Leuven Leuven Belgium Faculty of Medicine University of Lisbon Lisbon Portugal Fondazione IRCCS Istituto Neurologico Carlo Besta Milano Italy Neurology Service Faculty of Medicine University of Coimbra Coimbra Portugal Division of Psychology Communication and Human Neuroscience Wolfson Molecular Imaging Centre University of Manchester Manchester United Kingdom Department of Neurology Ludwig-Maximilians Universitat Munchen Munich Germany Department of Neurofarba University of Florence Italy Department of Neurology University of Ulm Germany Univ Lille France Douglas Mental Health University Institute Department of Psychiatry McGill University Montreal Canada Nuffield Department of Clinical Neurosciences Medical Sciences Division University of

In this study, we propose a novel approach to uncover subgroup-specific and subgroup-common latent factors addressing the challenges posed by the heterogeneity of neurological and mental disorders, which hinder disease understanding, treatment development, and outcome prediction. The proposed approach, sparse Group Factor Analysis (GFA) with regularised horseshoe priors, was implemented with probabilistic programming and can uncover associations (or latent factors) among multiple data modalities differentially expressed in sample subgroups. Synthetic data experiments showed the robustness of our sparse GFA by correctly inferring latent factors and model parameters. When applied to the Genetic Frontotemporal Dementia Initiative (GENFI) dataset, which comprises patients with frontotemporal dementia (FTD) with genetically defined subgroups, the sparse GFA identified latent disease factors differentially expressed across the subgroups, distinguishing between "subgroup-specific" latent factors within homogeneous groups and "subgroup common" latent factors shared across subgroups. The latent disease factors captured associations between brain structure and non-imaging variables (i.e., questionnaires assessing behaviour and disease severity, neuropsychological tasks and medical assessments of disease severity) across the different genetic subgroups, offering insights into disease profiles. Importantly, two latent factors were more pronounced in the two more homogeneous FTD patient subgroups (progranulin (GRN) and microtubule-associated protein tau (MAPT) mutation), showcasing the method's ability to reveal subgroup-specific characteristics. These findings underscore the potential of sparse GFA for integrating multiple data modalities and identifying interpretable latent disease factors that can improve the characterization and stratification of patients with neurological and mental health disorders. © 2024, CC BY-NC-ND.

关键词： Brain mapping

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The Free Energy Principle drives neuromorphic development

arXiv

引用

arXiv 2022年

作者： Fields, Chris Friston, Karl Glazebrook, James F. Levin, Michael Marcianò, Antonino 23 Rue des Lavandières Caunes Minervois 11160 France Allen Discovery Center Tufts University MedfordMA02155 United States Wellcome Centre for Human Neuroimaging University College London LondonWC1N 3AR United Kingdom Department of Mathematics and Computer Science Eastern Illinois University CharlestonIL61920 United States Adjunct Faculty Department of Mathematics University of Illinois at Urbana-Champaign UrbanaIL61801 United States Wyss Institute for Biologically Inspired Engineering Harvard University BostonMA02115 United States Center for Field Theory and Particle Physics Department of Physics Fudan University Shanghai China Laboratori Nazionali di Frascati INFN Frascati Rome Italy INFN sezione Roma Tor Vergata RomeI-00133 Italy

We show how any system with morphological degrees of freedom and locally limited free energy will, under the constraints of the free energy principle, evolve toward a neuromorphic morphology that supports hierarchical computations in which each "level" of the hierarchy enacts a coarse-graining of its inputs, and dually a fine-graining of its outputs. Such hierarchies occur throughout biology, from the architectures of intracellular signal transduction pathways to the large-scale organization of perception and action cycles in the mammalian brain. Formally, the close formal connections between cone-cocone diagrams (CCCD) as models of quantum reference frames on the one hand, and between CCCDs and topological quantum field theories on the other, allow the representation of such computations in the fully-general quantum- computational framework of topological quantum neural networks. Copyright © 2022, The Authors. All rights reserved.

关键词： Free energy

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Genome assembly and transcriptome analysis provide insights into the antischistosome mechanism of Microtus fortis

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Journal of Genetics and Genomics 2020年第12期47卷 743-755页

作者： Hong Li Zhen Wang Shumei Chai Xiong Bai Guohui Ding Yuanyuan Li Junyi Li Qingyu Xiao Benpeng Miao Weili Lin Jie Feng Mingyue Huang Cheng Gao Bin Li Wei Hu Jiaojiao Lin Zhiqiang Fu Jianyun Xie Yixue Li Bio-Med Big Data Center CAS Key Laboratory of Computational BiologyShanghai Institute of Nutrition and HealthUniversity of Chinese Academy of SciencesChinese Academy of SciencesShanghai 200031China Shanghai Veterinary Research Institute Chinese Academy of Agricultural SciencesKey Laboratory of Animal ParasitologyMinistry of AgricultureShanghai 200241China Shanghai Laboratory Animal Research Center Shanghai 201203China Institute for Digital Health International Human Phenome Institutes(Shanghai)Shanghai 200433China Shanghai Center for Bioinformation Technology Shanghai Academy of Science and TechnologyShanghai 201203China School of Computer Science and Technology Harbin Institute of Technology(Shenzhen)ShenzhenGuangdong 518055China Shanghai Institute of Immunology Department of Immunology and MicrobiologyShanghai JiaoTong University School of MedicineShanghai 200025China State Key Laboratory of Genetic Engineering Ministry of Education Key Laboratory of Contemporary AnthropologyCollaborative Innovation Center for Genetics and DevelopmentSchool of Life SciencesFudan UniversityShanghai 200438China Hangzhou Institute for Advanced Study University of Chinese Academy of SciencesHangzhouZhejiang 330106China

Microtus fortis is the only mammalian host that exhibits intrinsic resistance against Schistosoma japonicum ***,the underlying molecular mechanisms of this resistance are not yet ***,we perform the first de novo genome assembly of ***,comprehensive gene annotation analysis,and evolution ***,we compare the recovery rate of schistosomes,pathological changes,and liver transcriptomes between *** and mice at different time points after *** observe that the time and type of immune response in *** are different from those in *** activates immune and inflammatory responses on the 10th day post infection,such as leukocyte extravasation,antibody activation,Fc-gamma receptor-mediated phagocytosis,and the interferon signaling cascade,which play important roles in preventing the development of *** contrast,an intense immune response occurrs in mice at the late stages of infection and could not eliminate *** mice suffer severe pathological injury and continuous decreases in cell cycle,lipid metabolism,and other *** findings offer new insights into the intrinsic resistance mechanism of *** against schistosome *** genome sequence also provides the basis for future studies of other important traits in ***.

关键词： Genome assembly Microtus fortis Schistosome Immune Transcriptome

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A labanotation based ontology for representing Vietnamese folk dances 3

A labanotation based ontology for representing Vietnamese fo...

引用

3rd International Conference on Digital Arts, Media and Technology, ICDAMT 2018

作者： Chau, Ma Thi Thuy, Nguyen Thanh Human Machine Interaction Laboratory University of Engineering and Technology Hanoi Viet Nam Computer Science Department University of Engineering and Technology Hanoi Viet Nam

ISBN: (纸本)9781509052097

This paper aims at designing and constructing an ontology, representing and allowing Vietnamese folk dances annotation. An effective approach proposed is based on movement analysis. It is possible to divide Vietnamese folk dances into basic units, then movement phrases, movement primitives and dance poses. Studying deeply Vietnamese folk dances features and characteristics allows to find out 5 different types of relationships between main dance components. Typical relationships could be written in the form of logical predicates. For enriching ontologies, a formal encoding of the ontology expertise knowledge in the domain is performed by DL-Lite. The paper uses OWL-2 for building, organizing and visualizing ontologies. A case study-Mo folk dance with a knowledge base, is structured simply but effectively, with reasoning in DL-Lite and answering queries in SPARQL. © 2018 IEEE.

关键词： Ontology

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A conceptual framework of cognitive-affective theory of mind: towards a precision identification of mental disorders

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Npj mental health research 2023年第1期2卷 12页

作者： Peng Zhou Huimin Ma Bochao Zou Xiaowen Zhang Shuyan Zhao Yuxin Lin Yidong Wang Lei Feng Gang Wang School of International Studies Zhejiang University Hangzhou China. School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China. mhmpub@***. School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China. Department of Foreign Languages and Literatures Tsinghua University Beijing China. Department of Electronic Engineering Tsinghua University Beijing China. National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders Beijing Anding Hospital Capital Medical University Beijing China. Advanced Innovation Center for Human Brain Protection Capital Medical University Beijing China.

To explore the minds of others, which is traditionally referred to as Theory of Mind (ToM), is perhaps the most fundamental ability of humans as social beings. Impairments in ToM could lead to difficulties or even deficits in social interaction. The present study focuses on two core components of ToM, the ability to infer others' beliefs and the ability to infer others' emotions, which we refer to as cognitive and affective ToM respectively. Charting both typical and atypical trajectories underlying the cognitive-affective ToM promises to shed light on the precision identification of mental disorders, such as depressive disorders (DD) and autism spectrum disorder (ASD). However, most prior studies failed to capture the underlying processes involved in the cognitive-affective ToM in a fine-grained manner. To address this problem, we propose an innovative conceptual framework, referred to as visual theory of mind (V-ToM), by constructing visual scenes with emotional and cognitive meanings and by depicting explicitly a four-stage process of how humans make inferences about the beliefs and emotions of others. Through recording individuals' eye movements while looking at the visual scenes, our model enables us to accurately measure each stage involved in the computation of cognitive-affective ToM, thereby allowing us to infer about potential difficulties that might occur in each stage. Our model is based on a large sample size (n > 700) and a novel audio-visual paradigm using visual scenes containing cognitive-emotional meanings. Here we report the obtained differential features among healthy controls, DD and ASD individuals that overcome the subjectivity of conventional questionnaire-based assessment, and therefore could serve as valuable references for mental health applications based on AI-aided digital medicine.

关键词： human behaviour Diagnostic markers Psychiatric disorders

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Considerations and recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 3 — Ex vivo imaging: data processing, comparisons with microscopy, and tractography

arXiv

引用

arXiv 2024年

作者： Schilling, Kurt G. Howard, Amy F.D. Grussu, Francesco Ianus, Andrada Hansen, Brian Barrett, Rachel L.C. Aggarwal, Manisha Michielse, Stijn Nasrallah, Fatima Syeda, Warda Wang, Nian Veraart, Jelle Roebroeck, Alard Bagdasarian, Andrew F. Eichner, Cornelius Sepehrband, Farshid Zimmermann, Jan Soustelle, Lucas Bowman, Christien Tendler, Benjamin C. Hertanu, Andreea Jeurissen, Ben Verhoye, Marleen Frydman, Lucio van de Looij, Yohan Hike, David Dunn, Jeff F. Miller, Karla Landman, Bennett A. Shemesh, Noam Anderson, Adam McKinnon, Emilie Farquharson, Shawna Dell' Acqua, Flavio Pierpaoli, Carlo Drobnjak, Ivana Leemans, Alexander Harkins, Kevin D. Descoteaux, Maxime Xu, Duan Huang, Hao Santin, Mathieu D. Grant, Samuel C. Obenaus, Andre Kim, Gene S. Wu, Dan Le Bihan, Denis Blackband, Stephen J. Ciobanu, Luisa Fieremans, Els Bai, Ruiliang Leergaard, Trygve B. Zhang, Jiangyang Dyrby, Tim B. Johnson, G. Allan Cohen-Adad, Julien Budde, Matthew D. Jelescu, Ileana O. Radiology and Radiological Sciences Vanderbilt University Medical Center NashvilleTN United States Vanderbilt University Institute of Imaging Science Vanderbilt University NashvilleTN United States Department of Bioengineering Imperial College London London United Kingdom FMRIB Centre Wellcome Centre for Integrative Neuroimaging Nuffield Department of Clinical Neurosciences University of Oxford Oxford United Kingdom Radiomics Group Vall d’Hebron Institute of Oncology Vall d’Hebron Barcelona Hospital Campus Barcelona Spain Queen Square MS Centre Queen Square Institute of Neurology Faculty of Brain Sciences University College London London United Kingdom Champalimaud Research Champalimaud Foundation Lisbon Portugal Center of Functionally Integrative Neuroscience Aarhus University Aarhus Denmark Department of Neuroimaging Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom NatBrainLab Department of Forensics and Neurodevelopmental Sciences Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom Russell H. Morgan Department of Radiology and Radiological Science Johns Hopkins University School of Medicine BaltimoreMD United States Maastricht University Medical Center Maastricht Netherlands The Queensland Brain Institute The University of Queensland Queensland Australia Melbourne Neuropsychiatry Centre The University of Melbourne ParkvilleVIC Australia Department of Radiology and Imaging Sciences Indiana University IN United States Stark Neurosciences Research Institute Indiana University School of Medicine IN United States Center for Biomedical Imaging NYU Grossman School of Medicine New YorkNY United States Faculty of psychology and Neuroscience Maastricht University Maastricht Netherlands Department of Chemical & Biomedical Engineering FAMU-FSU College of Engineering Florida State University TallahasseeFL United States Center for Interdisciplinary Magnetic Res

Preclinical diffusion MRI (dMRI) has proven value in methods development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. While dMRI enables in vivo non-invasive characterization of tissue, ex vivo dMRI is increasingly being used to probe tissue microstructure and brain connectivity. Ex vivo dMRI has several experimental advantages that facilitate high spatial resolution and high signal-to-noise ratio (SNR) images, cutting-edge diffusion contrasts, and direct comparison with histological data as a methodological validation. However, there are a number of considerations that must be made when performing ex vivo experiments. The steps from tissue preparation, image acquisition and processing, and interpretation of results are complex, with many decisions that not only differ dramatically from in vivo imaging of small animals, but ultimately affect what questions can be answered using the data. This work concludes a 3-part series of recommendations and considerations for preclinical dMRI. Herein, we describe best practices for dMRI of ex vivo tissue, with a focus on image pre-processing, data processing and model fitting, and tractography. In each section, we attempt to provide guidelines and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should lie. We end by providing guidelines on code sharing and data sharing, and point towards open-source software and databases specific to small animal and ex vivo imaging. © 2024, CC BY.

关键词： Data Sharing

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Moving towards informative and actionable social media research

arXiv

引用

arXiv 2025年

作者： Bak-Coleman, Joseph B. Lewandowsky, Stephan Lorenz-Spreen, Philipp Narayanan, Arvind Orben, Amy Oswald, Lisa Centre for the Advanced Study of Collective Behavior University of Konstanz Konstanz Germany Department of Collective Behavior Max Planck Institute of Animal Behavior Konstanz Germany Department of Biology University of Konstanz Konstanz Germany Santa Fe Institute Santa FeNM United States Berkman Klein Center Harvard University CambridgeMA United States School of Psychological Science University of Bristol Bristol United Kingdom Department of Psychology University of Potsdam Potsdam Germany Center Synergy of Systems Center for Scalable Data Analytics and Artificial Intelligence Dresden University of Technology Dresden Germany Center for Adaptive Rationality Max Planck Institute for Human Development Berlin Germany Center for Information Technology Policy Princeton University PrincetonNJ United States Department of Computer Science Princeton University PrincetonNJ United States MRC Cognition and Brain Sciences Unit University of Cambridge Cambridge United Kingdom

Social media is nearly ubiquitous in modern life, and concerns have been raised about its putative societal impacts, ranging from undermining mental health and exacerbating polarization to fomenting violence and disrupting democracy. Despite extensive research, consensus on these effects remains elusive, with observational studies often highlighting concerns while randomized controlled trials (RCTs) yield conflicting or null findings. This review examines how the complexity inherent in social systems can account for such discrepancies, emphasizing that emergent societal and long-term outcomes cannot be readily inferred from individual-level effects. In complex systems, such as social networks, feedback loops, hysteresis, multi-scale dynamics, and non-linearity limit the utility of approaches for assessing causality that are otherwise robust in simpler contexts. Revisiting large-scale experiments, we explore how null or conflicting findings may reflect these complexities rather than a true absence of effects. Even in cases where the methods are appropriate, assessing the net impacts of social media provides little actionable insight given that eliminating social media is not a realistic option for whole populations. We argue that progress will require a complexity-minded approach focused on specific design choices of online platforms that triangulates experimental, observational and theoretical methods. © 2025, CC BY.

关键词： Tweets

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Spot that Bird: A Location Based Bird Game

arXiv

引用

arXiv 2018年

作者： Mehta, Sneha Department of Computer Science Center for Human Computer Interaction Virginia Tech BlacksburgVA United States

In today’s age of pervasive computing and social media people make extensive use of technology for communicating, sharing media and learning. Yet while in the outdoors, on a hike or a trail we find ourselves inept of information about the natural world surrounding us. In this paper I present in detail the design and technological considerations required to build a location based mobile application for learning about the avian taxonomy present in the user’s surroundings. It is designed to be a game for better engagement and learning. The application makes suggestions for birds likely to be sighted in the vicinity of the user and requires the user to spot those birds and upload a photograph to the system. If spotted correctly the user scores points. I also discuss some design methods and evaluation approaches for the application. Copyright © 2018, The Authors. All rights reserved.

关键词： Crowdsourcing

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RFES: a real-time fire evacuation system for Mobile Web3D

引用

Frontiers of Information Technology & Electronic Engineering 2019年第8期20卷 1061-1075页

作者： Feng-ting YAN Yong-hao HU Jin-yuan JIA Qing-hua GUO He-hua ZHU Zhi-geng PAN School of Electronic and Electrical Engineering Shanghai University of Engineering ScienceShanghai201620China School of Software Engineering Tongji UniversityShanghai201804China School of Civil Engineering Tongji UniversityShanghai200092China Research Center of Digital Media and Human-Computer Interaction Hangzhou Normal UniversityHangzhou310013China

There are many bottlenecks that limit the computing power of the Mobile Web3 D and they need to be solved before implementing a public fire evacuation system on this *** this study,we focus on three key problems:(1)The scene data for large-scale building information modeling(BIM)are huge,so it is difficult to transmit the data via the Internet and visualize them on the Web;(2)The raw fire dynamic simulator(FDS)smoke diffusion data are also very large,so it is extremely difficult to transmit the data via the Internet and visualize them on the Web;(3)A smart artificial intelligence fire evacuation app for the public should be accurate and *** address these problems,the following solutions are proposed:(1)The large-scale scene model is made lightweight;(2)The amount of dynamic smoke is also made lightweight;(3)The dynamic obstacle maps established from the scene model and smoke data are used for optimal path planning using a heuristic *** propose a real-time fire evacuation system based on the ant colony optimization(RFES-ACO)algorithm with reused dynamic *** results show that the public could use Mobile Web3 D devices to experience fire evacuation drills in real time *** real-time fire evacuation system(RFES)is efficient and the evacuation rate is better than those of the other two algorithms,i.e.,the leader-follower fire evacuation algorithm and the random fire evacuation algorithm.

关键词： Fire evacuation drill Building information modeling(BIM)building space Mobile Web3D Real-time fire evacuation system based on ant colony optimization(RFES-ACO)algorithm

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C-3PO: Cyclic-three-phase optimization for human-robot motion retargeting based on reinforcement learning

arXiv

引用

arXiv 2019年

作者： Kim, Taewoo Lee, Joo-Haeng Department of Computer Software and Engineering Korea University of Science and Technology Daejeon Korea Republic of Human-Robot Interaction Research Group Electronics and Telecommunications Research Institute Daejeon Korea Republic of

— Motion retargeting between heterogeneous poly-morphs with different sizes and kinematic configurations requires a comprehensive knowledge of kinematics and inverse kinematics. Moreover, it is non-trivial to provide a kinematic independent general solution. In this study, we developed a cyclic three-phase optimization method based on deep reinforcement learning for human-robot motion retargeting. The motion retargeting and reward calculations were performed using refined data in a latent space by the cyclic and filtering paths of our method. In addition, the human-in-the-loop based three-phase approach provides a framework for the improvement of the motion retargeting policy by both quantitative and qualitative manners. Using the proposed C-3PO method, we were successfully able to learn the motion retargeting skill between the human skeleton and the real NAO, Pepper, Baxter and C-3PO robot motions. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep learning

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