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Advanced Methods for Connectome-Based Predictive Modeling of Human Intelligence: A Novel Approach Based on Individual Differences in Cortical Topography

arXiv

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arXiv 2022年

作者： Anderson, Evan D. Wilcox, Ramsey Nayak, Anuj Zwilling, Christopher Robles-Granda, Pablo Kim, Been Varshney, Lav R. Barbey, Aron K. Neuroscience Program University of Illinois UrbanaIL United States Department of Psychology University of Illinois UrbanaIL United States Department of Electrical & Computer Engineering University of Illinois UrbanaIL United States Beckman Institute University of Illinois UrbanaIL United States Department of Computer Science University of Illinois UrbanaIL United States Google Brain Mountan View CA United States

Individual differences in human intelligence can be modeled and predicted from in vivo neurobiological connectivity. Many established modeling frameworks for predicting intelligence, however, discard higher-order information about individual differences in brain network topology, and show only moderate performance when generalized to make predictions in out-of-sample subjects. In this paper, we propose that connectome-based predictive modeling, a common predictive modeling framework for neuroscience data, can be productively modified to incorporate information about brain network topology and individual differences via the incorporation of bagged decision trees and the network based statistic. These modifications produce a novel predictive modeling framework that leverages individual differences in cortical tractography to generate accurate regression predictions of intelligence scores. Network topology-based feature selection provides for natively interpretable networks as input features, increasing the model's explainability. Investigating the proposed modeling framework's efficacy, we find that advanced connectome-based predictive modeling generates neuroscience predictions that account for a significantly greater proportion of variance in general intelligence scores than previously established methods, advancing our scientific understanding of the network architecture that underlies human intelligence. © 2022, CC BY-SA.

关键词： Forecasting

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The challenges of measuring spin Seebeck noise

arXiv

引用

arXiv 2023年

作者： Luo, Renjie Zhao, Xuanhan Legvold, Tanner J. Chen, Liyang Liu, Changjiang Hong, Deshun Bhattacharya, Anand Natelson, Douglas Department of Physics and Astronomy Rice University HoustonTX77005 United States Applied Physics Program Smalley-Curl Institute Rice University HoustonTX77005 United States Materials Science Division Argonne National Laboratory LemontIL60439 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States

Just as electronic shot noise in driven conductors results from the granularity of charge and the statistical variation in the arrival times of charge carriers, there are predictions for fundamental noise in magnon currents due to angular momentum being carried by discrete excitations. The inverse spin Hall effect as a transduction mechanism to convert spin current into charge current raises the prospect of experimental investigations of such magnon shot noise. Spin Seebeck effect measurements have demonstrated the electrical detection of thermally driven magnon currents and have been suggested as an avenue for accessing spin current fluctuations. Using spin Seebeck structures made from yttrium iron garnet on gadolinium gallium garnet, we demonstrate the technical challenges inherent in such noise measurements. While there is a small increase in voltage noise in the inverse spin Hall detector at low temperatures associated with adding a magnetic field, the dependence on field orientation implies that this is not due to magnon shot noise. We describe theoretical predictions for the expected magnitude of magnon shot noise, highlighting ambiguities that exist. Further, we show that magnon shot noise detection through the standard inverse spin Hall approach is likely impossible due to geometric factors. Implications for future attempts to measure magnon shot noise are discussed. Copyright © 2023, The Authors. All rights reserved.

关键词： Shot noise

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Magneto-optics in a van der Waals magnet tuned by self-hybridized polaritons

arXiv

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arXiv 2023年

作者： Dirnberger, Florian Quan, Jiamin Bushati, Rezlind Diederich, Geoffrey Florian, Matthias Klein, Julian Mosina, Kseniia Sofer, Zdenek Xu, Xiaodong Kamra, Akashdeep García-Vidal, Francisco J. Alù, Andrea Menon, Vinod M. Department of Physics City College of New York New YorkNY10031 United States Department of Physics The Graduate Center City University of New York New YorkNY10016 United States Photonics Initiative CUNY Advanced Science Research Center New YorkNY10031 United States Department of Electrical Engineering City College of the City University of New York New YorkNY10031 United States Intelligence Community Postdoctoral Research Fellowship Program University of Washington SeattleWA United States Department of Physics Department of Materials Science and Engineering University of Washington SeattleWA United States Department of Electrical and Computer Engineering Department of Physics University of Michigan Ann ArborMI48109 United States Department of Materials Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Inorganic Chemistry University of Chemistry and Technology Prague Technickaá 5 Prague 6166 28 Czech Republic Universidad Autónoma de Madrid MadridE- 28049 Spain

Controlling quantum materials with light is of fundamental and technological importance. By utilizing the strong coupling of light and matter in optical cavities [1–3], recent studies were able to modify some of their most defining features [4–6]. In this work, we study the magneto-optical properties of a van der Waals magnet that supports strong coupling of photons and excitons even in the absence of external cavity mirrors. In this material – the layered magnetic semiconductor CrSBr – emergent light-matter hybrids called polaritons are shown to significantly increase the spectral bandwidth of correlations between the magnetic, electronic, and optical properties, enabling largely tunable optical responses to applied magnetic fields and magnons. Our results highlight the importance of exciton-photon self-hybridization in van der Waals magnets and motivate novel directions for the manipulation of quantum material properties by strong light-matter coupling. © 2023, CC BY.

关键词： Van der Waals forces

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QUBIQ: Uncertainty Quantification for biomedical Image Segmentation Challenge

arXiv

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arXiv 2024年

作者： Li, Hongwei Bran Navarro, Fernando Ezhov, Ivan Bayat, Amirhossein Das, Dhritiman Kofler, Florian Shit, Suprosanna Waldmannstetter, Diana Paetzold, Johannes C. Hu, Xiaobin Wiestler, Benedikt Zimmer, Lucas Amiranashvili, Tamaz Prabhakar, Chinmay Berger, Christoph Weidner, Jonas Alonso-Basanta, Michelle Rashid, Arif Baid, Ujjwal Adel, Wesam Alis, Deniz Baheti, Bhakti Bai, Yingbin Bhat, Ishaan Cetindag, Sabri Can Chen, Wenting Cheng, Li Dutande, Prasad Dular, Lara Elattar, Mustafa A. Feng, Ming Gao, Shengbo Huisman, Henkjan Hu, Weifeng Innani, Shubham Ji, Wei Karimi, Davood Kuijf, Hugo J. Kwak, Jin Tae Le, Hoang Long Li, Xiang Lin, Huiyan Liu, Tongliang Ma, Jun Ma, Kai Ma, Ting Oksuz, Ilkay Holland, Robbie Oliveira, Arlindo L. Pal, Jimut Bahan Pei, Xuan Qiao, Maoying Saha, Anindo Selvan, Raghavendra Shen, Linlin Silva, Joao Lourenco Spiclin, Ziga Talbar, Sanjay Wang, Dadong Wang, Wei Wang, Xiong Wang, Yin Xi, Ruiling Xu, Kele Yang, Yanwu Yergin, Mert Yu, Shuang Zeng, Lingxi Zhang, YingLin Zhao, Jiachen Zheng, Yefeng Zukovec, Martin Do, Richard Becker, Anton Simpson, Amber Konukoglu, Ender Jakab, Andras Bakas, Spyridon Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Harvard Medical School United States Department of Quantitative Biomedicine University of Zurich Switzerland University Children’s Hospital Zurich University of Zurich Switzerland Department of Radioncology and Radiation Theraphy Klinikum rechts der Isar Technical University of Munich Germany Department of Information Technology and Electrical Engineering ETH-Zurich Switzerland Department of Radiology Memorial Sloan Kettering Cancer Center New York City United States Department of Biomedical and Molecular Sciences Queen’s University Canada TranslaTUM - Central Institute for Translational Cancer Research Technical University of Munich Germany McGovern Institute Massachusetts Institute of Technology United States Institute for Diagnostic and Interventional Radiology Unveristy Zurich Hospital Switzerland BioMedIA Imperial College London United Kingdom Department of Radiation Oncology University of Pennsylvania PA United States University of Pennsylvania PA United States Department of Radiation Oncology Winship Cancer Institute of Emory University Georgia United States Nile University Cairo Egypt Department of Medical Sciences Acibadem University Istanbul Turkey Shri Guru Gobind Singhji Institute of Engineering and Technology Maharashtra Nanded India Trustworthy Machine Learning Lab University of Sydney Australia Image Sciences Institute University Medical Center Utrecht Netherlands Computer Engineering Department Istanbul Technical University Istanbul Turkey School of Computer Science Shenzhen University Shenzhen China University of Alberta United States University of Ljubljana Faculty of Electrical Engineering Ljubljana Slovenia Tongji University Shanghai China OPPO Research Institute Shanghai China School of Biological and Medical Engineering Beihang University Beijing China Harvard Medical School Boston

Uncertainty in medical image segmentation tasks, especially inter-rater variability, arising from differences in interpretations and annotations by various experts, presents a significant challenge in achieving consistent and reliable image segmentation. This variability not only reflects the inherent complexity and subjective nature of medical image interpretation but also directly impacts the development and evaluation of automated segmentation algorithms. Accurately modeling and quantifying this variability is essential for enhancing the robustness and clinical applicability of these algorithms. We report the set-up and summarize the benchmark results of the Quantification of Uncertainties in biomedical Image Quantification Challenge (QUBIQ), which was organized in conjunction with International Conferences on Medical Image Computing and computer-Assisted Intervention (MICCAI) 2020 and 2021. The challenge focuses on the uncertainty quantification of medical image segmentation which considers the omnipresence of inter-rater variability in imaging datasets. The large collection of images with multi-rater annotations features various modalities such as MRI and CT;various organs such as the brain, prostate, kidney, and pancreas;and different image dimensions 2D-vs-3D. A total of 24 teams submitted different solutions to the problem, combining various baseline models, Bayesian neural networks, and ensemble model techniques. The obtained results indicate the importance of the ensemble models, as well as the need for further research to develop efficient 3D methods for uncertainty quantification methods in 3D segmentation tasks. © 2024, CC BY-NC-ND.

关键词： Image segmentation

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Lower limb joint angular phase plane coordination analysis on standard maximum vertical jump

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Gait & Posture 2021年 90卷 205-206页

作者： Rodrigues, C. Correia, M. Abrantes, J. Rodrigues, B. Nadal, J. INESC TEC - Institute for Systems and Computer Engineering- Technology and Science C-BER - Centre for Biomedical Engineering Research Porto Portugal University of Porto Faculty of Engineering Porto Portugal Lusófona University CICANT Centre for Research in Applied Communication Culture and New Technologies- MovLab Laboratory of Technologies for Interactions and Interfaces Lisbon Portugal Federal University of Pernambuco Department of Electronic and Systems Recife Brazil Federal University of Rio de Janeiro Biomedical Engineering Program Rio de Janeiro Brazil

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A Wireless Near-Infrared Spectroscopy Device for Flap Monitoring: Proof of Concept in a Porcine Musculocutaneous Flap Model

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Journal of Reconstructive Microsurgery 2021年第2期38卷 096-105页

作者： Changsheng Wu Alina Y. Rwei Jong Yoon Lee Wei Ouyang Lauren Jacobson Haixu Shen Haiwen Luan Yameng Xu Jun Bin Park Sung Soo Kwak Xiaoyue Ni Wubin Bai Daniel Franklin Shuo Li Yiming Liu Xinchen Ni Amanda M. Westman Matthew R. MacEwan John A. Rogers Mitchell A. Pet Department of Materials Science and Engineering Querrey Simpson Institute for Bioelectronics Northwestern University Chicago Illinois Department of Chemical Engineering Delft University of Technology Delft The Netherlands Sibel Inc. Evanston Illinois Division of Plastic and Reconstructive Surgery Department of Surgery School of Medicine Washington University St. Louis Missouri Department of Materials Science and Engineering Northwestern University Evanston Illinois Department of Neurosurgery School of Medicine Washington University St. Louis Missouri Department of Electrical and Computer Engineering Northwestern University Evanston Illinois Department of Mechanical Engineering Northwestern University Evanston Illinois Department of Biomedical Engineering Northwestern University Evanston Illinois Department of Chemistry Northwestern University Evanston Illinois Department of Neurological Surgery Feinberg School of Medicine Northwestern University Chicago Illinois

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Whole-body phase plane analysis for standard maximum vertical jump assessment

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Gait & Posture 2021年 90卷 203-204页

作者： Rodrigues, C. Correia, M. Abrantes, J. Rodrigues, B. Nadal, J. INESC TEC - Institute for Systems and Computer Engineering- Technology and Science C-BER - Centre for Biomedical Engineering Research Porto Portugal University of Porto Faculty of Engineering Porto Portugal Lusófona University CICANT Centre for Research in Applied Communication Culture and New Technologies - MovLab Laboratory of Technologies for Interactions and Interfaces Lisbon Portugal Federal University of Pernambuco Department of Electronic and Systems Recife Brazil Federal University of Rio de Janeiro Biomedical Engineering Program Rio de Janeiro Brazil

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Multi-Agent Trust Region Policy Optimization

arXiv

引用

arXiv 2020年

作者： Li, Hepeng He, Haibo The Department of Electrical Computer and Biomedical Engineering University of Rhode Island South KingstownRI United States

We extend trust region policy optimization (TRPO) [1] to cooperative multi-agent reinforcement learning (MARL) for partially observable Markov games (POMG). We show that the policy update rule in TRPO can be equivalently transformed into a distributed consensus optimization for networked agents when the agents’ observation is sufficient. By using local convexification and trust-region method, we propose a fully decentralized MARL algorithm based on a distributed alternating direction method of multipliers (ADMM). During training, agents only share local policy ratio with neighbors via a peer-to-peer communication network. Compared with traditional centralized training methods in MARL, the proposed algorithm does not need a control center to collect global information, such as global state, collective reward, or shared policy and value network parameters. Experiments on two cooperative environments demonstrate the effectiveness of the proposed method. Copyright © 2020, The Authors. All rights reserved.

关键词： Reinforcement learning

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Wireless electronic tattoos 12

Wireless electronic tattoos

引用

12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019

作者： Lu, Nanshu Jeong, Hyoyoung Department of Aerospace Engineering and Engineering Mechanic Department of Biomedical Engineering Department of Electrical and Computer Engineering Texas Materials Institute University of Texas at Austin 2501 Speedway Austin78712 United States Department of Electrical and Computer Engineering University of Texas at Austin 2501 Speedway Austin78712 United States

ISBN: (纸本)9781605956015

Wearable electronics are finding emerging applications in mobile health, rehabilitation, prosthetics/exoskeletons, athletic training, human-machine interaction, etc. However, our skin is soft, curvilinear and dynamic whereas wafer-based electronics are hard, planar, and rigid. As a result, state-of-the-art wearables can only be strapped or clipped on human body. The development of flexible and stretchable electronics offers a remedy for such challenge. E-tattoos represent a class of stretchable circuits, sensors, and actuators that are ultrathin, ultrasoft, skin-conformable and deformable just like a temporary tattoo. Our group has invented a low-cost, dry and freeform "cut-solder-paste" method for the rapid prototyping of multilayer and reconfigurable wireless e-tattoos. This method has been proved to work for thin film metals, polymers, ceramics, 2D materials and their integration with rigid integrated circuits (ICs). Through a modular and multilayer design, we created e-tattoos that can wirelessly receive power and transmit data through near field communication (NFC) and Bluetooth. Such e-tattoos can conform to any part of human skin for electrophysiological, mechanical, thermal and optical sensing. © 2019 by DEStech Publications, Inc. All rights reserved.

关键词： Internet of things

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Phase-induced frequency conversion and doppler effect with time-modulated metasurfaces

arXiv

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arXiv 2021年

作者： Ramaccia, Davide Sounas, Dimitrios L. Alù, Andrea Toscano, Alessandro Bilotti, Filiberto Department of Engineering ROMA TRE University Via Vito Volterra 62 Rome00146 Italy Department of Electrical and Computer Engineering Wayne State University DetroitMI48202 United States Photonics Initiative Advanced Science Research Center Physics Program Graduate Center Department of Electrical Engineering City College City University of New York New YorkNY10031 United States

Metasurfaces consisting of electrically thin and densely packed planar arrays of subwavelength elements enable an unprecedented control of the impinging electromagnetic fields. Spatially modulated metasurfaces can efficiently tailor the spatial distribution of these fields with great flexibility. Similarly, time modulated metasurfaces can be successfully used to manipulate the frequency content and time variations of the impinging field. In this paper, we present time-modulated reflective metasurfaces that cause a frequency shift to the impinging radiation, thus realizing an artificial Doppler effect in a non-moving electrically thin structure. Starting from the theoretical analysis, we analytically derive the required time modulation of the surface admittance to achieve this effect, and present a realistic time-varying structure, based on a properly designed and dynamically tuned high-impedance surface. It is analytically and numerically demonstrated that the field emerging from the metasurface is up-/down-converted in frequency according to the modulation profile of the metasurface. The proposed metasurface concept, enabling a frequency modulation of the electromagnetic field "on-the-fly", may find application in telecommunication, radar, and sensing scenarios. Copyright © 2021, The Authors. All rights reserved.

关键词： Doppler effect

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