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Hybrid dedicated and distributed coding in PMd/M1 provides separation and interaction of bilateral arm signals

PLoS Computational Biology 2021年第11期17卷 e1009615-e1009615页

作者： Dixon, Tanner C. Merrick, Christina M. Wallis, Joni D. Ivry, Richard B. Carmena, Jose M. UC Berkeley-UCSF Graduate Program in Bioengineering University of California-Berkeley BerkeleyCA United States Department of Psychology University of California-Berkeley BerkeleyCA United States Helen Wills Neuroscience Institute University of California-Berkeley BerkeleyCA United States Department of Electrical Engineering and Computer Sciences University of California-Berkeley BerkeleyCA United States

Pronounced activity is observed in both hemispheres of the motor cortex during preparation and execution of unimanual movements. The organizational principles of bi-hemispheric signals and the functions they serve throughout motor planning remain unclear. Using an instructed-delay reaching task in monkeys, we identified two components in population responses spanning PMd and M1. A "dedicated"component, which segregated activity at the level of individual units, emerged in PMd during preparation. It was most prominent following movement when M1 became strongly engaged, and principally involved the contralateral hemisphere. In contrast to recent reports, these dedicated signals solely accounted for divergence of arm-specific neural subspaces. The other "distributed"component mixed signals for each arm within units, and the subspace containing it did not discriminate between arms at any stage. The statistics of the population response suggest two functional aspects of the cortical network: One that spans both hemispheres for supporting preparatory and ongoing processes, and another that is predominantly housed in the contralateral hemisphere and specifies unilateral output. © 2021 Dixon et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

关键词： Population statistics

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Beyond Bounds on Light Scattering with Complex Frequency Excitations

arXiv

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arXiv 2022年

作者： Kim, Seunghwi Lepeshov, Sergey Krasnok, Alex Alù, Andrea Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States DTU Electro Department of Electrical and Photonics Engineering Technical University of Denmark Ørsteds Plads 343 Kgs. LyngbyDK-2800 Denmark Department of Electrical and Computer Engineering Florida International University MiamiFL33174 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States

Light scattering is one of the most established wave phenomena in optics, lying at the heart of light-matter interactions and of crucial importance for nanophotonic applications. Passivity, causality and energy conservation imply strict bounds on the degree of control over scattering from small particles, with implications on the performance of many optical devices. Here, we demonstrate that these bounds can be surpassed by considering excitations at complex frequencies, yielding extreme scattering responses as tailored nanoparticles reach a quasi-steady-state regime. These mechanisms can be used to engineer light scattering of nanostructures beyond conventional limits for noninvasive sensing, imaging, and nanoscale light manipulation. Copyright © 2022, The Authors. All rights reserved.

关键词： Light scattering

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Caco-2 Cell-Derived Biomimetic Electrochemical Biosensor for Cholera Toxin Detection

SSRN

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SSRN 2022年

作者： Kim, Yonghwan Lee, Dongtak Seo, Youngjun Jung, Hyo Gi Jang, Jae Won Park, Dongsung Kim, Insu Lee, Gyudo Hwang, Kyo Seon Kim, Seung-Hyun Lee, Sang Won Lee, Jeong Hoon Yoon, Dae Sung School of Biomedical Engineering Korea University Seoul02841 Korea Republic of Interdisciplinary Program in Precision Public Health Korea University Seoul02841 Korea Republic of Department of Clinical Pharmacology and Therapeutics College of Medicine Kyung Hee University Seoul02447 Korea Republic of Department of Biotechnology and Bioinformatics Korea University Sejong30019 Korea Republic of Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology Korea University Sejong30019 Korea Republic of School of Engineering Brown University ProvidenceRI02912 United States Department of Electrical Engineering and Computer Science University of California IrvineCA92697 United States Department of Electrical Engineering Kwangwoon University Seoul01897 Korea Republic of Astrion Inc Seoul02841 Korea Republic of

Cholera is a highly contagious and lethal waterborne disease induced by an infection with Vibrio cholerae (V. cholerae) secreting cholera toxin (CTx). Cholera toxin subunit B (CTxB) from the CTx specifically binds with monosialo-tetra-hexosyl-ganglioside (GM1) found on the exterior cell membrane of an enterocyte. Owing to the pathological process of CTx, a biomimetic electrochemical biosensor (CCB) was developed by applying GM1-expressing Caco-2 cell membrane (CCM) on the electrode surface of the biosensor for CTx detection. Briefly, the electrode surface was functionalized with CCM using the vesicle fusion method. The specific binding between GM1 and CTxB on the electrode surface was verified using confocal laser scanning microscopy and atomic force microscopy. The CTxB detection performances of the CCB, including sensitivity, selectivity, and long-term stability, were determined using electrochemical impedance spectroscopy (EIS). Based on the results, the CCB had an excellent limit of detection of ~11.46 nM and a detection range spanning 100 ng/mL - 1 mg/mL. Further, the CCB had high selectivity for the CTxB compared to different interfering molecules, which are abundant constituents of intestinal fluid and fecal matter in the human body. The long-term stability of the CCBs was also verified for 3 weeks using EIS. Overall, the CCB was found to have an excellent potential for application to point-of-care and cost-effective testing for CTxB detection in developing countries. © 2022, The Authors. All rights reserved.

关键词： Electrochemical impedance spectroscopy

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Identifying Materials-Level Sources of Performance Variation in Superconducting Transmon Qubits

arXiv

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arXiv 2025年

作者： Murthy, Akshay A. Bal, Mustafa Bedzyk, Michael J. Cansizoglu, Hilal Chan, Randall K. Chandrasekhar, Venkat Crisa, Francesco Datta, Amlan Deng, Yanpei Matute Diaz, Celeo D. Dravid, Vinayak P. Garcia-Wetten, David A. Garattoni, Sabrina Ghimire, Sunil Goronzy, Dominic P. de Graaf, Sebastian E. Haeuser, Sam Hersam, Mark C. Isheim, Dieter Joshi, Kamal Kim, Richard Kolachina, Saagar Kopas, Cameron J. Kramer, Matthew J. Lachman, Ella O. Lee, Jaeyel Lim, Peter G. Lunin, Andrei Mah, William Marshall, Jayss Mutus, Josh Y. Oh, Jin-Su Pappas, David P. Park, Joong-Mok Prozorov, Ruslan dos Reis, Roberto Seidman, David N. Sung, Zuhawn Tanatar, Makariy Walker, Mitchell J. Wang, Jigang Wu, Haotian Zhou, Lin Zhu, Shaojiang Grassellino, Anna Romanenko, Alexander BataviaIL60510 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Rigetti Computing BerkeleyCA94710 United States Ames National Laboratory AmesIA50011 United States Department of Physics & Astronomy Iowa State University AmesIA50011 United States Department of Physics and Astronomy Northwestern University EvanstonIL60208 United States The NUANCE Center Northwestern University EvanstonIL60208 United States International Institute of Nanotechnology Northwestern University EvanstonIL60208 United States National Physical Laboratory TeddingtonTW11 0LW United Kingdom Department of Chemistry Northwestern University EvanstonIL60208 United States Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States Applied Physics Graduate Program Northwestern University EvanstonIL60208 United States Department of Materials Science and Engineering Iowa State University AmesIA50011 United States

The Superconducting Materials and Systems (SQMS) Center, a DOE National Quantum Information science Research Center, has conducted a comprehensive and coordinated study using superconducting transmon qubit chips with known performance metrics to identify the underlying materials-level sources of device-to-device performance variation. Following qubit coherence measurements, these qubits of varying base superconducting metals and substrates have been examined with various nondestructive and invasive material characterization techniques at Northwestern University, Ames National Laboratory, and Fermilab as part of a blind study. We find trends in variations of the depth of the etched substrate trench, the thickness of the surface oxide, and the geometry of the sidewall, which when combined, lead to correlations with the T1 lifetime across different devices. In addition, we provide a list of features that varied from device to device, for which the impact on performance requires further studies. Finally, we identify two low-temperature characterization techniques that may potentially serve as proxy tools for qubit measurements. These insights provide materials-oriented solutions to not only reduce performance variations across neighboring devices, but also to engineer and fabricate devices with optimal geometries to achieve performance metrics beyond the state-of-the-art values. © 2025, CC BY.

关键词： Qubits

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A Platform for Monitoring Student Commuting in the Use of School Transport in Smart Cities - A Facial Recognition Based Approach

A Platform for Monitoring Student Commuting in the Use of Sc...

引用

International Conference on Smart Communications and Networking (SmartNets)

作者： Jessé Da Costa Rocha Marcela Alves de Souza Evelin Helena Silva Cardoso Nandamudi Vijaykumar Jasmine Priscyla Leite de Araújo Renato Lisboa Francês Graduate Program in Electrical Engineering Institute of Technology Federal University of Pará (UFPA) Belém Pará Brazil Information and Communication Technology Center Federal University of the South and Southeast of Para (Unifesspa) Marabá Pará Brazil Department of Computer Science Federal Rural University of the Amazon (UFRA) Capitão Poço Pará Brazil Coordination of Applied Research and Technological Development National Institute for Space Research (INPE) São Paulo Brazil

This article proposes an intelligent platform for monitoring students' steps on their way to school until they leave the school to their homes. This platform can identify students and notify those responsible and competent authorities in various situations of school life, such as: entering and leaving the school bus, entering and leaving school, entering the school cafeteria, etc. The first application aims to control access to the school bus through facial recognition. In the tests carried out, the recognition system achieved excellent results in all metrics.

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A Framework for Interpretability in Machine Learning for Medical Imaging

arXiv

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arXiv 2023年

作者： Wang, Alan Q. Karaman, Batuhan K. Kim, Heejong Rosenthal, Jacob Saluja, Rachit Young, Sean I. Sabuncu, Mert R. School of Electrical and Computer Engineering Cornell University Cornell Tech New YorkNY10044 United States Department of Radiology Weill Cornell Medical School New YorkNY10065 United States Weill Cornell/Rockefeller/Sloan Kettering Tri-Institutional MD-PhD Program New YorkNY10065 United States Martinos Center for Biomedical Imaging Harvard Medical School BostonMA02129 United States Computer Science and Artificial Intelligence Laboratory MIT CambridgeMA02139 United States

Interpretability for machine learning models in medical imaging (MLMI) is an important direction of research. However, there is a general sense of murkiness in what interpretability means. Why does the need for interpretability in MLMI arise? What goals does one actually seek to address when interpretability is needed? To answer these questions, we identify a need to formalize the goals and elements of interpretability in MLMI. By reasoning about real-world tasks and goals common in both medical image analysis and its intersection with machine learning, we identify five core elements of interpretability: localization, visual recognizability, physical attribution, model transparency, and actionability. From this, we arrive at a framework for interpretability in MLMI, which serves as a step-by-step guide to approaching interpretability in this context. Overall, this paper formalizes interpretability needs in the context of medical imaging, and our applied perspective clarifies concrete MLMI-specific goals and considerations in order to guide method design and improve real-world usage. Our goal is to provide practical and didactic information for model designers and practitioners, inspire developers of models in the medical imaging field to reason more deeply about what interpretability is achieving, and suggest future directions of interpretability research. © 2023, CC0.

关键词： Machine learning

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Template-free try-on image synthesis via semantic-guided optimization

arXiv

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arXiv 2021年

作者： Chou, Chien-Lung Chen, Chieh-Yun Hsieh, Chia-Wei Shuai, Hong-Han Liu, Jiaying Cheng, Wen-Huang Department of Electrical and Computer Engineering National Chiao Tung University Taiwan Institute of Electronics National Chiao Tung University Taiwan Artificial Intelligence and Data Science Program National Chung Hsing University Taiwan Wangxuan Institute of Computer Technology Peking University China

The virtual try-on task is so attractive that it has drawn considerable attention in the field of computer vision. However, presenting the three-dimensional (3D) physical characteristic (e.g., pleat and shadow) based on a 2D image is very challenging. Although there have been several previous studies on 2D-based virtual try-on work, most 1) required user-specified target poses that are not user-friendly and may not be the best for the target clothing, and 2) failed to address some problematic cases, including facial details, clothing wrinkles and body occlusions. To address these two challenges, in this paper, we propose an innovative template-free try-on image synthesis (TF-TIS) network. The TF-TIS first synthesizes the target pose according to the user-specified in-shop clothing. Afterward, given an in-shop clothing image, a user image, and a synthesized pose, we propose a novel model for synthesizing a human try-on image with the target clothing in the best fitting pose. The qualitative and quantitative experiments both indicate that the proposed TF-TIS outperforms the state-of-the-art methods, especially for difficult cases. Copyright © 2021, The Authors. All rights reserved.

关键词： Semantics

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Asymptotic analysis of an ensemble of randomly projected linear discriminants

arXiv

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arXiv 2020年

作者： Niyazi, Lama B. Kammoun, Abla Dahrouj, Hayssam Alouini, Mohamed-Slim Al-Naffouri, Tareq Y. Electrical Engineering Program King Abdullah University of Science and Technology Thuwal Saudi Arabia Department of Electrical and Computer Engineering Effat University Jeddah Saudi Arabia

Datasets from the fields of bioinformatics, chemometrics, and face recognition are typically characterized by small samples of high-dimensional data. Among the many variants of linear discriminant analysis that have been proposed in order to rectify the issues associated with classification in such a setting, the classifier in [1], composed of an ensemble of randomly projected linear discriminants, seems especially promising;it is computationally efficient and, with the optimal projection dimension parameter setting, is competitive with the state-of-the-art. In this work, we seek to further understand the behavior of this classifier through asymptotic analysis. Under the assumption of a growth regime in which the dataset and projection dimensions grow at constant rates to each other, we use random matrix theory to derive asymptotic misclassification probabilities showing the effect of the ensemble as a regularization of the data sample covariance matrix. The asymptotic errors further help to identify situations in which the ensemble offers a performance advantage. We also develop a consistent estimator of the misclassification probability as an alternative to the computationally-costly cross-validation estimator, which is conventionally used for parameter tuning. Finally, we demonstrate the use of our estimator for tuning the projection dimension on both real and synthetic data. Copyright © 2020, The Authors. All rights reserved.

关键词： Random variables

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RSAC: Regularized subspace approximation classifier for lightweight continuous learning

arXiv

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arXiv 2020年

作者： Ho, Chih-Hsing Tsai, Shang-Ho Department of Electrical Engineering and Computer Science Honor Program National Chiao Tung University Hsinchu Taiwan Department of Electrical Engineering National Chiao Tung University Hsinchu Taiwan

Continuous learning seeks to perform the learning on the data that arrives from time to time. While prior works have demonstrated several possible solutions, these approaches require excessive training time as well as memory usage. This is impractical for applications where time and storage are constrained, such as edge computing. In this work, a novel training algorithm, regularized subspace approximation classifier (RSAC), is proposed to achieve lightweight continuous learning. RSAC contains a feature reduction module and classifier module with regularization. Extensive experiments show that RSAC is more efficient than prior continuous learning works and outperforms these works on various experimental settings. Copyright © 2020, The Authors. All rights reserved.

关键词： Approximation algorithms

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3D OCT characterization and quantification of refractive indices of bacteria and biofilms with antibiotic interventions

3D OCT characterization and quantification of refractive ind...

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Optical Molecular Probes, Imaging and Drug Delivery, OMP 2021 - Part of Biophotonics Congress: Optics in the Life sciences 2021

作者： Zaki, Farzana R. Sudhir, Kavya Won, Jungeun Monroy, Guillermo L. Choi, Honggu Chaney, Eric J. Spillman, Darold R. Boppart, Stephen A. Beckman Institute for Advanced Science and Technology 405 North Mathews Avenue UrbanaIL61801 United States University of Illinois at Urbana–Champaign Department of Bioengineering 1304 West Springfield Avenue UrbanaIL61801 United States University of Illinois at Urbana–Champaign Department of Electrical and Computer Engineering 306 North Wright Street UrbanaIL61801 United States Carle Illinois College of Medicine University of Illinois at Urbana-Champaign 807 S. Wright St. ChampaignIL61820 United States

Using 3D OCT, we have quantified the refractive indices of ear-infection causing bacteria and biofilms with antibiotics interventions. This approach reveals changing optical properties of bacteria in biofilms followin...

ISBN: (纸本)9781557528209

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