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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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Spatiotemporal dynamics of NF-κB/Dorsal inhibitor IκBα/Cactus in Drosophila blastoderm embryos

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iScience 2025年

作者： Allison E. Schloop Sharva V. Hiremath Razeen Shaikh Sadia Siddika Dima Leslie Lizardo Amrit Bhakta Cranos M. Williams Gregory T. Reeves Graduate Program in Genetics North Carolina State University Raleigh NC 27606 Department of Electrical and Computer Engineering North Carolina State University Raleigh NC 27606 North Carolina Plant Sciences Initiative North Carolina State University Raleigh NC 27606 Department of Chemical Engineering Texas A&M University College Station TX 77843 Program in Genetics and Genomics Texas A&M University College Station TX 77843

The NF-κB/IκBα pathway regulates key cellular processes, including development, immunity, and inflammation. In Drosophila, the homologous Dorsal/Cactus system patterns the dorsoventral axis of the blastoderm embryo. While the inhibitor Cactus has been suggested to play multiple roles in regulating Dorsal, direct visualization of Cactus is challenging due to its rapid turnover. To overcome this challenge, we endogenously tagged Cactus with a nanobody against GFP and quantitatively imaged Cactus distribution in live embryos. We found that, like Dorsal, Cactus undergoes nuclear-cycle-driven dynamics and nucleocytoplasmic shuttling. Using a mathematical model constrained by our data, we estimated Cactus nuclear and cytoplasmic concentration. Our results imply that the Dorsal gradient has increased spatial range, robustness, and precision due to the presence of Cactus in the nucleus uniformly throughout the embryo. This study provides insights into NF-κB regulation in Drosophila embryos and highlights the need for similar quantitative studies in other biological systems.

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Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time 21

Deep inference of latent dynamics with spatio-temporal super...

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Proceedings of the 35th International Conference on Neural Information Processing Systems

作者： Feng Zhu Andrew R. Sedler Harrison A. Grier Nauman Ahad Mark A. Davenport Matthew T. Kaufman Andrea Giovannucci Chethan Pandarinath Neuroscience Graduate Program Emory University Center for Machine Learning Georgia Tech Computational Neuroscience Graduate Program The University of Chicago School of Electrical and Computer Engineering Georgia Tech Dept. of Organismal Biology and Anatomy The University of Chicago and Neuroscience Institute The University of Chicago Joint Dept. of Biomedical Engineering UNC Chapel Hill and NC State University and UNC Chapel Hill Neuroscience Center and NC State/UNC Closed-Loop Engineering for Advanced Rehabilitation (CLEAR) Coulter Dept. of Biomedical Engineering Emory University and Georgia Tech and Dept. of Neurosurgery Emory University

ISBN: (纸本)9781713845393

Modern neural interfaces allow access to the activity of up to a million neurons within brain circuits. However, bandwidth limits often create a trade-off between greater spatial sampling (more channels or pixels) and the temporal frequency of sampling. Here we demonstrate that it is possible to obtain spatio-temporal super-resolution in neuronal time series by exploiting relationships among neurons, embedded in latent low-dimensional population dynamics. Our novel neural network training strategy, selective backpropagation through time (SBTT), enables learning of deep generative models of latent dynamics from data in which the set of observed variables changes at each time step. The resulting models are able to infer activity for missing samples by combining observations with learned latent dynamics. We test SBTT applied to sequential autoencoders and demonstrate more efficient and higher-fidelity characterization of neural population dynamics in electrophysiological and calcium imaging data. In electrophysiology, SBTT enables accurate inference of neuronal population dynamics with lower interface bandwidths, providing an avenue to significant power savings for implanted neuroelectronic interfaces. In applications to two-photon calcium imaging, SBTT accurately uncovers high-frequency temporal structure underlying neural population activity, substantially outperforming the current state-of-the-art. Finally, we demonstrate that performance could be further improved by using limited, high-bandwidth sampling to pretrain dynamics models, and then using SBTT to adapt these models for sparsely-sampled data.

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Unveiling Topological Charges and Their Manipulation in Electronic Circuits

arXiv

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arXiv 2022年

作者： Sakotic, Zarko Stankovic, Predrag Bengin, Vesna Krasnok, Alex Alú, Andrea Jankovic, Nikolina BioSense Institute Research Institute for Information Technologies in Biosystems University of Novi Sad Dr Zorana Djindjica 1a Novi Sad21101 Serbia Department of Electrical and Computer Engineering Florida International University MiamiFL33174 United States Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States

Leveraging topological properties in the response of electromagnetic systems can greatly enhance their potential. Although the investigation of singularity-based electromagnetics and non-Hermitian electronics has considerably increased in recent years in the context of various scattering anomalies, their topological properties have not been fully assessed. In this work, we theoretically and experimentally demonstrate that non-Hermitian perturbations around bound states in the continuum can lead to singularities of the scattering matrix, which are topologically nontrivial and comply with charge conservation. The associated scattering matrix poles, zeros and pole-zero pairs delineate extreme scattering events, including lasing, coherent perfect absorption, and absorber-lasers. The presented framework enables a recipe for generation, annihilation and addition of these singularities in electric circuits, with potential for extreme scattering engineering across a broad range of the electromagnetic spectrum for sensing, wireless power transfer, lasing and thermal emission devices. Copyright © 2022, The Authors. All rights reserved.

关键词： Topology

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Data Processing of Functional Optical Microscopy for Neuroscience

arXiv

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arXiv 2022年

作者： Benisty, Hadas Song, Alexander Mishne, Gal Charles, Adam S. Yale Neuroscience New HavenCT06510 United States Max Planck Institute for Intelligent Systems Stuttgart Germany Halıcıoğlu Data Science Institute Department of Electrical and Computer Engineering Neurosciences Graduate Program UC San Diego 9500 Gilman Drive La Jolla CA92093 United States Department of Biomedical Engineering Kavli Neuroscience Discovery Institute Center for Imaging Science Department of Neuroscience Mathematical Institute for Data Science Johns Hopkins University BaltimoreMD21287 United States

Functional optical imaging in neuroscience is rapidly growing with the development of new optical systems and fluorescence indicators. To realize the potential of these massive spatiotemporal datasets for relating neuronal activity to behavior and stimuli and uncovering local circuits in the brain, accurate automated processing is increasingly essential. In this review, we cover recent computational developments in the full data processing pipeline of functional optical microscopy for neuroscience data and discuss ongoing and emerging challenges. © 2022, CC BY-NC-ND.

关键词： Fluorescence microscopy

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Electrostatic Properties and Ions Elimination Effect of Polyvinyl Chloride (PVC) Adhesive Tape Manufacturing

Electrostatic Properties and Ions Elimination Effect of Poly...

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International electrical engineering Congress (iEECON)

作者： Tatsanee Jenbanphue Komsan Hongesombut Kulsawasd Jitkajornwanich Siwapon Srisonphan Graduate program in safety engineering Kasetsart University Bangkok Thailand Department of Electrical Engineering Kasetsart University Bangkok Thailand Department of Computer Science King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (数字)9781728130767

ISBN: (纸本)9781728130774

Electrostatic discharges (ESD) can release large amounts of energy to products and humans, causing product failure and pain, respectively. In this research, we elucidate the electrostatic charge generation, and discharge phenomena in real polyvinyl chloride (PVC) based electrical tape factory, which is primarily operated by the roll to roll manufacturing process. We perform the electrostatic potential measurement to identify the critical process of charge generation and to eliminate static charge at the source in order to prevent incidents caused by electrostatic discharge to operators or staff in the winding process. We also perform a numerical simulation-based finite element method (FEM) that provides modeling of an induced electric field, allowing the electrostatic discharge. The maximum potential is ~20 kV measured at 25 mm, indicating that the meter was induced by the electric field approximately ~0.8 MV/m, corresponding to surface charges density is ~ 10 μC/m 2 . Therefore, we introduced the ionization emitter bar in this case because it is feasible to install to the current infrastructure of the tested factory. The ionization emitter appears to reduce the electrostatic charge deposited on the PVC surface ~ 30% of the original charges. Therefore, installing a charge-dissipation technology at a proper location or combining with other methods, the electrostatic charge generation can be minimized even in roll to roll process.

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Fourier diffuserscope: Single-shot 3d fourier light field microscopy with a diffuser

arXiv

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arXiv 2020年

作者： Liu, Fanglin Linda Grace, K.U.O. Antipa, Nick Yanny, Kyrollos Waller, Laura Electrical Engineering and Computer Sciences University of California Berkeley94709 United States UCB/UCSF Joint Graduate Program in Bioengineering University of California BerkeleyCA94709 United States

Light field microscopy (LFM) uses a microlens array (MLA) near the sensor plane of a microscope to achieve single-shot 3D imaging of a sample, without any moving parts. Unfortunately, the 3D capability of LFM comes with a significant loss of lateral resolution at the focal plane, which is highly undesirable in microscopy. Placing the MLA near the pupil plane of the microscope, rather than the image plane, can mitigate the artifacts near focus and provide an efficient shift-invariant model at the expense of field-of-view. Here, we show that our Fourier DiffuserScope achieves significantly better performance than Fourier LFM. Fourier DiffuserScope uses a diffuser in the pupil plane to encode depth information, then reconstructs volumetric information computationally by solving a sparsity-constrained inverse problem. Our diffuser consists of randomly placed microlenses with varying focal lengths. We show that by randomizing the microlens positions, a larger lateral field-of-view can be achieved compared to a conventional MLA;furthermore, by adding diversity to the focal lengths, the axial depth range is increased. To predict system performance based on diffuser parameters, we for the first time establish a theoretical framework as a design guideline, followed by numerical simulations to verify. Under both theoretical and numerical analysis, we demonstrate that our diffuser design provides more uniform resolution over a larger volume, both laterally and axially, outperforming the MLA used in LFM. We build an experiment system with an optimized lens set and achieve 3 volume. Copyright © 2020, The Authors. All rights reserved.

关键词： Microlenses

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Large optical tunability from charge density waves in 1T-TaS2 under incoherent illumination

arXiv

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arXiv 2020年

作者： Li, Weijian Naik, Gururaj V. Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Electrical & Computer Engineering Rice University TX77005 United States

Strongly correlated materials possess a complex energy landscape and host many interesting physical phenomena, including charge density waves (CDWs). CDWs have been observed and extensively studied in many materials since their first discovery in 1972. Yet, they present ample opportunities for discovery. Here, we report a large tunability in the optical response of a quasi-2D CDW material, 1T-TaS2, upon incoherent light illumination at room temperature. We show that the observed tunability is a consequence of light-induced rearrangement of CDW stacking across the layers of 1T-TaS2. Our model, based on this hypothesis, agrees reasonably well with experiments suggesting that the interdomain CDW interaction is a vital knob to control the phase of strongly correlated materials. Copyright © 2020, The Authors. All rights reserved.

关键词： Charge density waves

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1T-TaS2 - A strongly correlated material with a large photo-refractive effect at room temperature

1T-TaS2 - A strongly correlated material with a large photo-...

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Frontiers in Optics, FiO_2019

作者： Li, Weijian Naik, Gururaj V. Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Electrical and Computer Engineering Rice University TX77005 United States

We demonstrate a large photo-refractive effect in 1T-TaS2 in the visible at low intensity white light excitation. By using this optical tunability, we demonstrate tunable meta-gratings for nanophotonics applications. ... 详细信息

ISBN: (纸本)9781943580675

关键词： Finite difference time domain Light intensity Nanophotonics Photorefractive materials Thin film optical properties X ray diffraction

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cytoNet: Spatiotemporal network analysis of cell communities (vol 18, e1009846, 2022)

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PLOS COMPUTATIONAL BIOLOGY 2022年第11期18卷 e1009846页

作者： Mahadevan, A. S. Long, B. L. Hu, C. W. Ryan, D. T. Grandel, N. E. Department of Bioengineering University of Pennsylvania Philadelphia Pennsylvania United States of America Department of Bioengineering Rice University Houston Texas United States of America Department of Biomedical Engineering University of Texas at San Antonio San Antonio Texas United States of America Department of Computer Science University of Texas at San Antonio San Antonio Texas United States of America Systems Synthetic and Physical Biology Program Rice University Houston Texas United States of America Biophysics Graduate Program University of California Berkeley California United States of America Department of Oral & Maxillofacial Surgery University of Texas Health Science Center at San Antonio San Antonio Texas United States of America Department of Electrical and Computer Engineering Rice University Houston Texas United States of America Department of Biosciences Rice University Houston Texas United States of America UTSA–UT Health Joint Graduate Group in Biomedical Engineering San Antonio Texas United States of America Programs in Integrated Biomedical Sciences Translational Sciences Radiological Sciences University of Texas Health Science Center at San Antonio San Antonio Texas United States of America UTSA AI MATRIX Consortium San Antonio Texas United States of America

We introduce cytoNet, a cloud-based tool to characterize cell populations from microscopy images. cytoNet quantifies spatial topology and functional relationships in cell communities using principles of network science. Capturing multicellular dynamics through graph features, cytoNet also evaluates the effect of cell-cell interactions on individual cell phenotypes. We demonstrate cytoNet’s capabilities in four case studies: 1) characterizing the temporal dynamics of neural progenitor cell communities during neural differentiation, 2) identifying communities of pain-sensing neurons in vivo , 3) capturing the effect of cell community on endothelial cell morphology, and 4) investigating the effect of laminin α4 on perivascular niches in adipose tissue. The analytical framework introduced here can be used to study the dynamics of complex cell communities in a quantitative manner, leading to a deeper understanding of environmental effects on cellular behavior. The versatile, cloud-based format of cytoNet makes the image analysis framework accessible to researchers across domains.

关键词： Calcium imaging Fluorescence imaging Growth factors Centrality Cell cycle and cell division Endothelial cells Network analysis Stem cells

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