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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Xu, Xiaokun; Yue, Xiaomin; Lescroart, Mark D.; Biederman, Irving; +1 Authors

    AbstractViewing a sequence of faces of two different people results in a greater Blood Oxygenation Level Dependent (BOLD) response in FFA compared to a sequence of identical faces. Changes in identity, however, necessarily involve changes in the image. Is the release from adaptation a result of a change in face identity, per se, or could it be an effect that would arise from any change in the image of a face? Subjects viewed a sequence of two faces that could be of the same or different person, and in the same or different orientation in depth. Critically, the physical similarity of view changes of the same person was scaled, by Gabor-jet differences, to be equivalent to that produced by an identity change. Both person and orientation changes produced equivalent releases from adaptation in FFA (relative to identical faces) suggesting that FFA is sensitive to the physical similarity of faces rather than to the individuals depicted in the images.

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    Vision Research
    Article . 2009 . Peer-reviewed
    License: Elsevier Non-Commercial
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      Vision Research
      Article . 2009 . Peer-reviewed
      License: Elsevier Non-Commercial
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    Authors: Zhilin, Zhang; Tzyy-Ping, Jung; Scott, Makeig; Bhaskar D, Rao;

    Telemonitoring of electroencephalogram (EEG) through wireless body-area networks is an evolving direction in personalized medicine. Among various constraints in designing such a system, three important constraints are energy consumption, data compression, and device cost. Conventional data compression methodologies, although effective in data compression, consumes significant energy and cannot reduce device cost. Compressed sensing (CS), as an emerging data compression methodology, is promising in catering to these constraints. However, EEG is non-sparse in the time domain and also non-sparse in transformed domains (such as the wavelet domain). Therefore, it is extremely difficult for current CS algorithms to recover EEG with the quality that satisfies the requirements of clinical diagnosis and engineering applications. Recently, Block Sparse Bayesian Learning (BSBL) was proposed as a new method to the CS problem. This study introduces the technique to the telemonitoring of EEG. Experimental results show that its recovery quality is better than state-of-the-art CS algorithms, and sufficient for practical use. These results suggest that BSBL is very promising for telemonitoring of EEG and other non-sparse physiological signals. Comment: Matlab codes can be downloaded at: http://dsp.ucsd.edu/~zhilin/BSBL.html, or http://sites.google.com/site/researchbyzhang/bsbl

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    IEEE Transactions on Biomedical Engineering
    Article . 2013 . Peer-reviewed
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    https://doi.org/10.48550/arxiv...
    Article . 2012
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      IEEE Transactions on Biomedical Engineering
      Article . 2013 . Peer-reviewed
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      Article . 2012
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    Authors: Penny, W.D.; Duzel, E.; Miller, K.J.; Ojemann, J.G.;

    AbstractNested oscillation occurs when the amplitude of a faster rhythm is coupled to the phase of a slower rhythm. It has been proposed to underlie the discrete nature of perception and the capacity of working memory and is a phenomenon observable in human brain imaging data. This paper compares three published methods for detecting nested oscillation and a fourth method proposed in this paper. These are: (i) the modulation index, (ii) the phase-locking value (PLV), (iii) the envelope-to-signal correlation (ESC) and (iv) a general linear model (GLM) measure derived from ESC. We applied the methods to electrocorticographic (ECoG) data recorded during a working-memory task and to data from a simulated hippocampal interneuron network. Further simulations were then made to address the dependence of each measure on signal to noise level, coupling phase, epoch length, sample rate, signal nonstationarity, and multi-phasic coupling. Our overall conclusion is that the GLM measure is the best all-round approach for detecting nested oscillation.

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    Europe PubMed Central
    Article . 2008
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      Article . 2008
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    Authors: Talia Konkle; George A. Alvarez;

    Anterior regions of the ventral visual stream encode substantial information about object categories. Are top-down category-level forces critical for arriving at this representation, or can this representation be formed purely through domain-general learning of natural image structure? Here we present a fully self-supervised model which learns to represent individual images, rather than categories, such that views of the same image are embedded nearby in a low-dimensional feature space, distinctly from other recently encountered views. We find that category information implicitly emerges in the local similarity structure of this feature space. Further, these models learn hierarchical features which capture the structure of brain responses across the human ventral visual stream, on par with category-supervised models. These results provide computational support for a domain-general framework guiding the formation of visual representation, where the proximate goal is not explicitly about category information, but is instead to learn unique, compressed descriptions of the visual world. It is unknown whether object category learning can be formed purely through domain general learning of natural image structure. Here the authors show that human visual brain responses to objects are well-captured by self-supervised deep neural network models trained without labels, supporting a domain-general account.

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    Europe PubMed Central
    Article . 2022 . Peer-reviewed
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    Nature Communications
    Article . 2022
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    Nature Communications
    Article . 2022 . Peer-reviewed
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      Europe PubMed Central
      Article . 2022 . Peer-reviewed
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      Article . 2022 . Peer-reviewed
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    Authors: J. B. Vielfaure; S. D. Vergani; J. Japelj; Johan P. U. Fynbo; +22 Authors

    Context. The identification of the sources that reionized the Universe and their specific contribution to this process are key missing pieces of our knowledge of the early Universe. Faint star-forming galaxies may be the main contributors to the ionizing photon budget during the epoch of reionization, but their escaping photons cannot be detected directly due to inter-galactic medium opacity. Hence, it is essential to characterize the properties of faint galaxies with significant Lyman continuum (LyC) photon leakage up to z ∼ 4 to define indirect indicators allowing analogs to be found at the highest redshift. Aims. Long gamma-ray bursts (LGRBs) typically explode in star-forming regions of faint, star-forming galaxies. Through LGRB afterglow spectroscopy it is possible to detect directly LyC photons. Our aim is to use LGRBs as tools to study LyC leakage from faint, star-forming galaxies at high redshift. Methods. Here we present the observations of LyC emission in the afterglow spectra of GRB 191004B at z = 3.5055, together with those of the other two previously known LyC-leaking LGRB host galaxies (GRB 050908 at z = 3.3467, and GRB 060607A at z = 3.0749), to determine their LyC escape fraction and compare their properties. Results. From the afterglow spectrum of GRB 191004B we determine a neutral hydrogen column density at the LGRB redshift of log(NH I/cm−2) = 17.2 ± 0.15, and negligible extinction (AV = 0.03 ± 0.02 mag). The only metal absorption lines detected are C IV and Si IV. In contrast to GRB 050908 and GRB 060607A, the host galaxy of GRB 191004B displays significant Lyman-alpha (Lyα) emission. From its Lyα emission and the non-detection of Balmer emission lines we constrain its star-formation rate (SFR) to 1 ≤ SFR ≤ 4.7 M⊙ yr−1. We fit the Lyα emission with a shell model and find parameters values consistent with the observed ones. The absolute (relative) LyC escape fractions we find for GRB 191004B, GRB 050908 and GRB 060607A are of 0.35−0.11+0.10 (0.43−0.13+0.12), 0.08−0.04+0.05 (0.08−0.04+0.05) and 0.20−0.05+0.05 (0.45−0.15+0.15), respectively. We compare the LyC escape fraction of LGRBs to the values of other LyC emitters found from the literature, showing that LGRB afterglows can be powerful tools to study LyC escape for faint high-redshift star-forming galaxies. Indeed we could push LyC leakage studies to much higher absolute magnitudes. The host galaxies of the three LGRBs presented here have all M1600 > −19.5 mag, with the GRB 060607A host at M1600 > −16 mag. LGRB hosts may therefore be particularly suitable for exploring the ionizing escape fraction in galaxies that are too faint or distant for conventional techniques. Furthermore, the time involved is minimal compared to galaxy studies. © J.-B. Vielfaure et al. 2020 This work is part of the BEaPro project (PI: S.D. Vergani) funded by the French Agence Nationale de la Recherche (ANR-16-CE31-0003). We thank Giancarlo Ghirlanda for providing useful information. JBV and SDV thank Anne Verhamme for useful discussions. SDV acknowledges financial support from the French Space Agency (CNES). MG was supported by NASA through the NASA Hubble Fellowship grant HST-HF2-51409 and acknowledges support from HST grants HST-GO-15643.017-A, HST-AR-15039.003-A, and XSEDE grant TG-AST180036. The Cosmic DAWN center is funded by the DNRF. JPUF thanks the Carlsberg foundation for support. DBM acknowledges support from VILLUM FONDEN research grant 19054. NRT acknowledges support from STFC via grant ST/N000757/1. DAK acknowledges support from Spanish research project RTI2018-098104-J-I00 (GRBPhot). The PanSTARRS1 Surveys (PS1) and the PS1 public science archive have been made possible through contributions by the Institute for Astronomy, the University of Hawaii, the Pan-STARRS Project O ffice, the Max-Planck Society and its participating institutes, the Max Planck Institute for Astronomy, Heidelberg and the Max Planck Institute for Extraterrestrial Physics, Garching, The Johns Hopkins University, Durham University, the University of Edinburgh, the Queen's University Belfast, the Harvard-Smithsonian Center for Astrophysics, the Las Cumbres Observatory Global Telescope Network Incorporated, the National Central University of Taiwan, the Space Telescope Science Institute, the National Aeronautics and Space Administration under Grant No. NNX08AR22G issued through the Planetary Science Division of the NASA Science Mission Directorate, the National Science Foundation Grant No. AST-1238877, the University of Maryland, Eotvos Lorand University (ELTE), the Los Alamos National Laboratory, and the Gordon and Betty Moore Foundation. This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium).Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. The NumPy (van der Walt et al. 2011), SciPy (Virtanen et al. 2020) and matplotlib (Hunter 2007) packages have been extensively used for the preparation and presentation of this work. Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Peer reviewed

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    Article . 2020
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    Astronomy and Astrophysics
    Article
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    Opin visindi
    Article . 2020 . Peer-reviewed
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    Other literature type . Preprint . 2020
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      Astronomy and Astrophysics
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      Opin visindi
      Article . 2020 . Peer-reviewed
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      Radboud Repository
      Article . 2020
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Hal-Diderot
      Article . 2020
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      Other literature type . Preprint . 2020
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    Authors: Dahlem, Markus A.;

    Migraine is a common disabling headache disorder characterized by recurrent episodes sometimes preceded or accompanied by focal neurological symptoms called aura. The relation between two subtypes, migraine without aura (MWoA) and migraine with aura (MWA), is explored with the aim to identify targets for neuromodulation techniques. To this end, a dynamically regulated control system is schematically reduced to a network of the trigeminal nerve, which innervates the cranial circulation, an associated descending modulatory network of brainstem nuclei, and parasympathetic vasomotor efferents. This extends the idea of a migraine generator region in the brainstem to a larger network and is still simple and explicit enough to open up possibilities for mathematical modeling in the future. In this study, it is suggested that the migraine generator network (MGN) is driven and may therefore respond differently to different spatio-temporal noxious input in the migraine subtypes MWA and MWoA. The noxious input is caused by a cortical perturbation of homeostasis, known as spreading depression (SD). The MGN might even trigger SD in the first place by a failure in vasomotor control. As a consequence, migraine is considered as an inherently dynamical disease to which a linear course from upstream to downstream events would not do justice. Minimally invasive and noninvasive neuromodulation techniques are briefly reviewed and their rational is discussed in the context of the proposed mechanism. 12 pages, 8 figures, revised version

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    https://doi.org/10.48550/arxiv...
    Article . 2013
    License: arXiv Non-Exclusive Distribution
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      https://doi.org/10.48550/arxiv...
      Article . 2013
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    Authors: Saket Navlakha; Alison L Barth; Ziv Bar-Joseph;

    Robust, efficient, and low-cost networks are advantageous in both biological and engineered systems. During neural network development in the brain, synapses are massively over-produced and then pruned-back over time. This strategy is not commonly used when designing engineered networks, since adding connections that will soon be removed is considered wasteful. Here, we show that for large distributed routing networks, network function is markedly enhanced by hyper-connectivity followed by aggressive pruning and that the global rate of pruning, a developmental parameter not previously studied by experimentalists, plays a critical role in optimizing network structure. We first used high-throughput image analysis techniques to quantify the rate of pruning in the mammalian neocortex across a broad developmental time window and found that the rate is decreasing over time. Based on these results, we analyzed a model of computational routing networks and show using both theoretical analysis and simulations that decreasing rates lead to more robust and efficient networks compared to other rates. We also present an application of this strategy to improve the distributed design of airline networks. Thus, inspiration from neural network formation suggests effective ways to design distributed networks across several domains. Author Summary During development of neural circuits in the brain, synapses are massively over-produced and then pruned-back over time. This is a fundamental process that occurs in many brain regions and organisms, yet, despite decades of study of this process, the rate of synapse elimination, and how such rates affect the function and structure of networks, has not been studied. We performed large-scale brain imaging experiments to quantify synapse elimination rates in the developing mouse cortex and found that the rate is decreasing over time (i.e. aggressive elimination occurs early, followed by a longer phase of slow elimination). We show that such rates optimize the efficiency and robustness of distributed routing networks under several models. We also present an application of this strategy to improve the design of airline networks.

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    Europe PubMed Central
    Article . 2015
    Data sources: PubMed Central
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    PLoS Computational Biology
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    PLoS Computational Biology
    Article . 2015 . Peer-reviewed
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      Europe PubMed Central
      Article . 2015
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      PLoS Computational Biology
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      PLoS Computational Biology
      Article . 2015 . Peer-reviewed
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    Authors: Ozan Ozdenizci; Ye Wang; Toshiaki Koike-Akino; Deniz Erdogmus;

    Deep learning methods for person identification based on electroencephalographic (EEG) brain activity encounters the problem of exploiting the temporally correlated structures or recording session specific variability within EEG. Furthermore, recent methods have mostly trained and evaluated based on single session EEG data. We address this problem from an invariant representation learning perspective. We propose an adversarial inference approach to extend such deep learning models to learn session-invariant person-discriminative representations that can provide robustness in terms of longitudinal usability. Using adversarial learning within a deep convolutional network, we empirically assess and show improvements with our approach based on longitudinally collected EEG data for person identification from half-second EEG epochs. Comment: Accepted for publication by IEEE Signal Processing Letters

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    Europe PubMed Central
    Other literature type . 2019
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    IEEE Signal Processing Letters
    Article . 2019 . Peer-reviewed
    License: IEEE Copyright
    https://doi.org/10.48550/arxiv...
    Article . 2019
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      Europe PubMed Central
      Other literature type . 2019
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      IEEE Signal Processing Letters
      Article . 2019 . Peer-reviewed
      License: IEEE Copyright
      https://doi.org/10.48550/arxiv...
      Article . 2019
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    Authors: Franke, Barbara; Stein, Jason L; McIntosh, Andrew M; Eichhammer, Peter; +289 Authors

    Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between people with schizophrenia and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders. peerReviewed final draft Article

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