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High-dimensional tests for spherical location and spiked covariance [article]

Christophe Ley, Davy Paindaveine, Thomas Verdebout
<span title="2014-02-12">2014</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We further show that our results also provide high-dimensional tests for a problem that has recently attracted much attention, namely that of testing that the covariance matrix of a multinormal distribution  ...  The most classical way of addressing the spherical location problem H_0:theta=theta_0, with theta_0 a fixed location, is the so-called Watson test, which is based on the sample mean of the observations  ...  Davy Paindaveine's research is supported by an A.R.C. contract from the Communauté Française de Belgique and by the IAP research network grant nr.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1402.2823v1">arXiv:1402.2823v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/57fawpi6rzfwhd65gghbtdqvg4">fatcat:57fawpi6rzfwhd65gghbtdqvg4</a> </span>
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High-dimensional tests for spherical location and spiked covariance

Christophe Ley, Davy Paindaveine, Thomas Verdebout
<span title="">2015</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dzig5epjvbgqpkmvs5urnktqi4" style="color: black;">Journal of Multivariate Analysis</a> </i> &nbsp;
Turning to Euclidean data, we show that our results also lead to a test for the null that the covariance matrix of a high-dimensional multinormal distribution has a "θ θ θ 0 -spiked" structure.  ...  This reveals that (i) the Watson test is robust against high dimensionality, and that (ii) it allows for (n, p) -asymptotic results that are universal, in the sense that p may go to infinity arbitrarily  ...  All three authors would like to thank the Associate Editor and an anonymous referee for their comments that led to a significant improvement of the paper.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.jmva.2015.02.019">doi:10.1016/j.jmva.2015.02.019</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/h6zuewyzczdrljauftqtog6ebq">fatcat:h6zuewyzczdrljauftqtog6ebq</a> </span>
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Testing for subsphericity when n and p are of different asymptotic order

Joni Virta
<span title="">2021</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rwdjnin7wvc3xmoc6by27vqkgq" style="color: black;">Statistics and Probability Letters</a> </i> &nbsp;
We extend a test of subsphericity to the high-dimensional Gaussian regime where the spikes diverge to infinity and p/n → {0, ∞}.  ...  The test is used to derive a consistent estimator for the latent dimension of the model.  ...  Indeed, usually the spikes are taken to be constant in the literature for high-dimensional PCA, see, e.g. Baik and Silverstein (2006) ; Johnstone and Paul (2018) .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.spl.2021.109209">doi:10.1016/j.spl.2021.109209</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nvifefqrp5f7dfpv6yqumnfqei">fatcat:nvifefqrp5f7dfpv6yqumnfqei</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210805235102/https://pdf.sciencedirectassets.com/271498/AIP/1-s2.0-S0167715221001711/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEDcaCXVzLWVhc3QtMSJGMEQCIFxaqdgWy7BUV8ENjjh2MdRyAEY2TTYA7ZdF1NOzHrP4AiBaLHSPJp1BOhkJgCrWj1T0hzilFDi6I52tAvkDlXynXyr6AwhQEAQaDDA1OTAwMzU0Njg2NSIMMp6zGSec54Oykea7KtcDTHgyKEKyMy94Y5jEIWBEYg0C4Dqlqic%2Ft4y7SUPVld60GEC86EDipcfZjpHwDGzSA5czWrcb5G5diehbEiXSkOJfgJ1HQqAGsAii%2Bsu4NC0%2FuBzwFgWw0fgDajhWOFy2omPrjPirfROSVRzenzshYbnKLQeDFJxW9Ud3vxCHO8TOEMvKj9317u5HeYc4v4DEFvXxdugV%2BmqOmdkGYWOtMA5Ag7EYPj3UAB8zTbX2mKlWoamJZDYySoarKUMZyCKlTZVmv7QCnvayJhZuz5ZGlgA2TcSoatPkCFMLRExK7WwXEHaR4eigdfsD8kssHU1Si71cmCvVVRkBqHwqPdrpQtNpvIpyyRjx58CdbTAKt2dZvr6jY%2BM3uq6M6s2%2BQ6oUrGvDGFAtvYHwbQxDXxFPb6t7m9UxZ079QJO8qQKn07%2FIjsaqgDAQLA9M2lgCOHxhowqvZz6KCHFUePG0Rm82PElMx4GXPWdoesbFvi%2FqdGaENkX7SsByY0trO%2FdpWx0ULAT43kLjJIzQsV%2BUe2ICYZ97jfdfYFiJViNknfu%2Bnno5h%2F9w5MbYa%2Bxr4CMGQpZa9q0M7o1IMXpNY5GqB9wmlPJa%2Bglg3WnO8HKXMASP0jQp2BvjNNOTMP3UsYgGOqYBTQbJNWyj%2BdZiNbzLD88Cd7gmqpZR0m8amii4JJkd7C9MEBY7e8GAOpLCk71FbfO0rEpt85T8GQkN30h%2F8yb8F%2BNLQem35VeziuBRATqF1B0LFrCxLaaQnabsStpOvw741%2BqaFRzc4KDz4Oz1BHEBfMGb8Iwz5uMuOh4Ayq7GasVl6X%2FnUA2pWzS3x2nHDcYfOycpvXWkbA%2FW%2FgrjF%2FNziEryyDWfDw%3D%3D&amp;X-Amz-Algorithm=AWS4-HMAC-SHA256&amp;X-Amz-Date=20210805T235041Z&amp;X-Amz-SignedHeaders=host&amp;X-Amz-Expires=300&amp;X-Amz-Credential=ASIAQ3PHCVTYRUSLXZNN%2F20210805%2Fus-east-1%2Fs3%2Faws4_request&amp;X-Amz-Signature=0fff9a82d1fdeb1652b6f5b3e6122135dc6c2b571f5e74dbf97be1ea44376a1c&amp;hash=b8939c727c59a653ed4814ef54ca7cb72bf32ec1d80f738f768b8548157c8c64&amp;host=68042c943591013ac2b2430a89b270f6af2c76d8dfd086a07176afe7c76c2c61&amp;pii=S0167715221001711&amp;tid=spdf-1279ffbd-2903-4004-9714-de1dda9e59d4&amp;sid=9bcb6c7d8aeb464b9b-82bd-4a16833a329bgxrqa&amp;type=client" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/2c/39/2c39c326e9efc5593a89a5abdba58a03fd133421.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.spl.2021.109209"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> elsevier.com </button> </a>

Spike-triggered covariance: geometric proof, symmetry properties, and extension beyond Gaussian stimuli

Inés Samengo, Tim Gollisch
<span title="2012-07-15">2012</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2awqvcobm5bw3bostcqrykczhe" style="color: black;">Journal of Computational Neuroscience</a> </i> &nbsp;
The space of sensory stimuli is complex and high-dimensional. Yet, single neurons in sensory systems are typically affected by only a small subset of the vast space of all possible stimuli.  ...  Furthermore, we present a new resampling method for assessing statistical significance of identified relevant stimuli, applicable to spherical and elliptic stimulus distributions.  ...  We therefore arrive at the well-known recipe for estimating the single relevant direction by premultiplying the STA by the inverse of the prior covariance matrix (Theunissen et al. 2001; Paninski 2003  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10827-012-0411-y">doi:10.1007/s10827-012-0411-y</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/22798148">pmid:22798148</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC3558678/">pmcid:PMC3558678</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rynj4fwuwfa7tot47bal7nujtm">fatcat:rynj4fwuwfa7tot47bal7nujtm</a> </span>
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A survey of high dimension low sample size asymptotics

Makoto Aoshima, Dan Shen, Haipeng Shen, Kazuyoshi Yata, Yi-Hui Zhou, J. S. Marron
<span title="">2018</span> <i title="Wiley"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rwepdzab75hf3n3x7zffdclbrm" style="color: black;">Australian &amp; New Zealand journal of statistics (Print)</a> </i> &nbsp;
This is a survey of one of those areas, initiated by a seminal paper in 2005, on high dimension low sample size asymptotics.  ...  An interesting characteristic of that first paper, and of many of the following papers, is that they contain deep and insightful concepts which are frequently surprising and counter-intuitive, yet have  ...  The research of the first author was partially supported by Grants-in-Aid for Scientific Research (A) and Challenging Exploratory Research, Japan Society for the Promotion of Science (  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1111/anzs.12212">doi:10.1111/anzs.12212</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/30197552">pmid:30197552</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6124695/">pmcid:PMC6124695</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/66hifh2me5fslg7ymp6ibe3ivi">fatcat:66hifh2me5fslg7ymp6ibe3ivi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200504172628/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC6124695&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b0/6d/b06dc08f6947f4128e91fe1fee93d89de69e529d.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1111/anzs.12212"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6124695" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Sharp detection in PCA under correlations: All eigenvalues matter

Edgar Dobriban
<span title="">2017</span> <i title="Institute of Mathematical Statistics"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/uckskqht6vda3pkvsttysa4tvq" style="color: black;">Annals of Statistics</a> </i> &nbsp;
In high dimensional data, the "signal" eigenvalues corresponding to weak principal components (PCs) do not necessarily separate from the bulk of the "noise" eigenvalues.  ...  We consider a nonparametric, non-Gaussian generalization of the spiked model to the setting of Marchenko and Pastur (1967).  ...  Acknowledgments We are grateful to David Donoho for his encouragement, inspiring guidance and feedback on the manuscript; and to Iain Johnstone for his enthusiastic interest and helpful suggestions.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1214/16-aos1514">doi:10.1214/16-aos1514</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mauf6mj5qve3ffmmkoiwpz7ywe">fatcat:mauf6mj5qve3ffmmkoiwpz7ywe</a> </span>
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High-dimensional covariance matrices in elliptical distributions with application to spherical test [article]

Jiang Hu, Weiming Li, Zhi Liu, Wang Zhou
<span title="2018-03-21">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This general theoretical result has wide applications and, as an example, it is then applied to test the sphericity of elliptical populations.  ...  This paper discusses fluctuations of linear spectral statistics of high-dimensional sample covariance matrices when the underlying population follows an elliptical distribution.  ...  Testing for high-dimensional spherical distributions. 3.1. John's test and its extension. In this section, we revisit the sphericity test for covariance matrices in high-dimensional frameworks.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1803.07793v1">arXiv:1803.07793v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tsxohweaarckbln4hyhbyg5qty">fatcat:tsxohweaarckbln4hyhbyg5qty</a> </span>
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Testing for subsphericity when n and p are of different asymptotic order [article]

Joni Virta
<span title="2021-06-29">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We extend a classical test of subsphericity, based on the first two moments of the eigenvalues of the sample covariance matrix, to the high-dimensional regime where the signal eigenvalues of the covariance  ...  As our second main contribution, we use the test to derive a consistent estimator for the latent dimension of the model.  ...  Indeed, usually the spikes are taken to be constant in the literature for high-dimensional PCA, see, e.g. Baik and Silverstein (2006) ; Johnstone and Paul (2018) .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2101.09711v3">arXiv:2101.09711v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/sqnmb3gsxrdcldver4wntqlshi">fatcat:sqnmb3gsxrdcldver4wntqlshi</a> </span>
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Tetrode technology: advances in implantable hardware, neuroimaging, and data analysis techniques

M.S Jog, C.I Connolly, Y Kubota, D.R Iyengar, L Garrido, R Harlan, A.M Graybiel
<span title="">2002</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/huhco7lwxvct3fbbxk44mmpflu" style="color: black;">Journal of Neuroscience Methods</a> </i> &nbsp;
The technical advances in hardware and software for multiunit recordings have made it easier to gather data from a large number of neurons for behavioral correlations.  ...  This paper discusses several such advances in implantable hardware, magnetic resonance imaging of electrodes in situ, and data analysis software for multiple simultaneous signals. #  ...  Acknowledgements This work was supported by NIMH RO1-MH60379, NINDS P50-NS38372 and NIMH RO3-MH57878; the Medical Research Council of Canada, Royal College of Physicians and Surgeons of Canada; and SRI  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/s0165-0270(02)00092-4">doi:10.1016/s0165-0270(02)00092-4</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/12100979">pmid:12100979</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tbo74lnp4rdkhg4rj2f3vzdo3a">fatcat:tbo74lnp4rdkhg4rj2f3vzdo3a</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170808205332/http://www.ece.uvic.ca/~bctill/papers/neurimp/Jog_etal_2002.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/18/80/1880177f829ead4a00bdba069e1943eb00b15a0a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/s0165-0270(02)00092-4"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Deep Learning-Based Template Matching Spike Classification for Extracellular Recordings

In Yong Park, Junsik Eom, Hanbyol Jang, Sewon Kim, Sanggeon Park, Yeowool Huh, Dosik Hwang
<span title="2019-12-31">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/smrngspzhzce7dy6ofycrfxbim" style="color: black;">Applied Sciences</a> </i> &nbsp;
And for manual spike sorting, it requires professional knowledge along with extensive time cost and suffers from human bias.  ...  As a result, we showed that the deep learning-based classification can classify spikes from extracellular recordings, even showing high classification accuracy on spikes that are difficult even for manual  ...  When performed on a dataset with 3526 spikes using an Intel Xeon E5-1620 CPU equipped with a Nvidia Titan X GPU and 96 GB RAM, the model took approximately 9 s for training and 3 s for testing.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app10010301">doi:10.3390/app10010301</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7mlipfmiqje2talyvpcepembly">fatcat:7mlipfmiqje2talyvpcepembly</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200101013232/https://res.mdpi.com/d_attachment/applsci/applsci-10-00301/article_deploy/applsci-10-00301.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e5/4d/e54de644e61e7a5100511b2f62cec29d86030fea.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app10010301"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Light Scattering by Quasi-Spherical Ice Crystals

Timo Nousiainen, Greg M. McFarquhar
<span title="">2004</span> <i title="American Meteorological Society"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/52zwklo3cjcbpp3ocf6docuwwq" style="color: black;">Journal of the Atmospheric Sciences</a> </i> &nbsp;
The shapes and single-scattering properties of small, irregular, quasi-spherical ice crystals, with equivalent radii between approximately 8 and 90 m and size parameters from about 90 to 1000, are studied  ...  the shapes of small, quasi-spherical ice crystals in cirrus.  ...  We thank Karri Muinonen and the two anonymous referees for their helpful comments.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1175/1520-0469(2004)061&lt;2229:lsbqic&gt;2.0.co;2">doi:10.1175/1520-0469(2004)061&lt;2229:lsbqic&gt;2.0.co;2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vnbqkmm6azhnnif7o6dvqfsqse">fatcat:vnbqkmm6azhnnif7o6dvqfsqse</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170810074548/http://curry.eas.gatech.edu/MAP/pdf/nousiainen_mcfarquhar2004.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a4/73/a473942ead606072d4efae3feae802c7a0d7fa37.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1175/1520-0469(2004)061&lt;2229:lsbqic&gt;2.0.co;2"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

SPIKING NEURAL NETWORKS FOR BREAST CANCER CLASSIFICATION USING RADAR TARGET SIGNATURES

Brian McGinley, Martin O'Halloran, Raquel Cruz Conceicao, Fearghal Morgan, Martin Glavin, Edward Jones
<span title="">2010</span> <i title="EMW Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/nnlsqbhd6rdehnf3w63xosusky" style="color: black;">Progress In Electromagnetics Research C</a> </i> &nbsp;
This paper investigates Spiking Neural Networks (SNNs) applied as a novel tumour classification method.  ...  Rather than simply examining the dielectric properties of scatterers within the breast, other features of scatterers must be used for classification.  ...  In this research, high PCA values are mapped to high spike frequencies while low PCA values are mapped to low frequencies.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2528/pierc10100202">doi:10.2528/pierc10100202</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/smimiyacgvf6jjkk4oeecmiuem">fatcat:smimiyacgvf6jjkk4oeecmiuem</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180720140836/http://www.jpier.org/PIERC/pierc17/07.10100202.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/13/91/1391521aa39652f61437b321e8c39695cd68cf08.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2528/pierc10100202"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

A Bayesian supervised dual-dimensionality reduction model for simultaneous decoding of LFP and spike train signals

Andrew Holbrook, Alexander Vandenberg-Rodes, Norbert Fortin, Babak Shahbaba
<span title="">2017</span> <i title="Wiley"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/mgn2wo4tmzc7vm7yg6mhkh7qg4" style="color: black;">Stat</a> </i> &nbsp;
Despite being one probabilistic unit, the model consists of multiple modules: exponential principal components analysis (PCA) and wavelet PCA are used for dimensionality reduction in the spike train and  ...  The sDDR model is applied to data from an experiment testing the capacity for non-spatial sequential memory in rats.  ...  Acknowledgements This work was partially supported by NIH grant R01-AI107034 and NSF grant DMS-1622490. The authors would like to thank Hernando Ombao for helpful discussion.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1002/sta4.137">doi:10.1002/sta4.137</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/28529731">pmid:28529731</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5433266/">pmcid:PMC5433266</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/33taludhv5hlplzomy6bsmm5jm">fatcat:33taludhv5hlplzomy6bsmm5jm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190502082134/https://cloudfront.escholarship.org/dist/prd/content/qt77q6p1g0/qt77q6p1g0.pdf?t=ozs4kv" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/76/f2/76f242e90e1ad52eaf198a61dfa90516b5906896.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1002/sta4.137"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> wiley.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5433266" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

A comparison of deep learning and linear-nonlinear cascade approaches to neural encoding [article]

Theodore H. Moskovitz, Nicholas A. Roy, Jonathan W. Pillow
<span title="2018-11-06">2018</span> <i title="Cold Spring Harbor Laboratory"> bioRxiv </i> &nbsp; <span class="release-stage" >pre-print</span>
covariance (STC), information-theoretic spike-triggered averaging and covariance (iSTAC), and maximum likelihood estimators also known as "maximally informative dimensions" (MID).  ...  We discuss the implications of these findings for both the fitting and interpretation of LNP encoding models.  ...  This class includes information-theoretic Spike-Triggered Average and Covariance (iSTAC) Bayesian spike-triggered covariance, and moment-based estimators for generalized quadratic models (GQMs) (Park  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/463422">doi:10.1101/463422</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/u654b5fb2vhhlclfuw5dgdbgsa">fatcat:u654b5fb2vhhlclfuw5dgdbgsa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200325151925/https://www.biorxiv.org/content/biorxiv/early/2018/11/06/463422.full.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ea/b2/eab2b672db8bc81c57c5f4e9b45797a70e1b8f75.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/463422"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> biorxiv.org </button> </a>

Estimating the Number of Sources in Magnetoencephalography Using Spiked Population Eigenvalues [article]

Zhigang Yao, Ye Zhang, Zhidong Bai, William F. Eddy
<span title="2017-07-05">2017</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
To uncover the unknown sources from the very noisy MEG data, we introduce a framework, referred to as the intrinsic dimensionality (ID) of the optimal transformation for the SNR rescaling functional.  ...  It is defined as the number of the spiked population eigenvalues of the associated transformed data matrix.  ...  The location of each dipole (a total of four) is expressed in terms of spherical coordinates (r,θ,φ), where r is radial distance, θ is inclination and φ is azimuth.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1707.01225v1">arXiv:1707.01225v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dy6iuwwevfdvnekp5wtsmymkru">fatcat:dy6iuwwevfdvnekp5wtsmymkru</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200908115244/https://arxiv.org/pdf/1707.01225v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a3/7e/a37e7b341d64c5ec8374a3375090c4e446ba1874.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1707.01225v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>
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