Výsledky vyhledávání - "Mark Jarmasz"

A pattern recognition application framework for biomedical datasets

Autor: Ray L. Somorjai, Rodrigo A. Vivanco, Aleksander B. Demko, Nick J. Pizzi, Mark Jarmasz

Publikováno v: IEEE Engineering in Medicine and Biology Magazine. 26:82-85

Scopira facilitates the development of high-performance applications by providing many useful subsystems, flexible and efficient data models, low-level tools such as memory management and serialization, GUI constructs, high-level visualization module

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::21b1e1a5a9fd82d1c41f6b864fa0c77d
https://doi.org/10.1109/memb.2007.335583

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Exploratory data analysis reveals visuovisual interhemispheric transfer in functional magnetic resonance imaging

Autor: Mark Jarmasz, Sara Sullivan, Andrew Hamilton, Gerhard Stroink, Ryan C.N. D'Arcy

Publikováno v: Magnetic Resonance in Medicine. 55:952-958

We used an exploratory data analysis approach to detect interhemispheric processing of complex visual stimuli in functional magnetic resonance imaging (fMRI). A crossed-uncrossed visual field paradigm was used to elicit interhemispheric transfer of p

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6a50f8cdd53aab5e89bf8b5e473fb540
https://doi.org/10.1002/mrm.20839

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Neuroanatomy of coprolalia in Tourette syndrome using functional magnetic resonance imaging

Autor: Mark Jarmasz, Aidan Stokes, James R. Clarke, Ray L. Somorjai, Robert Vandorpe, Larry Gates, Serdar M. Dursun

Publikováno v: Progress in Neuro-Psychopharmacology and Biological Psychiatry. 28:397-400

Objective : To determine the neural substrates of phonic tics in Tourette syndrome (TS) using functional magnetic resonance imaging (fMRI) and compare with a proposed tic-generating network (TGN). Patients : One with TS and one normal control. Method

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::41d3c252bc700e834b4091eef4f57f62
https://doi.org/10.1016/j.pnpbp.2003.10.017

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Comparison of two exploratory data analysis methods for fMRI: fuzzy clustering vs. principal component analysis

Autor: Lawrence Ryner, Ray L. Somorjai, Mark Jarmasz, Wolfgang Richter, Richard Baumgartner, Randy Summers

Publikováno v: Magnetic Resonance Imaging. 18:89-94

Exploratory data-driven methods such as Fuzzy clustering analysis (FCA) and Principal component analysis (PCA) may be considered as hypothesis-generating procedures that are complementary to the hypothesis-led statistical inferential methods in funct

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b29004e517c27510a05ed7c5ced35ffe
https://doi.org/10.1016/s0730-725x(99)00102-2

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Resampling as a cluster validation technique in fMRI

Autor: Randy Summers, R. L. Somorjai, Lawrence Ryner, Richard Baumgartner, Mark Jarmasz, Wolfgang Richter

Exploratory, data-driven analysis approaches such as cluster analysis, principal component analysis, independent component analysis, or neural network-based techniques are complementary to hypothesis-led methods. They may be considered as hypothesis

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::218720181b6a99942b600e402e64f543
https://nrc-publications.canada.ca/eng/view/object/?id=1572b0dc-b3c5-410e-87b7-3f256f9b6b58

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Motor area activity during mental rotation studied by time-resolved single-trial fMRI

Autor: Carola Tegeler, Randy Summers, Ravi S. Menon, Seong-Gi Kim, Joseph S. Gati, Apostolos P. Georgopoulos, Ray L. Somorjai, Wolfgang Richter, Mark Jarmasz, Kamil Ugurbil

Publikováno v: Scopus-Elsevier

The functional equivalence of overt movements and dynamic imagery is of fundamental importance in neuroscience. Here, we investigated the participation of the neocortical motor areas in a classic task of dynamic imagery, Shepard and Metzler's mental

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7126daf88669da611d3782a9e91accd1
https://nrc-publications.canada.ca/eng/view/object/?id=0803f5b6-9636-4fc9-8694-f6ccc6f0e247

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