These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

365 related articles for article (PubMed ID: 19184561)

  • 1. PyMVPA: A python toolbox for multivariate pattern analysis of fMRI data.
    Hanke M; Halchenko YO; Sederberg PB; Hanson SJ; Haxby JV; Pollmann S
    Neuroinformatics; 2009; 7(1):37-53. PubMed ID: 19184561
    [TBL] [Abstract][Full Text] [Related]  

  • 2. The RUMBA software: tools for neuroimaging data analysis.
    Bly BM; Rebbechi D; Hanson SJ; Grasso G
    Neuroinformatics; 2004; 2(1):71-100. PubMed ID: 15067169
    [TBL] [Abstract][Full Text] [Related]  

  • 3. BrainIAK tutorials: User-friendly learning materials for advanced fMRI analysis.
    Kumar M; Ellis CT; Lu Q; Zhang H; Capotă M; Willke TL; Ramadge PJ; Turk-Browne NB; Norman KA
    PLoS Comput Biol; 2020 Jan; 16(1):e1007549. PubMed ID: 31940340
    [TBL] [Abstract][Full Text] [Related]  

  • 4. NeuroPycon: An open-source python toolbox for fast multi-modal and reproducible brain connectivity pipelines.
    Meunier D; Pascarella A; Altukhov D; Jas M; Combrisson E; Lajnef T; Bertrand-Dubois D; Hadid V; Alamian G; Alves J; Barlaam F; Saive AL; Dehgan A; Jerbi K
    Neuroimage; 2020 Oct; 219():117020. PubMed ID: 32522662
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Evaluation and optimization of fMRI single-subject processing pipelines with NPAIRS and second-level CVA.
    Zhang J; Anderson JR; Liang L; Pulapura SK; Gatewood L; Rottenberg DA; Strother SC
    Magn Reson Imaging; 2009 Feb; 27(2):264-78. PubMed ID: 18849131
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A Java-based fMRI processing pipeline evaluation system for assessment of univariate general linear model and multivariate canonical variate analysis-based pipelines.
    Zhang J; Liang L; Anderson JR; Gatewood L; Rottenberg DA; Strother SC
    Neuroinformatics; 2008; 6(2):123-34. PubMed ID: 18506642
    [TBL] [Abstract][Full Text] [Related]  

  • 7. PyMVPA: A Unifying Approach to the Analysis of Neuroscientific Data.
    Hanke M; Halchenko YO; Sederberg PB; Olivetti E; Fründ I; Rieger JW; Herrmann CS; Haxby JV; Hanson SJ; Pollmann S
    Front Neuroinform; 2009; 3():3. PubMed ID: 19212459
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Wyrm: A Brain-Computer Interface Toolbox in Python.
    Venthur B; Dähne S; Höhne J; Heller H; Blankertz B
    Neuroinformatics; 2015 Oct; 13(4):471-86. PubMed ID: 26001643
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Nighres: processing tools for high-resolution neuroimaging.
    Huntenburg JM; Steele CJ; Bazin PL
    Gigascience; 2018 Jul; 7(7):. PubMed ID: 29982501
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Optimization of functional MRI for detection, decoding and high-resolution imaging of the response patterns of cortical columns.
    Chaimow D; Uğurbil K; Shmuel A
    Neuroimage; 2018 Jan; 164():67-99. PubMed ID: 28461061
    [TBL] [Abstract][Full Text] [Related]  

  • 11. fMRIflows: A Consortium of Fully Automatic Univariate and Multivariate fMRI Processing Pipelines.
    Notter MP; Herholz P; Da Costa S; Gulban OF; Isik AI; Gaglianese A; Murray MM
    Brain Topogr; 2023 Mar; 36(2):172-191. PubMed ID: 36575327
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Transfer learning of deep neural network representations for fMRI decoding.
    Svanera M; Savardi M; Benini S; Signoroni A; Raz G; Hendler T; Muckli L; Goebel R; Valente G
    J Neurosci Methods; 2019 Dec; 328():108319. PubMed ID: 31585315
    [TBL] [Abstract][Full Text] [Related]  

  • 13. The connectome mapper: an open-source processing pipeline to map connectomes with MRI.
    Daducci A; Gerhard S; Griffa A; Lemkaddem A; Cammoun L; Gigandet X; Meuli R; Hagmann P; Thiran JP
    PLoS One; 2012; 7(12):e48121. PubMed ID: 23272041
    [TBL] [Abstract][Full Text] [Related]  

  • 14. An introduction to anatomical ROI-based fMRI classification analysis.
    Etzel JA; Gazzola V; Keysers C
    Brain Res; 2009 Jul; 1282():114-25. PubMed ID: 19505449
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Neu
    Heunis S; Besseling R; Lamerichs R; de Louw A; Breeuwer M; Aldenkamp B; Bergmans J
    Psychiatry Res Neuroimaging; 2018 Dec; 282():90-102. PubMed ID: 30293911
    [TBL] [Abstract][Full Text] [Related]  

  • 16. GMAC: a Matlab toolbox for spectral Granger causality analysis of fMRI data.
    Tana MG; Sclocco R; Bianchi AM
    Comput Biol Med; 2012 Oct; 42(10):943-56. PubMed ID: 22925560
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Evaluation and comparison of GLM- and CVA-based fMRI processing pipelines with Java-based fMRI processing pipeline evaluation system.
    Zhang J; Liang L; Anderson JR; Gatewood L; Rottenberg DA; Strother SC
    Neuroimage; 2008 Jul; 41(4):1242-52. PubMed ID: 18482849
    [TBL] [Abstract][Full Text] [Related]  

  • 18. PRoNTo: pattern recognition for neuroimaging toolbox.
    Schrouff J; Rosa MJ; Rondina JM; Marquand AF; Chu C; Ashburner J; Phillips C; Richiardi J; Mourão-Miranda J
    Neuroinformatics; 2013 Jul; 11(3):319-37. PubMed ID: 23417655
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Predicting brain states associated with object categories from fMRI data.
    Behroozi M; Daliri MR
    J Integr Neurosci; 2014 Dec; 13(4):645-67. PubMed ID: 25352153
    [TBL] [Abstract][Full Text] [Related]  

  • 20. The effect of acquisition resolution on orientation decoding from V1 BOLD fMRI at 7T.
    Sengupta A; Yakupov R; Speck O; Pollmann S; Hanke M
    Neuroimage; 2017 Mar; 148():64-76. PubMed ID: 28063973
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 19.