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 *

242 related articles for article (PubMed ID: 20004248)

  • 1. Effect of hemodynamic variability on Granger causality analysis of fMRI.
    Deshpande G; Sathian K; Hu X
    Neuroimage; 2010 Sep; 52(3):884-96. PubMed ID: 20004248
    [TBL] [Abstract][Full Text] [Related]  

  • 2. The effect of intra- and inter-subject variability of hemodynamic responses on group level Granger causality analyses.
    Schippers MB; Renken R; Keysers C
    Neuroimage; 2011 Jul; 57(1):22-36. PubMed ID: 21316469
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Lag-based effective connectivity applied to fMRI: a simulation study highlighting dependence on experimental parameters and formulation.
    Rodrigues J; Andrade A
    Neuroimage; 2014 Apr; 89():358-77. PubMed ID: 24513528
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Is Granger causality a viable technique for analyzing fMRI data?
    Wen X; Rangarajan G; Ding M
    PLoS One; 2013; 8(7):e67428. PubMed ID: 23861763
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Granger causality analysis of fMRI BOLD signals is invariant to hemodynamic convolution but not downsampling.
    Seth AK; Chorley P; Barnett LC
    Neuroimage; 2013 Jan; 65():540-55. PubMed ID: 23036449
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Group-level impacts of within- and between-subject hemodynamic variability in fMRI.
    Badillo S; Vincent T; Ciuciu P
    Neuroimage; 2013 Nov; 82():433-48. PubMed ID: 23735261
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Measuring relative timings of brain activities using fMRI.
    Katwal SB; Gore JC; Gatenby JC; Rogers BP
    Neuroimage; 2013 Feb; 66():436-48. PubMed ID: 23110880
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Multivariate analysis of neuronal interactions in the generalized partial least squares framework: simulations and empirical studies.
    Lin FH; McIntosh AR; Agnew JA; Eden GF; Zeffiro TA; Belliveau JW
    Neuroimage; 2003 Oct; 20(2):625-42. PubMed ID: 14568440
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Influence of fMRI data sampling on the temporal characterization of the hemodynamic response.
    Dilharreguy B; Jones RA; Moonen CT
    Neuroimage; 2003 Aug; 19(4):1820-8. PubMed ID: 12948736
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Functional MRI and multivariate autoregressive models.
    Rogers BP; Katwal SB; Morgan VL; Asplund CL; Gore JC
    Magn Reson Imaging; 2010 Oct; 28(8):1058-65. PubMed ID: 20444566
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Investigating effective brain connectivity from fMRI data: past findings and current issues with reference to Granger causality analysis.
    Deshpande G; Hu X
    Brain Connect; 2012; 2(5):235-45. PubMed ID: 23016794
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A blind deconvolution approach to recover effective connectivity brain networks from resting state fMRI data.
    Wu GR; Liao W; Stramaglia S; Ding JR; Chen H; Marinazzo D
    Med Image Anal; 2013 Apr; 17(3):365-74. PubMed ID: 23422254
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Hemodynamic response function (HRF) variability confounds resting-state fMRI functional connectivity.
    Rangaprakash D; Wu GR; Marinazzo D; Hu X; Deshpande G
    Magn Reson Med; 2018 Oct; 80(4):1697-1713. PubMed ID: 29656446
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Relative latency and temporal variability of hemodynamic responses at the human primary visual cortex.
    Lin FH; Polimeni JR; Lin JL; Tsai KW; Chu YH; Wu PY; Li YT; Hsu YC; Tsai SY; Kuo WJ
    Neuroimage; 2018 Jan; 164():194-201. PubMed ID: 28119135
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Variation of BOLD hemodynamic responses across subjects and brain regions and their effects on statistical analyses.
    Handwerker DA; Ollinger JM; D'Esposito M
    Neuroimage; 2004 Apr; 21(4):1639-51. PubMed ID: 15050587
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Multi-phase passband balanced SSFP fMRI with 50ms sampling rate at 7Tesla enables high precision in resolving 100ms neuronal events.
    Chen Z; Xue R; Zhang P; Sun K; Zuo Z; An J; Chen J; He S; Chen L; Wang DJJ
    Magn Reson Imaging; 2017 Jan; 35():20-28. PubMed ID: 27580519
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Multivariate Granger causality analysis of fMRI data.
    Deshpande G; LaConte S; James GA; Peltier S; Hu X
    Hum Brain Mapp; 2009 Apr; 30(4):1361-73. PubMed ID: 18537116
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Seeing patterns through the hemodynamic veil--the future of pattern-information fMRI.
    Formisano E; Kriegeskorte N
    Neuroimage; 2012 Aug; 62(2):1249-56. PubMed ID: 22421051
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A fully Bayesian approach to the parcel-based detection-estimation of brain activity in fMRI.
    Makni S; Idier J; Vincent T; Thirion B; Dehaene-Lambertz G; Ciuciu P
    Neuroimage; 2008 Jul; 41(3):941-69. PubMed ID: 18439839
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Imaging faster neural dynamics with fast fMRI: A need for updated models of the hemodynamic response.
    Polimeni JR; Lewis LD
    Prog Neurobiol; 2021 Dec; 207():102174. PubMed ID: 34525404
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 13.