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 *

197 related articles for article (PubMed ID: 19596072)

  • 21. Empirical Bayesian localization of event-related time-frequency neural activity dynamics.
    Cai C; Hinkley L; Gao Y; Hashemi A; Haufe S; Sekihara K; Nagarajan SS
    Neuroimage; 2022 Sep; 258():119369. PubMed ID: 35700943
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Bayesian inverse analysis of neuromagnetic data using cortically constrained multiple dipoles.
    Auranen T; Nummenmaa A; Hämäläinen MS; Jääskeläinen IP; Lampinen J; Vehtari A; Sams M
    Hum Brain Mapp; 2007 Oct; 28(10):979-94. PubMed ID: 17370346
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Hierarchical Bayesian estimation for MEG inverse problem.
    Sato MA; Yoshioka T; Kajihara S; Toyama K; Goda N; Doya K; Kawato M
    Neuroimage; 2004 Nov; 23(3):806-26. PubMed ID: 15528082
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Estimation of neural dynamics from MEG/EEG cortical current density maps: application to the reconstruction of large-scale cortical synchrony.
    David O; Garnero L; Cosmelli D; Varela FJ
    IEEE Trans Biomed Eng; 2002 Sep; 49(9):975-87. PubMed ID: 12214887
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Probabilistic algorithms for MEG/EEG source reconstruction using temporal basis functions learned from data.
    Zumer JM; Attias HT; Sekihara K; Nagarajan SS
    Neuroimage; 2008 Jul; 41(3):924-40. PubMed ID: 18455439
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Bayesian multi-dipole modelling in the frequency domain.
    Luria G; Duran D; Visani E; Sommariva S; Rotondi F; Rossi Sebastiano D; Panzica F; Piana M; Sorrentino A
    J Neurosci Methods; 2019 Jan; 312():27-36. PubMed ID: 30452978
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Non-Gaussian probabilistic MEG source localisation based on kernel density estimation.
    Mohseni HR; Kringelbach ML; Woolrich MW; Baker A; Aziz TZ; Probert-Smith P
    Neuroimage; 2014 Feb; 87():444-64. PubMed ID: 24055702
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Error bounds for EEG and MEG dipole source localization.
    Mosher JC; Spencer ME; Leahy RM; Lewis PS
    Electroencephalogr Clin Neurophysiol; 1993 May; 86(5):303-21. PubMed ID: 7685264
    [TBL] [Abstract][Full Text] [Related]  

  • 29. STRAPS: A Fully Data-Driven Spatio-Temporally Regularized Algorithm for M/EEG Patch Source Imaging.
    Liu K; Yu ZL; Wu W; Gu Z; Li Y
    Int J Neural Syst; 2015 Jun; 25(4):1550016. PubMed ID: 25903226
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Spatiotemporal Bayesian inference dipole analysis for MEG neuroimaging data.
    Jun SC; George JS; Paré-Blagoev J; Plis SM; Ranken DM; Schmidt DM; Wood CC
    Neuroimage; 2005 Oct; 28(1):84-98. PubMed ID: 16023866
    [TBL] [Abstract][Full Text] [Related]  

  • 31. An fMRI-constrained MEG source analysis with procedures for dividing and grouping activation.
    Fujimaki N; Hayakawa T; Nielsen M; Knösche TR; Miyauchi S
    Neuroimage; 2002 Sep; 17(1):324-43. PubMed ID: 12482087
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Quantitative Evaluation in Estimating Sources Underlying Brain Oscillations Using Current Source Density Methods and Beamformer Approaches.
    Halder T; Talwar S; Jaiswal AK; Banerjee A
    eNeuro; 2019; 6(4):. PubMed ID: 31311804
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Bayesian analysis of the neuromagnetic inverse problem with l(p)-norm priors.
    Auranen T; Nummenmaa A; Hämäläinen MS; Jääskeläinen IP; Lampinen J; Vehtari A; Sams M
    Neuroimage; 2005 Jul; 26(3):870-84. PubMed ID: 15955497
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Linear inverse solutions: simulations from a realistic head model in MEG.
    Soufflet L; Boeijinga PH
    Brain Topogr; 2005; 18(2):87-99. PubMed ID: 16341577
    [TBL] [Abstract][Full Text] [Related]  

  • 35. A Novel Scanning Algorithm for MEG/EEG imaging using Covariance Partitioning and Noise Learning.
    Cai C; Sekihara K; Nagarajan SS
    Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():4803-4806. PubMed ID: 31946936
    [TBL] [Abstract][Full Text] [Related]  

  • 36. MEG source localization under multiple constraints: an extended Bayesian framework.
    Mattout J; Phillips C; Penny WD; Rugg MD; Friston KJ
    Neuroimage; 2006 Apr; 30(3):753-67. PubMed ID: 16368248
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Modified covariance beamformer for solving MEG inverse problem in the environment with correlated sources.
    Kuznetsova A; Nurislamova Y; Ossadtchi A
    Neuroimage; 2021 Mar; 228():117677. PubMed ID: 33385549
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Testing covariance models for MEG source reconstruction of hippocampal activity.
    O'Neill GC; Barry DN; Tierney TM; Mellor S; Maguire EA; Barnes GR
    Sci Rep; 2021 Sep; 11(1):17615. PubMed ID: 34475476
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Data-driven parceling and entropic inference in MEG.
    Lapalme E; Lina JM; Mattout J
    Neuroimage; 2006 Mar; 30(1):160-71. PubMed ID: 16426867
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Variational Bayesian inversion of the equivalent current dipole model in EEG/MEG.
    Kiebel SJ; Daunizeau J; Phillips C; Friston KJ
    Neuroimage; 2008 Jan; 39(2):728-41. PubMed ID: 17951076
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 10.