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 *

132 related articles for article (PubMed ID: 37120044)

  • 1. Unsupervised representation learning of spontaneous MEG data with nonlinear ICA.
    Zhu Y; Parviainen T; Heinilä E; Parkkonen L; Hyvärinen A
    Neuroimage; 2023 Jul; 274():120142. PubMed ID: 37120044
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Decoding attentional states for neurofeedback: Mindfulness vs. wandering thoughts.
    Zhigalov A; Heinilä E; Parviainen T; Parkkonen L; Hyvärinen A
    Neuroimage; 2019 Jan; 185():565-574. PubMed ID: 30317018
    [TBL] [Abstract][Full Text] [Related]  

  • 3. MEGnet: Automatic ICA-based artifact removal for MEG using spatiotemporal convolutional neural networks.
    Treacher AH; Garg P; Davenport E; Godwin R; Proskovec A; Bezerra LG; Murugesan G; Wagner B; Whitlow CT; Stitzel JD; Maldjian JA; Montillo AA
    Neuroimage; 2021 Nov; 241():118402. PubMed ID: 34274419
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Data-driven tensor independent component analysis for model-based connectivity neurofeedback.
    Koush Y; Masala N; Scharnowski F; Van De Ville D
    Neuroimage; 2019 Jan; 184():214-226. PubMed ID: 30176368
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Representation learning of resting state fMRI with variational autoencoder.
    Kim JH; Zhang Y; Han K; Wen Z; Choi M; Liu Z
    Neuroimage; 2021 Nov; 241():118423. PubMed ID: 34303794
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A computational paradigm for real-time MEG neurofeedback for dynamic allocation of spatial attention.
    Rana KD; Khan S; Hämäläinen MS; Vaina LM
    Biomed Eng Online; 2020 Jun; 19(1):45. PubMed ID: 32532277
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Independent component analysis of short-time Fourier transforms for spontaneous EEG/MEG analysis.
    Hyvärinen A; Ramkumar P; Parkkonen L; Hari R
    Neuroimage; 2010 Jan; 49(1):257-71. PubMed ID: 19699307
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Deep Convolutional Neural Networks for Feature-Less Automatic Classification of Independent Components in Multi-Channel Electrophysiological Brain Recordings.
    Croce P; Zappasodi F; Marzetti L; Merla A; Pizzella V; Chiarelli AM
    IEEE Trans Biomed Eng; 2019 Aug; 66(8):2372-2380. PubMed ID: 30582523
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Deriving frequency-dependent spatial patterns in MEG-derived resting state sensorimotor network: A novel multiband ICA technique.
    Nugent AC; Luber B; Carver FW; Robinson SE; Coppola R; Zarate CA
    Hum Brain Mapp; 2017 Feb; 38(2):779-791. PubMed ID: 27770478
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Inferring task-related networks using independent component analysis in magnetoencephalography.
    Luckhoo H; Hale JR; Stokes MG; Nobre AC; Morris PG; Brookes MJ; Woolrich MW
    Neuroimage; 2012 Aug; 62(1):530-41. PubMed ID: 22569064
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Group-level spatial independent component analysis of Fourier envelopes of resting-state MEG data.
    Ramkumar P; Parkkonen L; Hyvärinen A
    Neuroimage; 2014 Feb; 86():480-91. PubMed ID: 24185028
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Interpretable many-class decoding for MEG.
    Csaky R; van Es MWJ; Jones OP; Woolrich M
    Neuroimage; 2023 Nov; 282():120396. PubMed ID: 37805019
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Group differences in MEG-ICA derived resting state networks: Application to major depressive disorder.
    Nugent AC; Robinson SE; Coppola R; Furey ML; Zarate CA
    Neuroimage; 2015 Sep; 118():1-12. PubMed ID: 26032890
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Rejecting deep brain stimulation artefacts from MEG data using ICA and mutual information.
    Abbasi O; Hirschmann J; Schmitz G; Schnitzler A; Butz M
    J Neurosci Methods; 2016 Aug; 268():131-41. PubMed ID: 27090949
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Comparison of beamformer and ICA for dynamic connectivity analysis: A simultaneous MEG-SEEG study.
    Coelli S; Medina Villalon S; Bonini F; Velmurugan J; López-Madrona VJ; Carron R; Bartolomei F; Badier JM; Bénar CG
    Neuroimage; 2023 Jan; 265():119806. PubMed ID: 36513288
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Source-space ICA for MEG source imaging.
    Jonmohamadi Y; Jones RD
    J Neural Eng; 2016 Feb; 13(1):016005. PubMed ID: 26644284
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Decoding Speech from Single Trial MEG Signals Using Convolutional Neural Networks and Transfer Learning.
    Dash D; Ferrari P; Heitzman D; Wang J
    Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():5531-5535. PubMed ID: 31947107
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Interictal networks in magnetoencephalography.
    Malinowska U; Badier JM; Gavaret M; Bartolomei F; Chauvel P; Bénar CG
    Hum Brain Mapp; 2014 Jun; 35(6):2789-805. PubMed ID: 24105895
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Magnetoencephalographic and functional MRI connectomics in schizophrenia via intra- and inter-network connectivity.
    Houck JM; Çetin MS; Mayer AR; Bustillo JR; Stephen J; Aine C; Cañive J; Perrone-Bizzozero N; Thoma RJ; Brookes MJ; Calhoun VD
    Neuroimage; 2017 Jan; 145(Pt A):96-106. PubMed ID: 27725313
    [TBL] [Abstract][Full Text] [Related]  

  • 20. ICA methods for MEG imaging.
    Moran JE; Drake CL; Tepley N
    Neurol Clin Neurophysiol; 2004 Nov; 2004():72. PubMed ID: 16012654
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.