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.
289 related articles for article (PubMed ID: 28891512)
1. Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network. Zafar R; Kamel N; Naufal M; Malik AS; Dass SC; Ahmad RF; Abdullah JM; Reza F J Integr Neurosci; 2017; 16(3):275-289. PubMed ID: 28891512 [TBL] [Abstract][Full Text] [Related]
2. fMRI volume classification using a 3D convolutional neural network robust to shifted and scaled neuronal activations. Vu H; Kim HC; Jung M; Lee JH Neuroimage; 2020 Dec; 223():117328. PubMed ID: 32896633 [TBL] [Abstract][Full Text] [Related]
3. Decoding the individual finger movements from single-trial functional magnetic resonance imaging recordings of human brain activity. Shen G; Zhang J; Wang M; Lei D; Yang G; Zhang S; Du X Eur J Neurosci; 2014 Jun; 39(12):2071-82. PubMed ID: 24661456 [TBL] [Abstract][Full Text] [Related]
4. Decoding and mapping task states of the human brain via deep learning. Wang X; Liang X; Jiang Z; Nguchu BA; Zhou Y; Wang Y; Wang H; Li Y; Zhu Y; Wu F; Gao JH; Qiu B Hum Brain Mapp; 2020 Apr; 41(6):1505-1519. PubMed ID: 31816152 [TBL] [Abstract][Full Text] [Related]
5. Decoding fMRI data with support vector machines and deep neural networks. Liang Y; Bo K; Meyyappan S; Ding M J Neurosci Methods; 2024 Jan; 401():110004. PubMed ID: 37914001 [TBL] [Abstract][Full Text] [Related]
6. 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]
7. A study of decoding human brain activities from simultaneous data of EEG and fMRI using MVPA. Zafar R; Kamel N; Naufal M; Malik AS; Dass SC; Ahmad RF; Abdullah JM; Reza F Australas Phys Eng Sci Med; 2018 Sep; 41(3):633-645. PubMed ID: 29948968 [TBL] [Abstract][Full Text] [Related]
8. The effect of spatial resolution on decoding accuracy in fMRI multivariate pattern analysis. Gardumi A; Ivanov D; Hausfeld L; Valente G; Formisano E; Uludağ K Neuroimage; 2016 May; 132():32-42. PubMed ID: 26899782 [TBL] [Abstract][Full Text] [Related]
9. Spatially regularized machine learning for task and resting-state fMRI. Song X; Panych LP; Chen NK J Neurosci Methods; 2016 Jan; 257():214-28. PubMed ID: 26470627 [TBL] [Abstract][Full Text] [Related]
10. Multivariate detrending of fMRI signal drifts for real-time multiclass pattern classification. Lee D; Jang C; Park HJ Neuroimage; 2015 Mar; 108():203-13. PubMed ID: 25573669 [TBL] [Abstract][Full Text] [Related]
11. Support vector machine learning-based fMRI data group analysis. Wang Z; Childress AR; Wang J; Detre JA Neuroimage; 2007 Jul; 36(4):1139-51. PubMed ID: 17524674 [TBL] [Abstract][Full Text] [Related]
12. Multiclass fMRI data decoding and visualization using supervised self-organizing maps. Hausfeld L; Valente G; Formisano E Neuroimage; 2014 Aug; 96():54-66. PubMed ID: 24531045 [TBL] [Abstract][Full Text] [Related]
13. Reproducibility of importance extraction methods in neural network based fMRI classification. Gotsopoulos A; Saarimäki H; Glerean E; Jääskeläinen IP; Sams M; Nummenmaa L; Lampinen J Neuroimage; 2018 Nov; 181():44-54. PubMed ID: 29964190 [TBL] [Abstract][Full Text] [Related]
14. Decoding fMRI Data: A Comparison Between Support Vector Machines and Deep Neural Networks. Liang Y; Bo K; Meyyappan S; Ding M bioRxiv; 2023 Jun; ():. PubMed ID: 37398470 [TBL] [Abstract][Full Text] [Related]
15. Two-step paretial least square regression classifiers in brain-state decoding using functional magnetic resonance imaging. Long Z; Wang Y; Liu X; Yao L PLoS One; 2019; 14(4):e0214937. PubMed ID: 30970029 [TBL] [Abstract][Full Text] [Related]
16. A Multichannel 2D Convolutional Neural Network Model for Task-Evoked fMRI Data Classification. Hu J; Kuang Y; Liao B; Cao L; Dong S; Li P Comput Intell Neurosci; 2019; 2019():5065214. PubMed ID: 32082370 [TBL] [Abstract][Full Text] [Related]
17. Classification of schizophrenia and normal controls using 3D convolutional neural network and outcome visualization. Oh K; Kim W; Shen G; Piao Y; Kang NI; Oh IS; Chung YC Schizophr Res; 2019 Oct; 212():186-195. PubMed ID: 31395487 [TBL] [Abstract][Full Text] [Related]
18. Multi-subject brain decoding with multi-task feature selection. Wang L; Tang X; Liu W; Peng Y; Gao T; Xu Y Biomed Mater Eng; 2014; 24(6):2987-94. PubMed ID: 25227006 [TBL] [Abstract][Full Text] [Related]
19. Automatic Recognition of fMRI-Derived Functional Networks Using 3-D Convolutional Neural Networks. Zhao Y; Dong Q; Zhang S; Zhang W; Chen H; Jiang X; Guo L; Hu X; Han J; Liu T IEEE Trans Biomed Eng; 2018 Sep; 65(9):1975-1984. PubMed ID: 28641239 [TBL] [Abstract][Full Text] [Related]
20. Combining multivariate voxel selection and support vector machines for mapping and classification of fMRI spatial patterns. De Martino F; Valente G; Staeren N; Ashburner J; Goebel R; Formisano E Neuroimage; 2008 Oct; 43(1):44-58. PubMed ID: 18672070 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]