257 related articles for article (PubMed ID: 30735828)
1. On the analysis of rapidly sampled fMRI data.
Chen JE; Polimeni JR; Bollmann S; Glover GH
Neuroimage; 2019 Mar; 188():807-820. PubMed ID: 30735828
[TBL] [Abstract][Full Text] [Related]
2. Serial correlations in single-subject fMRI with sub-second TR.
Bollmann S; Puckett AM; Cunnington R; Barth M
Neuroimage; 2018 Feb; 166():152-166. PubMed ID: 29066396
[TBL] [Abstract][Full Text] [Related]
3. Model-based physiological noise removal in fast fMRI.
Agrawal U; Brown EN; Lewis LD
Neuroimage; 2020 Jan; 205():116231. PubMed ID: 31589991
[TBL] [Abstract][Full Text] [Related]
4. Modular preprocessing pipelines can reintroduce artifacts into fMRI data.
Lindquist MA; Geuter S; Wager TD; Caffo BS
Hum Brain Mapp; 2019 Jun; 40(8):2358-2376. PubMed ID: 30666750
[TBL] [Abstract][Full Text] [Related]
5. Effective degrees of freedom of the Pearson's correlation coefficient under autocorrelation.
Afyouni S; Smith SM; Nichols TE
Neuroimage; 2019 Oct; 199():609-625. PubMed ID: 31158478
[TBL] [Abstract][Full Text] [Related]
6. Improving temporal resolution in fMRI using a 3D spiral acquisition and low rank plus sparse (L+S) reconstruction.
Petrov AY; Herbst M; Andrew Stenger V
Neuroimage; 2017 Aug; 157():660-674. PubMed ID: 28684333
[TBL] [Abstract][Full Text] [Related]
7. A comprehensive evaluation of increasing temporal resolution with multiband-accelerated protocols and effects on statistical outcome measures in fMRI.
Demetriou L; Kowalczyk OS; Tyson G; Bello T; Newbould RD; Wall MB
Neuroimage; 2018 Aug; 176():404-416. PubMed ID: 29738911
[TBL] [Abstract][Full Text] [Related]
8. Accurate modeling of temporal correlations in rapidly sampled fMRI time series.
Corbin N; Todd N; Friston KJ; Callaghan MF
Hum Brain Mapp; 2018 Oct; 39(10):3884-3897. PubMed ID: 29885101
[TBL] [Abstract][Full Text] [Related]
9. Simultaneous Multislice Resting-State Functional Magnetic Resonance Imaging at 3 Tesla: Slice-Acceleration-Related Biases in Physiological Effects.
Golestani AM; Faraji-Dana Z; Kayvanrad M; Setsompop K; Graham SJ; Chen JJ
Brain Connect; 2018 Mar; 8(2):82-93. PubMed ID: 29226689
[TBL] [Abstract][Full Text] [Related]
10. Inverse transformed encoding models - a solution to the problem of correlated trial-by-trial parameter estimates in fMRI decoding.
Soch J; Allefeld C; Haynes JD
Neuroimage; 2020 Apr; 209():116449. PubMed ID: 31866165
[TBL] [Abstract][Full Text] [Related]
11. WHOCARES: WHOle-brain CArdiac signal REgression from highly accelerated simultaneous multi-Slice fMRI acquisitions.
Colenbier N; Marino M; Arcara G; Frederick B; Pellegrino G; Marinazzo D; Ferrazzi G
J Neural Eng; 2022 Sep; 19(5):. PubMed ID: 35998568
[No Abstract] [Full Text] [Related]
12. Rapid whole-brain resting-state fMRI at 3 T: Efficiency-optimized three-dimensional EPI versus repetition time-matched simultaneous-multi-slice EPI.
Stirnberg R; Huijbers W; Brenner D; Poser BA; Breteler M; Stöcker T
Neuroimage; 2017 Dec; 163():81-92. PubMed ID: 28923276
[TBL] [Abstract][Full Text] [Related]
13. A comparison of denoising pipelines in high temporal resolution task-based functional magnetic resonance imaging data.
Mayer AR; Ling JM; Dodd AB; Shaff NA; Wertz CJ; Hanlon FM
Hum Brain Mapp; 2019 Sep; 40(13):3843-3859. PubMed ID: 31119818
[TBL] [Abstract][Full Text] [Related]
14. Potential pitfalls when denoising resting state fMRI data using nuisance regression.
Bright MG; Tench CR; Murphy K
Neuroimage; 2017 Jul; 154():159-168. PubMed ID: 28025128
[TBL] [Abstract][Full Text] [Related]
15. Optimizing fMRI preprocessing pipelines for block-design tasks as a function of age.
Churchill NW; Raamana P; Spring R; Strother SC
Neuroimage; 2017 Jul; 154():240-254. PubMed ID: 28216431
[TBL] [Abstract][Full Text] [Related]
16. LEICA: Laplacian eigenmaps for group ICA decomposition of fMRI data.
Liu C; JaJa J; Pessoa L
Neuroimage; 2018 Apr; 169():363-373. PubMed ID: 29246846
[TBL] [Abstract][Full Text] [Related]
17. Physiological denoising of BOLD fMRI data using Regressor Interpolation at Progressive Time Delays (RIPTiDe) processing of concurrent fMRI and near-infrared spectroscopy (NIRS).
Frederick Bd; Nickerson LD; Tong Y
Neuroimage; 2012 Apr; 60(3):1913-23. PubMed ID: 22342801
[TBL] [Abstract][Full Text] [Related]
18. Prospective motion correction in functional MRI using simultaneous multislice imaging and multislice-to-volume image registration.
Hoinkiss DC; Erhard P; Breutigam NJ; von Samson-Himmelstjerna F; Günther M; Porter DA
Neuroimage; 2019 Oct; 200():159-173. PubMed ID: 31226496
[TBL] [Abstract][Full Text] [Related]
19. Analysis strategies for high-resolution UHF-fMRI data.
Polimeni JR; Renvall V; Zaretskaya N; Fischl B
Neuroimage; 2018 Mar; 168():296-320. PubMed ID: 28461062
[TBL] [Abstract][Full Text] [Related]
20. Accurate autocorrelation modeling substantially improves fMRI reliability.
Olszowy W; Aston J; Rua C; Williams GB
Nat Commun; 2019 Dec; 10(1):1220. PubMed ID: 30899012
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]