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.
200 related articles for article (PubMed ID: 31852625)
21. Accounting for Non-Gaussian Sources of Spatial Correlation in Parametric Functional Magnetic Resonance Imaging Paradigms II: A Method to Obtain First-Level Analysis Residuals with Uniform and Gaussian Spatial Autocorrelation Function and Independent and Identically Distributed Time-Series. Gopinath K; Krishnamurthy V; Lacey S; Sathian K Brain Connect; 2018 Feb; 8(1):10-21. PubMed ID: 29161884 [TBL] [Abstract][Full Text] [Related]
22. Adjusting the effect of nonstationarity in cluster-based and TFCE inference. Salimi-Khorshidi G; Smith SM; Nichols TE Neuroimage; 2011 Feb; 54(3):2006-19. PubMed ID: 20955803 [TBL] [Abstract][Full Text] [Related]
23. Cluster failure revisited: Impact of first level design and physiological noise on cluster false positive rates. Eklund A; Knutsson H; Nichols TE Hum Brain Mapp; 2019 May; 40(7):2017-2032. PubMed ID: 30318709 [TBL] [Abstract][Full Text] [Related]
24. 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]
25. The Constrained Network-Based Statistic: A New Level of Inference for Neuroimaging. Noble S; Scheinost D Med Image Comput Comput Assist Interv; 2020 Oct; 12267():458-468. PubMed ID: 33870336 [TBL] [Abstract][Full Text] [Related]
26. Cluster size statistic and cluster mass statistic: two novel methods for identifying changes in functional connectivity between groups or conditions. Ing A; Schwarzbauer C PLoS One; 2014; 9(6):e98697. PubMed ID: 24906136 [TBL] [Abstract][Full Text] [Related]
27. Probabilistic TFCE: A generalized combination of cluster size and voxel intensity to increase statistical power. Spisák T; Spisák Z; Zunhammer M; Bingel U; Smith S; Nichols T; Kincses T Neuroimage; 2019 Jan; 185():12-26. PubMed ID: 30296561 [TBL] [Abstract][Full Text] [Related]
28. Detecting activations in PET and fMRI: levels of inference and power. Friston KJ; Holmes A; Poline JB; Price CJ; Frith CD Neuroimage; 1996 Dec; 4(3 Pt 1):223-35. PubMed ID: 9345513 [TBL] [Abstract][Full Text] [Related]
29. Statistical power comparisons at 3T and 7T with a GO / NOGO task. Torrisi S; Chen G; Glen D; Bandettini PA; Baker CI; Reynolds R; Yen-Ting Liu J; Leshin J; Balderston N; Grillon C; Ernst M Neuroimage; 2018 Jul; 175():100-110. PubMed ID: 29621615 [TBL] [Abstract][Full Text] [Related]
30. Multiple imputation of missing fMRI data in whole brain analysis. Vaden KI; Gebregziabher M; Kuchinsky SE; Eckert MA Neuroimage; 2012 Apr; 60(3):1843-55. PubMed ID: 22500925 [TBL] [Abstract][Full Text] [Related]
31. A method to mitigate spatio-temporally varying task-correlated motion artifacts from overt-speech fMRI paradigms in aphasia. Krishnamurthy V; Krishnamurthy LC; Meadows ML; Gale MK; Ji B; Gopinath K; Crosson B Hum Brain Mapp; 2021 Mar; 42(4):1116-1129. PubMed ID: 33210749 [TBL] [Abstract][Full Text] [Related]
32. Selective peak inference: Unbiased estimation of raw and standardized effect size at local maxima. Davenport S; Nichols TE Neuroimage; 2020 Apr; 209():116375. PubMed ID: 31866164 [TBL] [Abstract][Full Text] [Related]