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For: Keilholz SD, Pan WJ, Billings J, Nezafati M, Shakil S. Noise and non-neuronal contributions to the BOLD signal: applications to and insights from animal studies. Neuroimage 2017;154:267-81. [PMID: 28017922 DOI: 10.1016/j.neuroimage.2016.12.019] [Cited by in Crossref: 14] [Cited by in F6Publishing: 13] [Article Influence: 2.3] [Reference Citation Analysis]
Number Citing Articles
1 Kelly RE Jr, Hoptman MJ, Lee S, Alexopoulos GS, Gunning FM, McKeown MJ. Seed-based dual regression: An illustration of the impact of dual regression's inherent filtering of global signal. J Neurosci Methods 2022;366:109410. [PMID: 34798212 DOI: 10.1016/j.jneumeth.2021.109410] [Reference Citation Analysis]
2 Drew PJ, Winder AT, Zhang Q. Twitches, Blinks, and Fidgets: Important Generators of Ongoing Neural Activity. Neuroscientist 2019;25:298-313. [PMID: 30311838 DOI: 10.1177/1073858418805427] [Cited by in Crossref: 14] [Cited by in F6Publishing: 9] [Article Influence: 3.5] [Reference Citation Analysis]
3 Yousefi B, Shin J, Schumacher EH, Keilholz SD. Quasi-periodic patterns of intrinsic brain activity in individuals and their relationship to global signal. Neuroimage 2018;167:297-308. [PMID: 29175200 DOI: 10.1016/j.neuroimage.2017.11.043] [Cited by in Crossref: 35] [Cited by in F6Publishing: 26] [Article Influence: 7.0] [Reference Citation Analysis]
4 Thompson GJ. Neural and metabolic basis of dynamic resting state fMRI. Neuroimage 2018;180:448-62. [PMID: 28899744 DOI: 10.1016/j.neuroimage.2017.09.010] [Cited by in Crossref: 27] [Cited by in F6Publishing: 26] [Article Influence: 5.4] [Reference Citation Analysis]
5 Bright MG, Murphy K. Cleaning up the fMRI time series: Mitigating noise with advanced acquisition and correction strategies. NeuroImage 2017;154:1-3. [DOI: 10.1016/j.neuroimage.2017.03.056] [Cited by in Crossref: 9] [Cited by in F6Publishing: 8] [Article Influence: 1.8] [Reference Citation Analysis]
6 Belloy ME, Shah D, Abbas A, Kashyap A, Roßner S, Van der Linden A, Keilholz SD, Keliris GA, Verhoye M. Quasi-Periodic Patterns of Neural Activity improve Classification of Alzheimer's Disease in Mice. Sci Rep 2018;8:10024. [PMID: 29968786 DOI: 10.1038/s41598-018-28237-9] [Cited by in Crossref: 14] [Cited by in F6Publishing: 11] [Article Influence: 3.5] [Reference Citation Analysis]
7 Pan WJ, Billings J, Nezafati M, Abbas A, Keilholz S. Resting State fMRI in Rodents. Curr Protoc Neurosci 2018;83:e45. [PMID: 30040200 DOI: 10.1002/cpns.45] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.7] [Reference Citation Analysis]
8 Kucyi A, Tambini A, Sadaghiani S, Keilholz S, Cohen JR. Spontaneous cognitive processes and the behavioral validation of time-varying brain connectivity. Netw Neurosci 2018;2:397-417. [PMID: 30465033 DOI: 10.1162/netn_a_00037] [Cited by in Crossref: 46] [Cited by in F6Publishing: 36] [Article Influence: 11.5] [Reference Citation Analysis]
9 Keilholz S, Caballero-Gaudes C, Bandettini P, Deco G, Calhoun V. Time-Resolved Resting-State Functional Magnetic Resonance Imaging Analysis: Current Status, Challenges, and New Directions. Brain Connect 2017;7:465-81. [PMID: 28874061 DOI: 10.1089/brain.2017.0543] [Cited by in Crossref: 47] [Cited by in F6Publishing: 41] [Article Influence: 11.8] [Reference Citation Analysis]
10 Yabluchanskiy A, Nyul-Toth A, Csiszar A, Gulej R, Saunders D, Towner R, Turner M, Zhao Y, Abdelkari D, Rypma B, Tarantini S. Age-related alterations in the cerebrovasculature affect neurovascular coupling and BOLD fMRI responses: Insights from animal models of aging. Psychophysiology 2021;58:e13718. [PMID: 33141436 DOI: 10.1111/psyp.13718] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
11 Yang H, Zhang H, Meng C, Wohlschläger A, Brandl F, Di X, Wang S, Tian L, Biswal B. Frequency-specific coactivation patterns in resting-state and their alterations in schizophrenia: An fMRI study. Hum Brain Mapp 2022. [PMID: 35475569 DOI: 10.1002/hbm.25884] [Reference Citation Analysis]
12 Pais-Roldán P, Mateo C, Pan WJ, Acland B, Kleinfeld D, Snyder LH, Yu X, Keilholz S. Contribution of animal models toward understanding resting state functional connectivity. Neuroimage 2021;245:118630. [PMID: 34644593 DOI: 10.1016/j.neuroimage.2021.118630] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
13 O'Connor D, Lake EMR, Scheinost D, Constable RT. Resample aggregating improves the generalizability of connectome predictive modeling. Neuroimage 2021;236:118044. [PMID: 33848621 DOI: 10.1016/j.neuroimage.2021.118044] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
14 Waschkies CF, Pfiffner FK, Heuberger DM, Schneider MA, Tian Y, Wolint P, Calcagni M, Giovanoli P, Buschmann J. Tumor grafts grown on the chicken chorioallantoic membrane are distinctively characterized by MRI under functional gas challenge. Sci Rep 2020;10:7505. [PMID: 32371865 DOI: 10.1038/s41598-020-64290-z] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
15 Belloy ME, Naeyaert M, Abbas A, Shah D, Vanreusel V, van Audekerke J, Keilholz SD, Keliris GA, Van der Linden A, Verhoye M. Dynamic resting state fMRI analysis in mice reveals a set of Quasi-Periodic Patterns and illustrates their relationship with the global signal. Neuroimage 2018;180:463-84. [PMID: 29454935 DOI: 10.1016/j.neuroimage.2018.01.075] [Cited by in Crossref: 34] [Cited by in F6Publishing: 26] [Article Influence: 8.5] [Reference Citation Analysis]