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For: Kong R, Yang Q, Gordon E, Xue A, Yan X, Orban C, Zuo X, Spreng N, Ge T, Holmes A, Eickhoff S, Yeo BT. Individual-Specific Areal-Level Parcellations Improve Functional Connectivity Prediction of Behavior.. [DOI: 10.1101/2021.01.16.426943] [Cited by in Crossref: 8] [Cited by in F6Publishing: 9] [Article Influence: 4.0] [Reference Citation Analysis]
Number Citing Articles
1 Smith DD, Meca A, Bottenhorn KL, Bartley JE, Riedel MC, Salo T, Peraza JA, Laird RW, Pruden SM, Sutherland MT, Brewe E, Laird AR. Task-based attentional and default mode connectivity associated with STEM anxiety profiles among university physics students.. [DOI: 10.1101/2022.09.30.508557] [Reference Citation Analysis]
2 Udochi AL, Blain SD, Sassenberg TA, Burton PC, Medrano L, Deyoung CG. Activation of the default network during a theory of mind task predicts individual differences in agreeableness and social cognitive ability. Cogn Affect Behav Neurosci 2022;22:383-402. [DOI: 10.3758/s13415-021-00955-0] [Reference Citation Analysis]
3 Dhamala E, Rong Ooi LQ, Chen J, Kong R, Anderson KM, Chin R, Yeo BT, Holmes AJ. Proportional intracranial volume correction differentially biases behavioral predictions across neuroanatomical features and populations.. [DOI: 10.1101/2022.03.15.483970] [Reference Citation Analysis]
4 Hermosillo RJ, Moore LA, Fezcko E, Dworetsky A, Pines A, Conan G, Mooney MA, Randolph A, Adeyemo B, Earl E, Perrone A, Carrasco CM, Uriarte-lopez J, Snider K, Doyle O, Cordova M, Nagel BJ, Feldstein Ewing SW, Satterthwaite T, Dosenbach N, Gratton C, Petersen S, Miranda-domínguez Ó, Fair DA. A Precision Functional Atlas of Network Probabilities and Individual-Specific Network Topography.. [DOI: 10.1101/2022.01.12.475422] [Reference Citation Analysis]
5 Setton R, Mwilambwe-tshilobo L, Girn M, Lockrow AW, Baracchini G, Hughes C, Lowe AJ, Cassidy BN, Li J, Luh W, Bzdok D, Leahy RM, Ge T, Margulies DS, Misic B, Bernhardt BC, Stevens WD, De Brigard F, Kundu P, Turner GR, Spreng RN. Age differences in the functional architecture of the human brain.. [DOI: 10.1101/2021.03.31.437922] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
6 Lohmann G, Lacosse E, Ethofer T, Kumar VJ, Scheffler K, Jost J. Predicting intelligence from fMRI data of the human brain in a few minutes of scan time.. [DOI: 10.1101/2021.03.18.435935] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
7 Dahan S, Williams LZJ, Rueckert D, Robinson EC. Improving Phenotype Prediction Using Long-Range Spatio-Temporal Dynamics of Functional Connectivity. Lecture Notes in Computer Science 2021. [DOI: 10.1007/978-3-030-87586-2_15] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
8 Feilong M, Guntupalli JS, Haxby JV. The neural basis of intelligence in fine-grained cortical topographies.. [DOI: 10.1101/2020.06.06.138099] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.3] [Reference Citation Analysis]