The Chronnectome: Time-Varying Connectivity Networks as the Next Frontier in fMRI Data Discovery von Calhoun, Vince D., Miller, Robyn, Pearlson, Godfrey, Adalı, Tulay

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Classification and Prediction of Brain Disorders Using Functional Connectivity: Promising but Challenging von Du, Yuhui, Fu, Zening, Calhoun, Vince D

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Machine learning in major depression: From classification to treatment outcome prediction von Gao, Shuang, Calhoun, Vince D., Sui, Jing

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Dynamic connectivity states estimated from resting fMRI Identify differences among Schizophrenia, bipolar disorder, and healthy control subjects von Rashid, Barnaly, Damaraju, Eswar, Pearlson, Godfrey D, Calhoun, Vince D

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Resting state connectivity differences in eyes open versus eyes closed conditions von Agcaoglu, Oktay, Wilson, Tony W., Wang, Yu‐Ping, Stephen, Julia, Calhoun, Vince D.

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A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data von Calhoun, Vince D., Liu, Jingyu, Adalı, Tülay

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Classification of schizophrenia and bipolar patients using static and dynamic resting-state fMRI brain connectivity von Rashid, Barnaly, Arbabshirani, Mohammad R., Damaraju, Eswar, Cetin, Mustafa S., Miller, Robyn, Pearlson, Godfrey D., Calhoun, Vince D.

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Abnormal dynamic functional connectivity is linked to recovery after acute ischemic stroke von Bonkhoff, Anna K., Schirmer, Markus D., Bretzner, Martin, Etherton, Mark, Donahue, Kathleen, Tuozzo, Carissa, Nardin, Marco, Giese, Anne‐Katrin, Wu, Ona, D. Calhoun, Vince, Grefkes, Christian, Rost, Natalia S.

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A review of multivariate methods for multimodal fusion of brain imaging data von Sui, Jing, Adali, Tülay, Yu, Qingbao, Chen, Jiayu, Calhoun, Vince D.

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Dynamic functional connectivity: Promise, issues, and interpretations von Hutchison, R. Matthew, Womelsdorf, Thilo, Allen, Elena A., Bandettini, Peter A., Calhoun, Vince D., Corbetta, Maurizio, Della Penna, Stefania, Duyn, Jeff H., Glover, Gary H., Gonzalez-Castillo, Javier, Handwerker, Daniel A., Keilholz, Shella, Kiviniemi, Vesa, Leopold, David A., de Pasquale, Francesco, Sporns, Olaf, Walter, Martin, Chang, Catie

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Task-induced brain connectivity promotes the detection of individual differences in brain-behavior relationships von Jiang, Rongtao, Zuo, Nianming, Ford, Judith M., Qi, Shile, Zhi, Dongmei, Zhuo, Chuanjun, Xu, Yong, Fu, Zening, Bustillo, Juan, Turner, Jessica A., Calhoun, Vince D., Sui, Jing

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Interaction among subsystems within default mode network diminished in schizophrenia patients: A dynamic connectivity approach von Du, Yuhui, Pearlson, Godfrey D, Yu, Qingbao, He, Hao, Lin, Dongdong, Sui, Jing, Wu, Lei, Calhoun, Vince D

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Functional brain networks in schizophrenia: a review von Calhoun, Vince D, Eichele, Tom, Pearlson, Godfrey

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Gray matters: ViT-GAN framework for identifying schizophrenia biomarkers linking structural MRI and functional network connectivity von Bi, Yuda, Abrol, Anees, Jia, Sihan, Sui, Jing, Calhoun, Vince D.

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Dynamic state with covarying brain activity-connectivity: On the pathophysiology of schizophrenia von Fu, Zening, Iraji, Armin, Turner, Jessica A., Sui, Jing, Miller, Robyn, Pearlson, Godfrey D., Calhoun, Vince D.

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Estimating the number of independent components for functional magnetic resonance imaging data von Li, Yi-Ou, Adalı, Tülay, Calhoun, Vince D.

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NeuroMark: An automated and adaptive ICA based pipeline to identify reproducible fMRI markers of brain disorders von Du, Yuhui, Fu, Zening, Sui, Jing, Gao, Shuang, Xing, Ying, Lin, Dongdong, Salman, Mustafa, Abrol, Anees, Rahaman, Md Abdur, Chen, Jiayu, Hong, L. Elliot, Kochunov, Peter, Osuch, Elizabeth A., Calhoun, Vince D.

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Local-structure-preservation and redundancy-removal-based feature selection method and its application to the identification of biomarkers for schizophrenia von Xing, Ying, Pearlson, Godfrey D., Kochunov, Peter, Calhoun, Vince D., Du, Yuhui

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Editorial: Insights in brain imaging methods: 2023 von Giove, Federico, Zuo, Xi-Nian, Calhoun, Vince D

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Aging brain shows joint declines in brain within-network connectivity and between-network connectivity: a large-sample study ( N  > 6,000) von Du, Yuhui, Guo, Yating, Calhoun, Vince D

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