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Defining language networks from resting-state fMRI for surgical planning-a feasibility study
Tie, Yanmei, Rigolo, Laura, Norton, Isaiah H., Huang, Raymond Y., Wu, Wentao, Orringer, Daniel, Mukundan Jr, Srinivasan, Golby, Alexandra J.
Published in Human brain mapping (01.03.2014)
Published in Human brain mapping (01.03.2014)
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Connectopic mapping with resting-state fMRI
Haak, Koen V., Marquand, Andre F., Beckmann, Christian F.
Published in NeuroImage (Orlando, Fla.) (15.04.2018)
Published in NeuroImage (Orlando, Fla.) (15.04.2018)
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Machine learning in resting-state fMRI analysis
Khosla, Meenakshi, Jamison, Keith, Ngo, Gia H., Kuceyeski, Amy, Sabuncu, Mert R.
Published in Magnetic resonance imaging (01.12.2019)
Published in Magnetic resonance imaging (01.12.2019)
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Resting-state fMRI correlations: From link-wise unreliability to whole brain stability
Pannunzi, Mario, Hindriks, Rikkert, Bettinardi, Ruggero G., Wenger, Elisabeth, Lisofsky, Nina, Martensson, Johan, Butler, Oisin, Filevich, Elisa, Becker, Maxi, Lochstet, Martyna, Kühn, Simone, Deco, Gustavo
Published in NeuroImage (Orlando, Fla.) (15.08.2017)
Published in NeuroImage (Orlando, Fla.) (15.08.2017)
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Benchmarking functional connectome-based predictive models for resting-state fMRI
Dadi, Kamalaker, Rahim, Mehdi, Abraham, Alexandre, Chyzhyk, Darya, Milham, Michael, Thirion, Bertrand, Varoquaux, Gaël
Published in NeuroImage (Orlando, Fla.) (15.05.2019)
Published in NeuroImage (Orlando, Fla.) (15.05.2019)
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Dynamic effective connectivity in resting state fMRI
Park, Hae-Jeong, Friston, Karl J., Pae, Chongwon, Park, Bumhee, Razi, Adeel
Published in NeuroImage (Orlando, Fla.) (15.10.2018)
Published in NeuroImage (Orlando, Fla.) (15.10.2018)
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Identifying canonical and replicable multi‐scale intrinsic connectivity networks in 100k+ resting‐state fMRI datasets
Iraji, A., Fu, Z., Faghiri, A., Duda, M., Chen, J., Rachakonda, S., DeRamus, T., Kochunov, P., Adhikari, B. M., Belger, A., Ford, J. M., Mathalon, D. H., Pearlson, G. D., Potkin, S. G., Preda, A., Turner, J. A., van Erp, T. G. M., Bustillo, J. R., Yang, K., Ishizuka, K., Faria, A., Sawa, A., Hutchison, K., Osuch, E. A., Theberge, J., Abbott, C., Mueller, B. A., Zhi, D., Zhuo, C., Liu, S., Xu, Y., Salman, M., Liu, J., Du, Y., Sui, J., Adali, T., Calhoun, V. D.
Published in Human brain mapping (01.12.2023)
Published in Human brain mapping (01.12.2023)
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Alterations in amplitude of low frequency fluctuation in treatment-naïve major depressive disorder measured with resting-state fMRI
Liu, Jie, Ren, Ling, Womer, Fay Y., Wang, Jue, Fan, Guoguang, Jiang, Wenyan, Blumberg, Hilary P., Tang, Yanqing, Xu, Ke, Wang, Fei
Published in Human brain mapping (01.10.2014)
Published in Human brain mapping (01.10.2014)
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How to Interpret Resting-State fMRI: Ask Your Participants
Gonzalez-Castillo, Javier, Kam, Julia W.Y., Hoy, Colin W., Bandettini, Peter A.
Published in The Journal of neuroscience (10.02.2021)
Published in The Journal of neuroscience (10.02.2021)
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Identifying patients with Alzheimer’s disease using resting-state fMRI and graph theory
Khazaee, Ali, Ebrahimzadeh, Ata, Babajani-Feremi, Abbas
Published in Clinical neurophysiology (01.11.2015)
Published in Clinical neurophysiology (01.11.2015)
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3D-CNN based discrimination of schizophrenia using resting-state fMRI
Qureshi, Muhammad Naveed Iqbal, Oh, Jooyoung, Lee, Boreom
Published in Artificial intelligence in medicine (01.07.2019)
Published in Artificial intelligence in medicine (01.07.2019)
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Infraslow LFP correlates to resting-state fMRI BOLD signals
Pan, Wen-Ju, Thompson, Garth John, Magnuson, Matthew Evan, Jaeger, Dieter, Keilholz, Shella
Published in NeuroImage (Orlando, Fla.) (01.07.2013)
Published in NeuroImage (Orlando, Fla.) (01.07.2013)
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A Deep Learning Approach for Automated Diagnosis and Multi-Class Classification of Alzheimer’s Disease Stages Using Resting-State fMRI and Residual Neural Networks
Ramzan, Farheen, Khan, Muhammad Usman Ghani, Rehmat, Asim, Iqbal, Sajid, Saba, Tanzila, Rehman, Amjad, Mehmood, Zahid
Published in Journal of medical systems (01.02.2020)
Published in Journal of medical systems (01.02.2020)
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Can sliding-window correlations reveal dynamic functional connectivity in resting-state fMRI?
Hindriks, R., Adhikari, M.H., Murayama, Y., Ganzetti, M., Mantini, D., Logothetis, N.K., Deco, G.
Published in NeuroImage (Orlando, Fla.) (15.02.2016)
Published in NeuroImage (Orlando, Fla.) (15.02.2016)
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Resting State fMRI: Going Through the Motions
Maknojia, Sanam, Churchill, Nathan W., Schweizer, Tom A., Graham, S. J.
Published in Frontiers in neuroscience (13.08.2019)
Published in Frontiers in neuroscience (13.08.2019)
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Representation learning of resting state fMRI with variational autoencoder
Kim, Jung-Hoon, Zhang, Yizhen, Han, Kuan, Wen, Zheyu, Choi, Minkyu, Liu, Zhongming
Published in NeuroImage (Orlando, Fla.) (01.11.2021)
Published in NeuroImage (Orlando, Fla.) (01.11.2021)
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