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Vince D. Calhoun

Vincent D. Calhoun

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affiliation: University of New Mexico, Albuquerque, USA

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2025
[j335]
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Hanlu Yang, Trung Vu, Ehsan Ahmed Dhrubo, Vince D. Calhoun, Tülay Adali:
A Flexible Constrained ICA Approach for Multisubject fMRI Analysis. Int. J. Biomed. Imaging 2025(1) (2025)
[j334]
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Bishal Thapaliya, Esra Akbas, Jiayu Chen, Ram Sapkota, Bhaskar Ray, Pranav Suresh, Vince D. Calhoun, Jingyu Liu:
Brain networks and intelligence: A graph neural network based approach to resting state fMRI data. Medical Image Anal. 101: 103433 (2025)
[j333]
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Bishal Thapaliya, Robyn L. Miller, Jiayu Chen, Yu-Ping Wang, Esra Akbas, Ram Sapkota, Bhaskar Ray, Pranav Suresh, Santosh Ghimire, Vince D. Calhoun, Jingyu Liu:
DSAM: A deep learning framework for analyzing temporal and spatial dynamics in brain networks. Medical Image Anal. 101: 103462 (2025)
[j332]
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Marlena Duda, Ashkan Faghiri, Aysenil Belger, Juan R. Bustillo, Judith M. Ford, Daniel H. Mathalon, Bryon A. Mueller, Godfrey D. Pearlson, Steven G. Potkin, Adrian Preda, Jing Sui, Theo G. M. van Erp, Vince D. Calhoun:
Alterations in Gray Matter Structure Linked to Frequency-Specific Cortico-Subcortical Connectivity in Schizophrenia via Multimodal Data Fusion. Neuroinformatics 23(2): 31 (2025)
[j331]
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Lan Yang, Chen Qiao, Takafumi Kanamori, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang:
Tensor dictionary-based heterogeneous transfer learning to study emotion-related gender differences in brain. Neural Networks 183: 106974 (2025)
[j330]
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Bin Gao, Aiju Yu, Chen Qiao, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang:
An Explainable Unified Framework of Spatio-Temporal Coupling Learning With Application to Dynamic Brain Functional Connectivity Analysis. IEEE Trans. Medical Imaging 44(2): 941-951 (2025)
[j329]
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Ben Gabrielson, Hanlu Yang, Trung Vu, Vince D. Calhoun, Tülay Adali:
Large-Scale Independent Vector Analysis (IVA-G) via Coresets. IEEE Trans. Signal Process. 73: 230-244 (2025)
[c397]
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Ashfia Binte Habib, Ben Gabrielson, Hanlu Yang, Vince D. Calhoun, Tülay Adali:
Grassmannian Kernels for Efficient and Effective Detection of Group Differences in fMRI Data. CISS 2025: 1-6
[c396]
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Chunying Jia, Weixin Wang, Trung Vu, Hanlu Yang, Ben Gabrielson, Vince D. Calhoun, Tülay Adali:
Adaptive Constrained ICA with Mixing Matrix Column Constraints: Application to fMRI Data. CISS 2025: 1-6
[c395]
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Emin Erdem Kumbasar, Hanlu Yang, Trung Vu, Vince D. Calhoun, Tülay Adali:
Fusion of Multitask fMRI Data with Constrained Independent Vector Analysis. CISS 2025: 1-6
[c394]
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Yuxiang Wei, Anees Abrol, Vince D. Calhoun:
Hierarchical Spatio-Temporal State-Space Modeling for fMRI Analysis. RECOMB 2025: 86-98
[i69]
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  - journals/corr/abs-2501-16345
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Bishal Thapaliya, Esra Akbas, Ram Sapkota, Bhaskar Ray, Vince D. Calhoun, Jingyu Liu:
Self-Clustering Graph Transformer Approach to Model Resting-State Functional Brain Activity. CoRR abs/2501.16345 (2025)
[i68]
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  - journals/corr/abs-2501-17207
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Keqi Han, Yao Su, Lifang He, Liang Zhan, Sergey M. Plis, Vince D. Calhoun, Carl Yang:
Rethinking Functional Brain Connectome Analysis: Do Graph Deep Learning Models Help? CoRR abs/2501.17207 (2025)
[i67]
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  - journals/corr/abs-2501-18859
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Faming Xu, Yiding Wang, Chen Qiao, Gang Qu, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang:
A Deep Spatio-Temporal Architecture for Dynamic Effective Connectivity Network Analysis Based on Dynamic Causal Discovery. CoRR abs/2501.18859 (2025)
[i66]
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  - journals/corr/abs-2502-01885
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Yipu Zhang, Likai Wang, Kuan-Jui Su, Aiying Zhang, Hao Zhu, Xiaowen Liu, Hui Shen, Vince D. Calhoun, Yuping Wang, Hong-Wen Deng:
A Privacy-Preserving Domain Adversarial Federated learning for multi-site brain functional connectivity analysis. CoRR abs/2502.01885 (2025)
2024
[j328]
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  - journals/access/LehmannHGACA24
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Isabell Lehmann, Tanuj Hasija, Ben Gabrielson, Mohammad A. B. S. Akhonda, Vince D. Calhoun, Tülay Adali:
Identifying the Relationship Structure Among Multiple Datasets Using Independent Vector Analysis: Application to Multi-Task fMRI Data. IEEE Access 12: 109443-109456 (2024)
[j327]
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Ben Gabrielson, Hanlu Yang, Trung Vu, Vince D. Calhoun, Tülay Adali:
Mode Coresets for Efficient, Interpretable Tensor Decompositions: An Application to Feature Selection in fMRI Analysis. IEEE Access 12: 192356-192376 (2024)
[j326]
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  - journals/brain/SahaSRFLC24
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Rekha Saha, Debbrata K. Saha, Md Abdur Rahaman, Zening Fu, Jingyu Liu, Vince D. Calhoun:
A Method to Estimate Longitudinal Change Patterns in Functional Network Connectivity of the Developing Brain Relevant to Psychiatric Problems, Cognition, and Age. Brain Connect. 14(2): 130-140 (2024)
[j325]
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  - journals/brain/LaureysRFWWCDB24
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Steven Laureys, Marc Raichle, Karl J. Friston, Susan L. Whitfield-Gabrieli, Jennifer L. Whitwell, Vince D. Calhoun, Linda Douw, Mélanie Boly:
A Roundtable Discussion on Brain Connectivity. Brain Connect. 14(5): 263-273 (2024)
[j324]
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  - journals/bspc/HanLKZGCWC24
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Yue Han, Qiu-Hua Lin, Li-Dan Kuang, Bin-Hua Zhao, Xiao-Feng Gong, Fengyu Cong, Yu-Ping Wang, Vince D. Calhoun:
A core tensor sparsity enhancement method for solving Tucker-2 model of multi-subject fMRI data. Biomed. Signal Process. Control. 95: 106471 (2024)
[j323]
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  - journals/entropy/BlairMC24
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David Sutherland Blair, Robyn L. Miller, Vince D. Calhoun:
A Dynamic Entropy Approach Reveals Reduced Functional Network Connectivity Trajectory Complexity in Schizophrenia. Entropy 26(7): 545 (2024)
[j322]
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  - journals/fini/ThapaliyaOG0CP24
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Bishal Thapaliya, Riyasat Ohib, Eloy Geenjaar, Jingyu Liu, Vince D. Calhoun, Sergey M. Plis:
Efficient federated learning for distributed neuroimaging data. Frontiers Neuroinformatics 18 (2024)
[j321]
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  - journals/ijns/JiangPCLLWGWLDCYL24
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Sisi Jiang, Haonan Pei, Junxia Chen, Hechun Li, Zetao Liu, Yuehan Wang, Jinnan Gong, Sheng Wang, Qifu Li, Mingjun Duan, Vince D. Calhoun, Dezhong Yao, Cheng Luo:
Striatum- and Cerebellum-Modulated Epileptic Networks Varying Across States with and without Interictal Epileptic Discharges. Int. J. Neural Syst. 34(4): 2450017:1-2450017:15 (2024)
[j320]
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Wei Wang, Li Xiao, Gang Qu, Vince D. Calhoun, Yu-Ping Wang, Xiaoyan Sun:
Multiview hyperedge-aware hypergraph embedding learning for multisite, multiatlas fMRI based functional connectivity network analysis. Medical Image Anal. 94: 103144 (2024)
[j319]
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  - journals/neuroimage/FedorovGWSDLMMHPC24
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Alex Fedorov, Eloy Geenjaar, Lei Wu, Tristan Sylvain, Thomas P. DeRamus, Margaux Luck, Maria B. Misiura, Girish Mittapalle, R. Devon Hjelm, Sergey M. Plis, Vince D. Calhoun:
Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links. NeuroImage 285: 120485 (2024)
[j318]
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  - journals/neuroimage/FuBWAASDISSC24
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Zening Fu, Ishaan Batta, Lei Wu, Anees Abrol, Oktay Agcaoglu, Mustafa S. Salman, Yuhui Du, Armin Iraji, Sarah Shultz, Jing Sui, Vince D. Calhoun:
Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities. NeuroImage 292: 120617 (2024)
[j317]
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  - journals/neuroimage/BiAJSC24
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Yuda Bi, Anees Abrol, Sihan Jia, Jing Sui, Vince D. Calhoun:
Gray matters: ViT-GAN framework for identifying schizophrenia biomarkers linking structural MRI and functional network connectivity. NeuroImage 297: 120674 (2024)
[j316]
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  - journals/neuroimage/ChenQRQCSWW24
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Longyun Chen, Chen Qiao, Kai Ren, Gang Qu, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang:
Explainable spatio-temporal graph evolution learning with applications to dynamic brain network analysis during development. NeuroImage 298: 120771 (2024)
[j315]
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  - journals/neuroimage/DerosaFCB24
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Jacob Derosa, Naomi P. Friedman, Vince D. Calhoun, Marie T. Banich:
Neurodevelopmental subtypes of functional brain organization in the ABCD study using a rigorous analytic framework. NeuroImage 299: 120827 (2024)
[j314]
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  - journals/neuroimage/XingPKCD24
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Ying Xing, Godfrey D. Pearlson, Peter V. Kochunov, Vince D. Calhoun, Yuhui Du:
Local-structure-preservation and redundancy-removal-based feature selection method and its application to the identification of biomarkers for schizophrenia. NeuroImage 299: 120839 (2024)
[j313]
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  - journals/neuroimage/PopovMFYCP24
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Pavel Popov, Usman Mahmood, Zening Fu, Carl Yang, Vince D. Calhoun, Sergey M. Plis:
A simple but tough-to-beat baseline for fMRI time-series classification. NeuroImage 303: 120909 (2024)
[j312]
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  - journals/ni/BasodiRGRPMNC24
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Sunitha Basodi, Rajikha Raja, Harshvardhan Gazula, Javier Tomas Romero, Sandeep R. Panta, Thomas Maullin-Sapey, Thomas E. Nichols, Vince D. Calhoun:
Decentralized Mixed Effects Modeling in COINSTAC. Neuroinformatics 22(2): 163-175 (2024)
[j311]
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  - journals/patterns/RootesMurdyPKRQCLCCJGHK24
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Kelly Rootes-Murdy, Sandeep R. Panta, Ross Kelly, Javier Tomas Romero, Yann Quidé, Murray J. Cairns, C. M. Loughland, Vaughan J. Carr, Stanley V. Catts, Assen Jablensky, Melissa J. Green, Frans Henskens, Dylan Kiltschewskij, Patricia T. Michie, Bryan J. Mowry, Christos Pantelis, Paul E. Rasser, William R. Reay, Ulrich Schall, Rodney J. Scott, Oliver J. Watkeys, Gloria M. P. Roberts, Philip B. Mitchell, Janice M. Fullerton, Bronwyn J. Overs, Masataka Kikuchi, Ryota Hashimoto, Junya Matsumoto, Masaki Fukunaga, Perminder S. Sachdev, Henry Brodaty, Wei Wen, Jiyang Jiang, Negar Fani, Timothy D. Ely, Adriana Lorio, Jennifer S. Stevens, Kerry J. Ressler, Tanja Jovanovic, Sanne J. H. van Rooij, Lydia M. Federmann, Christiane Jockwitz, Alexander Teumer, Andreas J. Forstner, Svenja Caspers, Sven Cichon, Sergey M. Plis, Anand D. Sarwate, Vince D. Calhoun:
Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC. Patterns 5(7): 100987 (2024)
[j310]
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  - journals/ploscb/ChungHCCG24
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Moo K. Chung, Shih-Gu Huang, Ian C. Carroll, Vince D. Calhoun, H. Hill Goldsmith:
Topological state-space estimation of functional human brain networks. PLoS Comput. Biol. 20(5): 1011869 (2024)
[j309]
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  - journals/sensors/KollaFAFC24
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Sahithi Kolla, Haleh Falakshahi, Anees Abrol, Zening Fu, Vince D. Calhoun:
Intra-Atlas Node Size Effects on Graph Metrics in fMRI Data: Implications for Alzheimer's Disease and Cognitive Impairment. Sensors 24(3): 814 (2024)
[j308]
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Weizheng Yan, Zening Fu, Rongtao Jiang, Jing Sui, Vince D. Calhoun:
Maximum Classifier Discrepancy Generative Adversarial Network for Jointly Harmonizing Scanner Effects and Improving Reproducibility of Downstream Tasks. IEEE Trans. Biomed. Eng. 71(4): 1170-1178 (2024)
[j307]
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Irina Belyaeva, Ben Gabrielson, Yu-Ping Wang, Tony W. Wilson, Vince D. Calhoun, Julia M. Stephen, Tülay Adali:
Learning Spatiotemporal Brain Dynamics in Adolescents via Multimodal MEG and fMRI Data Fusion Using Joint Tensor/Matrix Decomposition. IEEE Trans. Biomed. Eng. 71(7): 2189-2200 (2024)
[j306]
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  - journals/tbe/KotoskiLMC24
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Aline Kotoski, Jingyu Liu, Robin Morris, Vince D. Calhoun:
Inter-Modality Source Coupling: A Fully-Automated Whole-Brain Data-Driven Structure-Function Fingerprint Shows Replicable Links to Reading in a Large-Scale (N∼8K) Analysis. IEEE Trans. Biomed. Eng. 71(12): 3383-3389 (2024)
[j305]
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Yingying Wang, Chen Qiao, Gang Qu, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang:
A Deep Dynamic Causal Learning Model to Study Changes in Dynamic Effective Connectivity During Brain Development. IEEE Trans. Biomed. Eng. 71(12): 3390-3401 (2024)
[j304]
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Trung Vu, Francisco Laport, Hanlu Yang, Vince D. Calhoun, Tülay Adali:
Constrained Independent Vector Analysis With Reference for Multi-Subject fMRI Analysis. IEEE Trans. Biomed. Eng. 71(12): 3531-3542 (2024)
[j303]
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Gang Qu, Anton Orlichenko, Junqi Wang, Gemeng Zhang, Li Xiao, Kun Zhang, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang:
Interpretable Cognitive Ability Prediction: A Comprehensive Gated Graph Transformer Framework for Analyzing Functional Brain Networks. IEEE Trans. Medical Imaging 43(4): 1568-1578 (2024)
[c393]
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  - conf/acssc/XuJKAC24
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Shuai Xu, Rui Jin, Seung-Jun Kim, Tülay Adali, Vince D. Calhoun:
Improved Dictionary Learning for FMRI Data Analysis Capturing Common and Individual Activation Maps. IEEECONF 2024: 549-553
[c392]
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  - conf/bhi/AjithC24
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Meenu Ajith, Vince D. Calhoun:
Denoising Diffusion Probabilistic Models for High-Fidelity fMRI Intrinsic Connectivity Network Data Generation. BHI 2024: 1-4
[c391]
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Ishaan Batta, Anees Abrol, Vince D. Calhoun:
Constrained Source-based Salience: Network-based Visualization of Deep Learning Neuroimaging Models. BHI 2024: 1-8
[c390]
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Fangling Sun, Chuang Liang, Tülay Adali, Daoqiang Zhang, Rongtao Jiang, Vince D. Calhoun, Shile Qi:
GPR-SCSANet: Unequal-Length Time Series Normalization with Split-Channel Residual Convolution and Self-Attention for Brain Age Prediction. BIBM 2024: 5097-5103
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Ye Tao, Anand D. Sarwate, Sandeep R. Panta, Sergey M. Plis, Vince D. Calhoun:
Federated Privacy-Preserving Visualization: A Vision Paper. IEEE Big Data 2024: 8035-8041
[c388]
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Sunitha Basodi, Javier Tomas Romero, Sandeep R. Panta, Dylan Martin, Sergey M. Plis, Anand D. Sarwate, Vince D. Calhoun:
Advanced machine learning in neuroimaging studies via federated learning. IEEE Big Data 2024: 8623-8624
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Ishaan Batta, Anees Abrol, Vince D. Calhoun:
A Novel Deep Subspace Learning Framework to Automatically Uncover Assessment-Specific Independent Brain Networks. CISS 2024: 1-6
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  - conf/cvpr/RahamanFIC22
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Md Abdur Rahaman, Zening Fu, Armin Iraji, Vince D. Calhoun:
A Deep Biclustering Framework for Brain Network Analysis. CVPR Workshops 2024: 5075-5085
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Yuxiang Wei, Anees Abrol, James J. Lah, Deqiang Qiu, Vince D. Calhoun:
A deep spatio-temporal attention model of dynamic functional network connectivity shows sensitivity to Alzheimer's in asymptomatic individuals. EMBC 2024: 1-4
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Oktay Agcaoglu, Deniz Alaçam, Tülay Adali, Vince D. Calhoun, Rogers F. Silva, Sergey M. Plis, Biozid Bostami:
Copula linked parallel ICA jointly estimates linked structural and functional MRI brain networks. EMBC 2024: 1-4
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Prerana Bajracharya, Ashkan Faghiri, Zening Fu, Vince D. Calhoun, Sarah Shultz, Armin Iraji:
Identifying Canonical multi-scale Intrinsic Connectivity Networks in Infant resting-state fMRI and their Association with Age. EMBC 2024: 1-4
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Neda Behzadfar, Armin Iraji, Vince D. Calhoun:
Multiband Group Independent Component Analysis: Unveiling Frequency-Dependent Dynamics of Functional Connectivity in Group-Level fMRI Analyses. EMBC 2024: 1-5
[c381]
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Biozid Bostami, Noah Lewis, Victor M. Vergara, Vince D. Calhoun:
Dynamic Functional Network Connectivity Clustering and Harmonization Evaluation Metric. EMBC 2024: 1-4
[c380]
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Xiangxiang Cui, Dongmei Zhi, Weizheng Yan, Vince D. Calhoun, Chuanjun Zhuo, Jing Sui:
CGDM-GAN: An Adversarial Network Approach with Self-supervised Learning for Site Effect Removal. EMBC 2024: 1-4
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Marlena Duda, Vince D. Calhoun:
Functionally-Adaptive Gray and White Matter Structural Basis Sets via Dynamic Fusion of Multimodal MRI Data. EMBC 2024: 1-4
[c378]
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Cyrus Eierud, Zening Fu, Helen Petropoulos, Anastasia Bohsali, Armin Iraji, Melanie Ganz, Cyril R. Pernet, Vince D. Calhoun:
NeuroMark PET: Replicable positron emission tomography ICA templates for florbetapir and florbetaben radioligands. EMBC 2024: 1-4
[c377]
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Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun:
Evaluating Augmentation Approaches for Deep Learning-based Major Depressive Disorder Diagnosis with Raw Electroencephalogram Data. EMBC 2024: 1-5
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M. Moein Esfahani, Robyn L. Miller, Vince D. Calhoun:
Exploring Schizophrenia Classification in fMRI Data: A Common Spatial Patterns(CSP) Approach for Enhanced Feature Extraction and Classification. EMBC 2024: 1-4
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Haleh Falakshahi, Hooman Rokham, Vince D. Calhoun:
Path-based Differential Analysis in Near-centenarians and Centenarians Brain Network. EMBC 2024: 1-4
[c374]
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Britny Farahdel, Bishal Thapaliya, Pranav Suresh, Bhaskar Ray, Vince D. Calhoun, Jingyu Liu:
Brain community detection in the general children population. EMBC 2024: 1-6
[c373]
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Reihaneh Hassanzadeh, Anees Abrol, Hamid Reza Hassanzadeh, Vince D. Calhoun:
Cross-Modality Translation with Generative Adversarial Networks to Unveil Alzheimer's Disease Biomarkers. EMBC 2024: 1-4
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Behnam Kazemivash, Pranav Suresh, Jingyu Liu, Dong Hye Ye, Vince D. Calhoun:
Scepter: Weakly Supervised Framework for Spatiotemporal Dense Prediction of 4D Dynamic Brain Networks. EMBC 2024: 1-4
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K. M. Ibrahim Khalilullah, Oktay Agcaoglu, Marlena Duda, Vince D. Calhoun:
Parallel Multilink Joint ICA for Multimodal Fusion of Gray Matter and Multiple Resting fMRI Networks. EMBC 2024: 1-4
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Nigar Khasayeva, Cyrus Eierud, Kyle M. Jensen, Enrico Premi, Barbara Borroni, Vince D. Calhoun, Armin Iraji:
Revealing Alzheimer's Disease Dementia Patterns in [18F]Florbetapir PET with Independent Component Analysis. EMBC 2024: 1-4
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Aline Kotoski, Robin Morris, Vince D. Calhoun:
Inter-modality source coupling: a fully automated whole-brain data-driven structure-function fingerprint shows replicable links to reading in large-scale (N~8K) analysis. EMBC 2024: 1-4
[c368]
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Samujjwal Kumar, Spencer Kinsey, Kyle M. Jensen, Prerana Bajracharya, Vince D. Calhoun, Armin Iraji:
Beyond Artifacts: Rethinking Motion-Related Signals in Resting-State fMRI Analysis. EMBC 2024: 1-4
[c367]
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Krishna Pusuluri, Armin Iraji, Vince D. Calhoun:
Joint density distributions of dynamic spatial brain networks show systematic variations at rest. EMBC 2024: 1-4
[c366]
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  - conf/embc/RahamanFIC24
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Md Abdur Rahaman, Zening Fu, Armin Iraji, Vince D. Calhoun:
SpaDE: Semantic Locality Preserving Biclustering for Neuroimaging Data. EMBC 2024: 1-5
[c365]
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Hooman Rokham, Haleh Falakshahi, Vince D. Calhoun:
Label Noise-Robust Ensemble Deep Multimodal Framework For Neuroimaging Data. EMBC 2024: 1-4
[c364]
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  - conf/embc/SanchoEMC24
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Martina Lapera Sancho, Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun:
Identifying Reproducibly Important EEG Markers of Schizophrenia with an Explainable Multi-Model Deep Learning Approach. EMBC 2024: 1-4
[c363]
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Masoud Seraji, Charles A. Ellis, Mohammad S. Eslampanah Sendi, Robyn L. Miller, Vince D. Calhoun:
Uncovering Effects of Schizophrenia upon a Maximally Significant, Minimally Complex Subset of Default Mode Network Connectivity Features. EMBC 2024: 1-4
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Najme Soleimani, Vince D. Calhoun:
Neural Complexity Unveiled: Doubly Functionally Independent Primitives (dFIPs) in Psychiatric Risk Score Assessment. EMBC 2024: 1-4
[c361]
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Bishal Thapaliya, Zundong Wu, Ram Sapkota, Bhaskar Ray, Pranav Suresh, Santosh Ghimire, Vince D. Calhoun, Jingyu Liu:
Graph-based deep learning models in the prediction of early-stage Alzheimers. EMBC 2024: 1-5
[c360]
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Duc My Vo, Sergey M. Plis, Vince D. Calhoun:
Classification of Schizophrenia using Intrinsic Connectivity Networks and Incremental Boosting Convolution Neural Networks. EMBC 2024: 1-4
[c359]
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Min Zhao, Rongtao Xu, Dongmei Zhi, Shan Yu, Vince D. Calhoun, Jing Sui:
A Cross-Feature Mutual Learning Framework to Integrate Functional Connectivity and Activity for Brain Disorder Classification. EMBC 2024: 1-4
[c358]
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Francisco Laport, Adriana Dapena, Trung Vu, Hanlu Yang, Vince D. Calhoun, Tülay Adali:
Reproducibility and Replicability in Neuroimaging: Constrained IVA as an Effective Assessment Tool. EUSIPCO 2024: 802-806
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Chunying Jia, Mohammad Abu Baker Siddique Akhonda, Hanlu Yang, Vince D. Calhoun, Tülay Adali:
Fusion of Novel FMRI Features Using Independent Vector Analysis for a Multifaceted Characterization of Schizophrenia. EUSIPCO 2024: 1112-1116
[c356]
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Irina Belyaeva, Yu-Ping Wang, Tony W. Wilson, Vince D. Calhoun, Julia M. Stephen, Tülay Adali:
Assessing Pediatric Cognitive Development via Multisensory Brain Imaging Analysis. EUSIPCO 2024: 1362-1366
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Yuda Bi, Anees Abrol, Jing Sui, Vince D. Calhoun:
Cross-Modal Synthesis of Structural MRI and Functional Connectivity Networks via Conditional ViT-GANs. ICASSP 2024: 1756-1760
[c354]
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Trung Vu, Hanlu Yang, Francisco Laport, Ben Gabrielson, Vince D. Calhoun, Tülay Adali:
A Robust and Scalable Method with an Analytic Solution for Multi-Subject FMRI Data Analysis. ICASSP 2024: 1831-1835
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  - conf/icassp/SapkotaTSRC024
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Ram Sapkota, Bishal Thapaliya, Pranav Suresh, Bhaskar Ray, Vince D. Calhoun, Jingyu Liu:
Multimodal Imaging Feature Extraction with Reference Canonical Correlation Analysis Underlying Intelligence. ICASSP 2024: 2071-2075
[c352]
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  - conf/icassp/YangOVLCAA24
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Hanlu Yang, Meiby Ortiz-Bouza, Trung Vu, Francisco Laport, Vince D. Calhoun, Selin Aviyente, Tülay Adali:
Subgroup Identification Through Multiplex Community Structure Within Functional Connectivity Networks. ICASSP 2024: 2141-2145
[c351]
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Ashkan Faghiri, Armin Iraji, Tülay Adali, Vince D. Calhoun:
Analysis of High-Order Brain Networks Resolved in Time and Frequency Using CP Decomposition. ICASSP 2024: 13346-13350
[c350]
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  - conf/isbi/BakerSFIOBC24
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Bradley T. Baker, Mustafa S. Salman, Zening Fu, Armin Iraji, Elizabeth A. Osuch, Henry Jeremy Bockholt, Vince D. Calhoun:
Multiscale Neuroimaging Features for the Identification of Medication Class and Non-Responders in Mood Disorder Treatment. ISBI 2024: 1-5
[c349]
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Giorgio Dolci, Federica Cruciani, Lorenza Brusini, Lorenzo Pini, Ilaria Boscolo Galazzo, Vince D. Calhoun, Gloria Menegaz:
Diffusion MRI Allows Capturing the Amyloid-β and τ Proteins Status in Alzheimer's Disease Continuum. ISBI 2024: 1-5
[c348]
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Marlena Duda, Oktay Agcaoglu, Vince D. Calhoun:
Dynamic Fusion of Multimodal MRI Data Captures Flexible, Time-Sensitive Structure-Function Linkages in the Brain. ISBI 2024: 1-4
[c347]
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Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun:
Cross-Sampling Rate Transfer Learning for Enhanced Raw EEG Deep Learning Classifier Performance in Major Depressive Disorder Diagnosis. ISBI 2024: 1-5
[c346]
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  - conf/isbi/ItkyalALC24
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Vaibhavi S. Itkyal, Anees Abrol, Theodore J. LaGrow, Vince D. Calhoun:
Voxelwise Intensity Projection for the Spatial Representation of Resting State Functional MRI Networks and Multimodal Deep Learning. ISBI 2024: 1-4
[c345]
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Souvik Phadikar, Krishna Pusuluri, Kyle M. Jensen, Lei Wu, Armin Iraji, Vince D. Calhoun:
Coupling between Time-Varying EEG Spectral Bands and Spatial Dynamic FMRI Networks. ISBI 2024: 1-4
[c344]
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  - conf/isbi/RayCFSTFCL24
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Bhaskar Ray, Jiayu Chen, Zening Fu, Pranav Suresh, Bishal Thapaliya, Britny Farahdel, Vince D. Calhoun, Jingyu Liu:
Replication and Refinement of Brain Age Model for Adolescent Development. ISBI 2024: 1-5
[c343]
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  - conf/isbi/ShaikCCY24
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Nagur Shareef Shaik, Teja Krishna Cherukuri, Vince D. Calhoun, Dong Hye Ye:
Spatial Sequence Attention Network for Schizophrenia Classification from Structural Brain MR Images. ISBI 2024: 1-5
[c342]
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Najme Soleimani, Godfrey D. Pearlson, Armin Iraji, Vince D. Calhoun:
Double Functionally Independent Primitives Provide Disorder Specific Fingerprints of Mental Illnesses. ISBI 2024: 1-4
[c341]
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  - conf/isbi/TaoSPPC24
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Ye Tao, Anand D. Sarwate, Sandeep R. Panta, Sergey M. Plis, Vince D. Calhoun:
Privacy-Preserving Visualization of Brain Functional Network Connectivity. ISBI 2024: 1-5
[c340]
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  - conf/isbi/WiafeFFMC24
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Sir-Lord Wiafe, Ashkan Faghiri, Zening Fu, Robyn L. Miller, Vince D. Calhoun:
Capturing Stretching and Shrinking of Inter-Network Temporal Coupling in FMRI Via WARP Elasticity. ISBI 2024: 1-4
[c339]
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  - conf/metroxraine/DolciMCBPCGM24
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Giorgio Dolci, Cristian Morasso, Federica Cruciani, Lorenza Brusini, Lorenzo Pini, Vince D. Calhoun, Ilaria Boscolo Galazzo, Gloria Menegaz:
Integrated Gradients Demystified: An MRI Case Study on Aβ-T Protein Localization. MetroXRAINE 2024: 1177-1182
[c338]
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Badhan Mazumder, Ayush Kanyal, Lei Wu, Vince D. Calhoun, Dong Hye Ye:
Physics-Guided Multi-view Graph Neural Network for Schizophrenia Classification via Structural-Functional Coupling. PRIME@MICCAI 2024: 61-73
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Qiang Li, Masoud Seraji, Vince D. Calhoun, Armin Iraji:
Complexity Measures of Psychotic Brain Activity In The FMRI Signal. SSIAI 2024: 9-12
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Robyn L. Miller, Victor M. Vergara, Vince D. Calhoun:
Markov Spatial Flows in Bold FMRI: A Novel Lens on the Bold Signal Applied To an Imaging Study of Schizophrenia. SSIAI 2024: 13-16
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Natalia Maksymchuk, Robyn L. Miller, Vince D. Calhoun:
Distribution of Connectivity Strengths Across Functional Regions has Higher Entropy in Schizophrenia Patients than in Controls. SSIAI 2024: 37-40
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Yutong Gao, Charles A. Ellis, Vince D. Calhoun, Robyn L. Miller:
Improving Age Prediction: Utilizing LSTM-Based Dynamic Forecasting For Data Augmentation in Multivariate Time Series Analysis. SSIAI 2024: 125-128
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Charles A. Ellis, Martina Lapera Sancho, Robyn L. Miller, Vince D. Calhoun:
Identifying EEG Biomarkers of Depression with Novel Explainable Deep Learning Architectures. xAI (4) 2024: 102-124
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Vince D. Calhoun, Sergey M. Plis, Jessica A. Turner, Anand D. Sarwate:
COINSTAC: Decentralizing the future of brain imaging analysis. Zenodo, 2024
[i65]
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Bradley T. Baker, Barak A. Pearlmutter, Robyn L. Miller, Vince D. Calhoun, Sergey M. Plis:
Low-Rank Learning by Design: the Role of Network Architecture and Activation Linearity in Gradient Rank Collapse. CoRR abs/2402.06751 (2024)
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Bradley T. Baker, Mustafa S. Salman, Zening Fu, Armin Iraji, Elizabeth A. Osuch, Henry Jeremy Bockholt, Vince D. Calhoun:
Multiscale Neuroimaging Features for the Identification of Medication Class and Non-Responders in Mood Disorder Treatment. CoRR abs/2402.07858 (2024)
[i63]
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  - journals/corr/abs-2404-00144
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Ziyu Zhou, Anton Orlichenko, Gang Qu, Zening Fu, Vince D. Calhoun, Zhengming Ding, Yu-Ping Wang:
An Interpretable Cross-Attentive Multi-modal MRI Fusion Framework for Schizophrenia Diagnosis. CoRR abs/2404.00144 (2024)
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  - journals/corr/abs-2405-00721
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M. Moein Esfahani, Hossein Sadati, Vince D. Calhoun:
Optimizing Brain-Computer Interface Performance: Advancing EEG Signals Channel Selection through Regularized CSP and SPEA II Multi-Objective Optimization. CoRR abs/2405.00721 (2024)
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Reihaneh Hassanzadeh, Anees Abrol, Hamid Reza Hassanzadeh, Vince D. Calhoun:
Cross-Modality Translation with Generative Adversarial Networks to Unveil Alzheimer's Disease Biomarkers. CoRR abs/2405.05462 (2024)
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  - journals/corr/abs-2405-07977
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Anton Orlichenko, Gang Qu, Ziyu Zhou, Anqi Liu, Hong-Wen Deng, Zhengming Ding, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds. CoRR abs/2405.07977 (2024)
[i59]
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Riyasat Ohib, Bishal Thapaliya, Gintare Karolina Dziugaite, Jingyu Liu, Vince D. Calhoun, Sergey M. Plis:
Unmasking Efficiency: Learning Salient Sparse Models in Non-IID Federated Learning. CoRR abs/2405.09037 (2024)
[i58]
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Bishal Thapaliya, Robyn L. Miller, Jiayu Chen, Yu-Ping Wang, Esra Akbas, Ram Sapkota, Bhaskar Ray, Pranav Suresh, Santosh Ghimire, Vince D. Calhoun, Jingyu Liu:
DSAM: A Deep Learning Framework for Analyzing Temporal and Spatial Dynamics in Brain Networks. CoRR abs/2405.15805 (2024)
[i57]
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  - journals/corr/abs-2406-11825
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Bradley T. Baker, Vince D. Calhoun, Sergey M. Plis:
Spectral Introspection Identifies Group Training Dynamics in Deep Neural Networks for Neuroimaging. CoRR abs/2406.11825 (2024)
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  - journals/corr/abs-2406-12683
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Nagur Shareef Shaik, Teja Krishna Cherukuri, Vince D. Calhoun, Dong Hye Ye:
Spatial Sequence Attention Network for Schizophrenia Classification from Structural Brain MR Images. CoRR abs/2406.12683 (2024)
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  - journals/corr/abs-2406-13292
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Giorgio Dolci, Federica Cruciani, Md Abdur Rahaman, Anees Abrol, Jiayu Chen, Zening Fu, Ilaria Boscolo Galazzo, Gloria Menegaz, Vince D. Calhoun:
An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease. CoRR abs/2406.13292 (2024)
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Giorgio Dolci, Charles A. Ellis, Federica Cruciani, Lorenza Brusini, Anees Abrol, Ilaria Boscolo Galazzo, Gloria Menegaz, Vince D. Calhoun:
Multimodal MRI-based Detection of Amyloid Status in Alzheimer's Disease Continuum. CoRR abs/2406.13305 (2024)
[i53]
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  - journals/corr/abs-2407-19385
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Nagur Shareef Shaik, Teja Krishna Cherukuri, Vince D. Calhoun, Dong Hye Ye:
Multi-modal Imaging Genomics Transformer: Attentive Integration of Imaging with Genomic Biomarkers for Schizophrenia Classification. CoRR abs/2407.19385 (2024)
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  - journals/corr/abs-2408-00378
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Yuxiang Wei, Anees Abrol, James J. Lah, Deqiang Qiu, Vince D. Calhoun:
A deep spatio-temporal attention model of dynamic functional network connectivity shows sensitivity to Alzheimer's in asymptomatic individuals. CoRR abs/2408.00378 (2024)
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  - journals/corr/abs-2408-13074
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Yuxiang Wei, Anees Abrol, Reihaneh Hassanzadeh, Vince D. Calhoun:
Hierarchical Spatio-Temporal State-Space Modeling for fMRI Analysis. CoRR abs/2408.13074 (2024)
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  - journals/corr/abs-2408-14254
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Gang Qu, Ziyu Zhou, Vince D. Calhoun, Aiying Zhang, Yu-Ping Wang:
Integrated Brain Connectivity Analysis with fMRI, DTI, and sMRI Powered by Interpretable Graph Neural Networks. CoRR abs/2408.14254 (2024)
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  - journals/corr/abs-2410-19774
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Oktay Agcaoglu, Rogers F. Silva, Deniz Alaçam, Sergey M. Plis, Tülay Adali, Vince D. Calhoun:
Copula-Linked Parallel ICA: A Method for Coupling Structural and Functional MRI brain Networks. CoRR abs/2410.19774 (2024)
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  - journals/corr/abs-2410-23515
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Yutong Gao, Vince D. Calhoun, Robyn L. Miller:
Generative forecasting of brain activity enhances Alzheimer's classification and interpretation. CoRR abs/2410.23515 (2024)
2023
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  - journals/brain/SendiZFLDMSCM23
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Mohammad S. Eslampanah Sendi, Elaheh Zendehrouh, Zening Fu, Jingyu Liu, Yuhui Du, Elizabeth Mormino, David H. Salat, Vince D. Calhoun, Robyn L. Miller:
Disrupted Dynamic Functional Network Connectivity Among Cognitive Control Networks in the Progression of Alzheimer's Disease. Brain Connect. 13(6): 334-343 (2023)
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Yutong Gao, Noah Lewis, Vince D. Calhoun, Robyn L. Miller:
Interpretable LSTM model reveals transiently-realized patterns of dynamic brain connectivity that predict patient deterioration or recovery from very mild cognitive impairment. Comput. Biol. Medicine 161: 107005 (2023)
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Eric Verner, Helen Petropoulos, Bradley T. Baker, Henry Jeremy Bockholt, Jill Fries, Anastasia Bohsali, Rajikha Raja, Duc Hoai Trinh, Vince D. Calhoun:
BrainForge: An online data analysis platform for integrative neuroimaging acquisition, analysis, and sharing. Concurr. Comput. Pract. Exp. 35(18) (2023)
[j299]
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  - journals/fini/EllisSZCWMC23
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Charles A. Ellis, Mohammad S. Eslampanah Sendi, Rongen Zhang, Darwin A. Carbajal, May D. Wang, Robyn L. Miller, Vince D. Calhoun:
Novel methods for elucidating modality importance in multimodal electrophysiology classifiers. Frontiers Neuroinformatics 17 (2023)
[j298]
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  - journals/fini/MartinBPRPSKRBGBTEFPC23
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Dylan Martin, Sunitha Basodi, Sandeep R. Panta, Kelly Rootes-Murdy, Paul Prae, Anand D. Sarwate, Ross Kelly, Javier Tomas Romero, Bradley T. Baker, Harshvardhan Gazula, Henry Jeremy Bockholt, Jessica A. Turner, Nathalia Bianchini Esper, Alexandre R. Franco, Sergey M. Plis, Vince D. Calhoun:
Enhancing collaborative neuroimaging research: introducing COINSTAC Vaults for federated analysis and reproducibility. Frontiers Neuroinformatics 17 (2023)
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  - journals/mia/QiaoGLHHCW23
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Chen Qiao, Bin Gao, Yuechen Liu, Xin-Yu Hu, Wenxing Hu, Vince D. Calhoun, Yu-Ping Wang:
Deep learning with explainability for characterizing age-related intrinsic differences in dynamic brain functional connectivity. Medical Image Anal. 90: 102941 (2023)
[j296]
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  - journals/neuroimage/TaylorRCGHBMC23
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Paul A. Taylor, Richard C. Reynolds, Vince D. Calhoun, Javier Gonzalez-Castillo, Daniel A. Handwerker, Peter A. Bandettini, Amanda F. Mejia, Gang Chen:
Highlight results, don't hide them: Enhance interpretation, reduce biases and improve reproducibility. NeuroImage 274: 120138 (2023)
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  - journals/ni/BelyaevaGWWCSA23
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Irina Belyaeva, Ben Gabrielson, Yu-Ping Wang, Tony W. Wilson, Vince D. Calhoun, Julia M. Stephen, Tülay Adali:
Multi-Subject Analysis for Brain Developmental Patterns Discovery via Tensor Decomposition of MEG Data. Neuroinformatics 21(1): 115-141 (2023)
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Irina Belyaeva, Ben Gabrielson, Yu-Ping Wang, Tony W. Wilson, Vince D. Calhoun, Julia M. Stephen, Tülay Adali:
Correction to: Multi-Subject Analysis for Brain Developmental Patterns Discovery via Tensor Decomposition of MEG Data. Neuroinformatics 21(1): 143 (2023)
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Harshvardhan Gazula, Kelly Rootes-Murdy, Bharath Holla, Sunitha Basodi, Zuo Zhang, Eric Verner, Ross Kelly, Pratima Murthy, Amit Chakrabarti, Debasish Basu, Subodh Bhagyalakshmi Nanjayya, Rajkumar Lenin Singh, Roshan Lourembam Singh, Kartik Kalyanram, Kamakshi Kartik, Kalyanaraman Kumaran, Krishnaveni Ghattu, Rebecca Kuriyan, Sunita Simon Kurpad, Gareth J. Barker, Rose Dawn Bharath, Sylvane Desrivières, Meera Purushottam, Dimitri Papadopoulos-Orfanos, Eesha Sharma, Matthew Hickman, Mireille Toledano, Nilakshi Vaidya, Tobias Banaschewski, Arun L. W. Bokde, Herta Flor, Antoine Grigis, Hugh Garavan, Penny A. Gowland, Andreas Heinz, Rüdiger Brühl, Jean-Luc Martinot, Marie-Laure Paillère-Martinot, Eric Artiges, Frauke Nees, Tomás Paus, Luise Poustka, Juliane H. Fröhner, Lauren Robinson, Michael N. Smolka, Henrik Walter, Jeanne Winterer, Robert Whelan, Jessica A. Turner, Anand D. Sarwate, Sergey M. Plis, Vivek Benegal, Gunter Schumann, Vince D. Calhoun:
Federated Analysis in COINSTAC Reveals Functional Network Connectivity and Spectral Links to Smoking and Alcohol Consumption in Nearly 2,000 Adolescent Brains. Neuroinformatics 21(2): 287-301 (2023)
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Faming Xu, Chen Qiao, Huiyu Zhou, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang:
An explainable autoencoder with multi-paradigm fMRI fusion for identifying differences in dynamic functional connectivity during brain development. Neural Networks 159: 185-197 (2023)
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  - journals/sensors/YangVLCA23
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Hanlu Yang, Trung Vu, Qunfang Long, Vince D. Calhoun, Tülay Adali:
Identification of Homogeneous Subgroups from Resting-State fMRI Data. Sensors 23(6): 3264 (2023)
[j290]
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  - journals/sensors/SunGA0LCA23
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Mingyu Sun, Ben Gabrielson, Mohammad Abu Baker Siddique Akhonda, Hanlu Yang, Francisco Laport, Vince D. Calhoun, Tülay Adali:
A Scalable Approach to Independent Vector Analysis by Shared Subspace Separation for Multi-Subject fMRI Analysis. Sensors 23(11): 5333 (2023)
[j289]
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Anton Orlichenko, Gang Qu, Gemeng Zhang, Binish Patel, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang:
Latent Similarity Identifies Important Functional Connections for Phenotype Prediction. IEEE Trans. Biomed. Eng. 70(6): 1979-1989 (2023)
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Lan Yang, Chen Qiao, Huiyu Zhou, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang:
Explainable Multimodal Deep Dictionary Learning to Capture Developmental Differences From Three fMRI Paradigms. IEEE Trans. Biomed. Eng. 70(8): 2404-2415 (2023)
[j287]
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  - journals/titb/XingKEMCD23
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Ying Xing, Peter V. Kochunov, Theo G. M. van Erp, Tianzhou Ma, Vince D. Calhoun, Yuhui Du:
A Novel Neighborhood Rough Set-Based Feature Selection Method and Its Application to Biomarker Identification of Schizophrenia. IEEE J. Biomed. Health Informatics 27(1): 215-226 (2023)
[j286]
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Xiang Li, Sheri L. Towe, Ryan P. Bell, Rongtao Jiang, Shana A. Hall, Vince D. Calhoun, Christina S. Meade, Jing Sui:
The Individualized Prediction of Neurocognitive Function in People Living With HIV Based on Clinical and Multimodal Connectome Data. IEEE J. Biomed. Health Informatics 27(4): 2094-2104 (2023)
[c332]
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  - conf/acssc/0001GCA23
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Hanlu Yang, Ben Gabrielson, Vince D. Calhoun, Tülay Adali:
REGRESSION-ASSISTED INDEPENDENT VECTOR ANALYSIS: A SOLUTION TO LARGE-SCALE FMRI DATA ANALYSIS. ACSSC 2023: 1443-1447
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Francisco Laport, Trung Vu, Hanlu Yang, Vince D. Calhoun, Tülay Adali:
Reproducibility in Joint Blind Source Separation: Application to fMRI Analysis. ACSSC 2023: 1448-1452
[c330]
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Rui Jin, Shuai Xu, Seung-Jun Kim, Vince D. Calhoun:
Flexible Multisubject Multiset FMRI Data Analysis Using Robust Discriminative Dictionary Learning. ACSSC 2023: 1458-1462
[c329]
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  - conf/bhi/SahaSFSC23
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Rekha Saha, Debbrata K. Saha, Zening Fu, Rogers F. Silva, Vince D. Calhoun:
Multimodal Fusion of Functional and Structural Data to Recognize Longitudinal Change Patterns in the Adolescent Brain. BHI 2023: 1-5
[c328]
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Abhinav Sattiraju, Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun:
An Explainable and Robust Deep Learning Approach for Automated Electroencephalography-Based Schizophrenia Diagnosis. BIBE 2023: 255-259
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Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, Vince D. Calhoun:
Improving Multichannel Raw Electroencephalography-based Diagnosis of Major Depressive Disorder via Transfer Learning with Single Channel Sleep Stage Data. BIBM 2023: 2466-2473
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Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun:
Improving Explainability for Single-Channel EEG Deep Learning Classifiers via Interpretable Filters and Activation Analysis. BIBM 2023: 2474-2481
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Yuhui Du, Yating Guo, Vince D. Calhoun:
How Does Aging Affect Whole-brain Functional Network Connectivity? Evidence from An ICA Method. EMBC 2023: 1-4
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Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun:
A Novel Explainable Fuzzy Clustering Approach for fMRI Dynamic Functional Network Connectivity Analysis. EMBC 2023: 1-4
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Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun:
A Convolutional Autoencoder-based Explainable Clustering Approach for Resting-State EEG Analysis. EMBC 2023: 1-4
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Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun:
Neuropsychiatric Disorder Subtyping Via Clustered Deep Learning Classifier Explanations. EMBC 2023: 1-4
[c321]
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Haleh Falakshahi, Hooman Rokham, Robyn L. Miller, Jean Liu, Vince D. Calhoun:
Network Differential in Gaussian Graphical Models from Multimodal Neuroimaging Data. EMBC 2023: 1-6
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Xiang Li, Ming Xu, Rongtao Jiang, Xuemei Li, Vince D. Calhoun, Xinyu Zhou, Jing Sui:
ICA-based Individualized Differential Structure Similarity Networks for Predicting Symptom Scores in Adolescents with Major Depressive Disorder. EMBC 2023: 1-5
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Robyn L. Miller, Victor M. Vergara, Vince D. Calhoun:
Hyperlocal Spatial Flows in BOLD fMRI Expose Novel Brain-Based Correlates of Schizophrenia. EMBC 2023: 1-4
[c318]
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Chan Aek Panichvatana, Jiayu Chen, Bradley T. Baker, Bishal Thapaliya, Vince D. Calhoun, Jingyu Liu:
Decentralized Parallel Independent Component Analysis for Multimodal, Multisite Data. EMBC 2023: 1-4
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Hooman Rokham, Haleh Falakshahi, Vince D. Calhoun:
A Deep Learning Approach for Psychosis Spectrum Label Noise Detection from Multimodal Neuroimaging Data. EMBC 2023: 1-4
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Debbrata Kumar Saha, Anastasia Bohsali, Rekha Saha, Ihab Hajjar, Vince D. Calhoun:
A Multivariate Method for Estimating and comparing whole brain functional connectomes from fMRI and PET data. EMBC 2023: 1-4
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Rekha Saha, Debbrata K. Saha, Zening Fu, Rogers F. Silva, Vince D. Calhoun:
Functional and Structural Longitudinal Change Patterns in Adolescent Brain. EMBC 2023: 1-4
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Sir-Lord Wiafe, Zening Fu, Vince D. Calhoun, Ashkan Faghiri:
Phase and amplitude, two sides of functional connectivity. EMBC 2023: 1-4
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Elaheh Zendehrouh, Mohammad S. Eslampanah Sendi, Vince D. Calhoun:
Towards a multimodal neuroimaging-based risk score for Alzheimer's disease by combining clinical and large N>37000 population data. EMBC 2023: 1-4
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R. A. Borsoi, Isabell Lehmann, Mohammad A. B. S. Akhonda, Vince D. Calhoun, Konstantin Usevich, David Brie, Tülay Adali:
Coupled CP Tensor Decomposition with Shared and Distinct Components for Multi-Task Fmri Data Fusion. ICASSP 2023: 1-5
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Giorgio Dolci, Md Abdur Rahaman, Ilaria Boscolo Galazzo, Federica Cruciani, Anees Abrol, Jiayu Chen, Zening Fu, Kuaikuai Duan, Gloria Menegaz, Vince D. Calhoun:
Deep Generative Transfer Learning Predicts Conversion To Alzheimer'S Disease From Neuroimaging Genomics Data. ICASSP Workshops 2023: 1-5
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Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, Vince D. Calhoun:
Novel Approach Explains Spatio-Spectral Interactions In Raw Electroencephalogram Deep Learning Classifiers. ICASSP Workshops 2023: 1-5
[c309]
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Ben Gabrielson, Mingyu Sun, Mohammad A. B. S. Akhonda, Vince D. Calhoun, Tülay Adali:
Independent Vector Analysis with Multivariate Gaussian Model: a Scalable Method by Multilinear Regression. ICASSP 2023: 1-5
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Fateme Ghayem, Hanlu Yang, Furkan Kantar, Seung-Jun Kim, Vince D. Calhoun, Tülay Adali:
New Interpretable Patterns and Discriminative Features from Brain Functional Network Connectivity using Dictionary Learning. ICASSP 2023: 1-5
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Ayush Kanyal, Srinivas Kandula, Vince D. Calhoun, Dong Hye Ye:
Multi-Modal Deep Learning on Imaging Genetics for Schizophrenia Classification. ICASSP Workshops 2023: 1-5
[c306]
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Qiang Li, Shujian Yu, Kristoffer H. Madsen, Vince D. Calhoun, Armin Iraji:
Higher-Order Organization in the Human Brain From Matrix-Based Rényi's Entropy. ICASSP Workshops 2023: 1-5
[c305]
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Mark D. LoPresto, Mohammad A. B. S. Akhonda, Vince D. Calhoun, Tülay Adali:
Fusion of Multi-Modal Neuroimaging Data and Association With Cognitive Data. ICASSP Workshops 2023: 1-5
[c304]
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  - conf/icassp/MahmoodFCP23
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Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis:
Glacier: Glass-Box Transformer for Interpretable Dynamic Neuroimaging. ICASSP 2023: 1-5
[c303]
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  - conf/icassp/MillerVPC23
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Robyn L. Miller, Victor M. Vergara, Helen Petropoulos, Vince D. Calhoun:
Local Spatial Flow Strengths in Bold FMRI are Strongly Impacted by Schizophrenia. ICASSP Workshops 2023: 1-4
[c302]
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Hanlu Yang, Fateme Ghayem, Ben Gabrielson, Mohammad A. B. S. Akhonda, Vince D. Calhoun, Tülay Adali:
Constrained Independent Component Analysis Based on Entropy Bound Minimization for Subgroup Identification from Multi-subject fMRI Data. ICASSP 2023: 1-5
[c301]
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Oktay Agcaoglu, Rogers F. Silva, Deniz Alaçam, Vince D. Calhoun:
A Multi-dimensional Joint ICA Model with Gaussian Copula. ICIAP Workshops (2) 2023: 152-163
[c300]
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  - conf/iconip/HanLKHLGC23
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Yue Han, Qiu-Hua Lin, Li-Dan Kuang, Ying-Guang Hao, Wei-Xing Li, Xiao-Feng Gong, Vince D. Calhoun:
Extraction of One Time Point Dynamic Group Features via Tucker Decomposition of Multi-subject FMRI Data: Application to Schizophrenia. ICONIP (9) 2023: 518-527
[c299]
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  - conf/isbi/AjithC23
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Meenu Ajith, Vince D. Calhoun:
Functional Network Connectivity Based Mental Health Category Prediction from Rest-fMRI Data. ISBI 2023: 1-5
[c298]
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  - conf/isbi/BasodiRGRPC23
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Sunitha Basodi, Rajikha Raja, Harshvardhan Gazula, Javier Tomas Romero, Sandeep R. Panta, Vince D. Calhoun:
Federated Linear Mixed Effects Modeling for Voxel-Based Morphometry. ISBI 2023: 1-4
[c297]
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Ishaan Batta, Anees Abrol, Vince D. Calhoun:
A Multimodal Deep Learning Approach for Automated Detection and Characterization of Distinctly Salient Features of Alzheimers Disease. ISBI 2023: 1-4
[c296]
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Yuda Bi, Anees Abrol, Zening Fu, Vince D. Calhoun:
MultiViT: Multimodal Vision Transformer for Schizophrenia Prediction using Structural MRI and Functional Network Connectivity Data. ISBI 2023: 1-5
[c295]
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  - conf/isbi/BostamiDACI23
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Biozid Bostami, Mukesh Dhamala, Tülay Adali, Vince D. Calhoun, Armin Iraji:
Spatial Dynamic Propagation of Network Activity in Resting fMRI Data. ISBI 2023: 1-4
[c294]
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  - conf/isbi/DuWNC23
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Yuhui Du, Fulin Wu, Ju Niu, Vince D. Calhoun:
An Adaptive Semi-Supervised Deep Clustering and Its Application to Identifying Biotypes of Psychiatric Disorders. ISBI 2023: 1-4
[c293]
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  - conf/isbi/DuanSLAC23
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Kuaikuai Duan, Rogers F. Silva, Jingyu Liu, Oktay Agcaoglu, Vince D. Calhoun:
Any-Way Independent Component Analysis with Reference. ISBI 2023: 1-4
[c292]
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  - conf/isbi/EllisMC23
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Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun:
Identifying Neuropsychiatric Disorder Subtypes and Subtype-Dependent Variation in Diagnostic Deep Learning Classifier Performance. ISBI 2023: 1-4
[c291]
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Armin Iraji, Jiayu Chen, Ashkan Faghiri, Zening Fu, Jingyu Liu, Juan R. Bustillo, Tülay Adali, Mukesh Dhamala, Vince D. Calhoun:
Capturing Spatial Dynamics Using Time-Resolved Referenced-Informed Network Estimation Techniques. ISBI 2023: 1-4
[c290]
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  - conf/isbi/IrajiKCMSAC23
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Armin Iraji, Katarzyna Kazimierczak, Jiayu Chen, Sara Motlaghian, Karsten Specht, Tülay Adali, Vince D. Calhoun:
The Nonlinear Brain: Towards Uncovering Hidden Brain Networks Using Explicitly Nonlinear Functional Interaction. ISBI 2023: 1-4
[c289]
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  - conf/isbi/LewisIMC23
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Noah Lewis, Armin Iraji, Robyn L. Miller, Vince D. Calhoun:
Topological Correction of Subject-Level Intrinsic Connectivity Networks. ISBI 2023: 1-4
[c288]
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  - conf/isbi/LiASC23
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Xinhui Li, Tülay Adali, Rogers F. Silva, Vince D. Calhoun:
Multimodal Subspace Independent Vector Analysis Better Captures Hidden Relationships in Multimodal Neuroimaging Data. ISBI 2023: 1-5
[c287]
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Xinhui Li, Daniel Khosravinezhad, Vince D. Calhoun, Rogers F. Silva:
Evaluating Trade-Offs in IVA of Multimodal Neuroimaging using Cross-Platform Multidataset Independent Subspace Analysis. ISBI 2023: 1-5
[c286]
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  - conf/isbi/SalmanILC23
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Mustafa S. Salman, Armin Iraji, Noah Lewis, Vince D. Calhoun:
Topological Characteristics of 5d Spatially Dynamic Brain Networks in Schizophrenia. ISBI 2023: 1-5
[c285]
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Pranav Suresh, Bhaskar Ray, Bishal Thapaliya, Britny Farahdel, Behnam Kazemivash, Jiayu Chen, Kuaikuai Duan, Vince D. Calhoun, Jingyu Liu:
Effective Training Strategy for NN Models of Working Memory Classification with Limited Samples. ISBI 2023: 1-4
[c284]
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  - conf/metroxraine/DolciCGCM23
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Giorgio Dolci, Federica Cruciani, Ilaria Boscolo Galazzo, Vince D. Calhoun, Gloria Menegaz:
Objective Assessment of the Bias Introduced by Baseline Signals in XAI Attribution Methods. MetroXRAINE 2023: 266-271
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Mahshid Fouladivanda, Armin Iraji, Lei Wu, Vince D. Calhoun:
Joint Structural and Functional Connectivity Learning Based Independent Component Analysis. MLSP 2023: 1-5
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Aaron Oliver-Taylor, Adam Li, Adam G. Thomas, Adeen Flinker, Adina S. Wagner, Agah Karakuzu, Aki Nikolaidis, Alberto Lazari, Alejandro de la Vega, Alessio Giacomel, Alexander Rockhill, Alexander Jones, Alexander Li Cohen, Alexander von Lautz, Alexandre Gramfort, Alexandre Hutton, Alexandre Routier, Alexandru Foias, Ali Khan, Alizee Wickenheiser, Ana Fouto, Anders Eklund, Andrea Pigorini, Andrew Hoopes, Andrew Jahn, Andrew Janke, Anibal Sólon, Anthony Galassi, Ariel Rokem, Arjen Stolk, Arnaud Delorme, Arnaud Marcoux, Arshitha Basavaraj, Ashley G. Gillman, Athanasia M. Mowinckel, Aysegul Gunduz, Azeez Adebimpe, B. Nolan Nichols, Balint Kincses, Benjamin Beasley, Benjamin K. Dichter, Benjamin Gagl, Bertrand Thirion, Bradley Voytek, Brett L. Foster, Brian A. Wandell, Brian N. Lundstrom, Camille Maumet, Carlo Miniussi, Cecile Madjar, Chloé Pasturel, Chris Benjamin, Chris Gahnström, Chris Holdgraf, Chris Gorgolewski, Chris Rorden, Christian Büchel, Christian Horea, Christine Rogers, Christophe Phillips, Christopher J. Honey, Christopher J. Markiewicz, Christopher Lee-Messer, Clara Moreau, Clint Hansen, Cyril R. Pernet, Cyrus Eierud, D. Sturgeon, Dan Levitas, Dan Lurie, Daniel A. Handwerker, David C. Alsop, David A. Boas, David M. Groppe, David B. Keator, David McAlpine, David Thomas, Dejan Draschkow, Dianne K. Patterson, Dimitri Papadopoulos Orfanos, Dmitry Petrov, Dora Hermes, Dorien Huijser, Douglas N. Greve, Duncan Macleod, Dung Truong, Dylan Nielson, Eduard Ort, Eleonora Marcantoni, Elizabeth Bock, Elizabeth DuPre, Elke Warmerdam, Erdal Karaca, Eric A. Earl, Eric Achten, Eric Bridgeford, Erin W. Dickie, Ethan Blackwood, Eugene P. Duff, Ezequiel Mikulan, Felipe Orihuela-Espina, Fidel Alfaro-Almagro, Filip Szczepankiewicz, Filippo Maria Castelli, Franco Pestilli, Franklin W. Feingold, François Tadel, Gaia Rizzo, Gang Chen, Gaël Varoquaux, Ghislain Vaillant, Giacomo Bertazzoli, Giacomo Guidali, Giacomo Mazzamuto, Gilles de Hollander, Gio Piantoni, Gitte M. Knudsen, Giulio Castegnaro, Giuseppe Gallitto, Graham Searle, Granville J. Matheson, Gregory Kiar, Gregory Noack, Greydon Gilmore, Guillaume Flandin, Gunnar Schaefer, Gustav Nilsonne, Hamish Innes-Brown, Hanne D. Hansen, Hanzhang Lu, Hao-Ting Wang, Helena Cockx, Henk Mutsaerts, Hernando Ombao, Hugo Boniface, Ayse Ilkay Isik, Ilona Lipp, International Neuroinformatics Coordinating Facility, Iris I. A. Groen, Isla Staden, Jaap von der Aar, Jakub Kaczmarzyk, James Gholam, James D. Kent, Jan-Mathijs Schoffelen, Jan Petr, Jean-Baptiste Poline, Jean-Christophe Houde, Jean-Dominique Gallezot, Jean-Philippe Lachaux, Jeanette Mumford, Jefferson Casimir, Jeffrey G. Ojemann, Jeffrey S. Grethe, JegouA, Jelle R. Dalenberg, Jeremy T. Moreau, Jessica A. Turner, Jochem W. Rieger, John A. Detre, John Pellman, John T. Wodder, Joke Durnez, Jon Haitz Legarreta Gorrono, Jonathan C. Lau, Jonathan Winawer, Joost P. A. Kuijer, Jose Manuel Saborit, Joseph Wexler, Joseph G. Woods, J. Guiomar Niso, Julia Sprenger, Julien Cohen-Adad, Julius Welzel, Kai J. Miller, Kangjoo Lee, Katja Heuer, Kay Robbins, Kevin Larcher, Kimberly L. Ray, Kirstie J. Whitaker, Klara Gregorova, Klaus Gramann, Kris Thielemans, Kristofer E. Bouchard, Kurt Schilling, Laetitia Fesselier, Laura & John Arnold Foundation, Leandro Beltrachini, Lee Kamentsky, Lennart Walger, Lennart Wittkuhn, Liberty S. Hamilton, Luca Pollonini, Luis Hernandez-Garcia, Luke J. Edwards, Lyuba Zehl, Mainak Jas, Manjari Narayan, Manuel R. Mercier, Maqsood Yaqub, Marc Lalancette, Marco Castellaro, Maria de la Iglesia, Marie-Hélène Bourget, Mark Mikkelsen, Markus Morawski, Marta Bortoletto, Martin Craig, Martin Nørgaard, Martin Szinte, Martin Wilson, Martina Bulgari, Mateusz Pawlik, Mathias Goncalves, Mathieu Boudreau, Matt Sanderson, Matteo Tonietto, Matthias Günther, Matthias Van Osch, Maureen J. Shader, Maurice Pasternak, Max A. van den Boom, Melanie Ganz-Benjaminsen, Michael Chappell, Michael Hanke, Michael P. Harms, Michael P. Milham, Michael P. Notter, Michael Schirner, Mikaël Naveau, Nader Pouratian, Natalia Petridou, National Institute of Mental Health, Nell Hardcastle, Nicholas Traut, Nick F. Ramsey, Nicole C. Swann, Nima Bigdely Shamlo, Olivier David, Orrin Devinsky, Oscar Esteban, Pamela LaMontagne, Parul Sethi, Patricia Clement, Patrick Park, Paule-Joanne Toussaint, Peer Herholz, Petra Ritter, Pierre Rioux, Pieter Vandemaele, Pradeep Reddy Raamana, R. Cameron Craddock, Rémi Gau, Richard Höchenberger, Richard N. Henson, Robert B. Innis, Robert E. Smith, Robert Knight, Robert Luke, Robert Oostenveld, Roberto Toro, Rohan Goyal, Ross W. Blair, Russell A. Poldrack, Rémi Adon, Samir Das, Samuel Garcia, Samuel A. Nastase, Sara Elgayar, Sasha D'Ambrosio, Satrajit S. Ghosh, Scott Makeig, Sein Jeung, Shashank Bansal, Sjoerd B. Vos, Soichi Hayashi, Stefan Appelhoff, Stephan Bickel, Steven L. Meisler, Suyash Bhogawar, Sylvain Baillet, Sylvain Takerkart, Sébastien Tourbier, Sören Grothkopp, Tal Pal Attia, Tal Yarkoni, Tamás Spisák, Tamás Józsa, Taylor Salo, Teon L. Brooks, Thomas E. Nichols, Thomas Funck, Thomas Kirk, Thomas W. Okell, Tibor Auer, Timo Dickscheid, Timotheus Berg, Tobey Betthauser, Tobias Bengfort, Tom Hampshire, Tor Wager, Travis Riddle, Tristan Glatard, Tyler Collins, Ulrike Bingel, Vanessa V. Sochat, Vasudev Raguram, Vince D. Calhoun, Vittorio Iacovella, Vladimir Litvak, Wietske van der Zwaag, William Clarke, William Triplett, Wouter V. Potters, Xiangrui Li, Yaroslav O. Halchenko, Yoni Ashar, Yuan Wang, Zachary Michael, ezemikulan, josator2, monkeyman192, Étienne Bergeron:
bids-specification. Zenodo, 2023
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Qiang Li, Shujian Yu, Kristoffer H. Madsen, Vince D. Calhoun, Armin Iraji:
Higher-order Organization in the Human Brain from Matrix-Based Rényi's Entropy. CoRR abs/2303.11994 (2023)
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Riyasat Ohib, Bishal Thapaliya, Pratyush Gaggenapalli, Jingyu Liu, Vince D. Calhoun, Sergey M. Plis:
SalientGrads: Sparse Models for Communication Efficient and Data Aware Distributed Federated Training. CoRR abs/2304.07488 (2023)
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Eloy Geenjaar, Donghyun Kim, Riyasat Ohib, Marlena Duda, Amrit Kashyap, Sergey M. Plis, Vince D. Calhoun:
Learning low-dimensional dynamics from whole-brain data improves task capture. CoRR abs/2305.14369 (2023)
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Md. Mahfuzur Rahman, Vince D. Calhoun, Sergey M. Plis:
Looking deeper into interpretable deep learning in neuroimaging: a comprehensive survey. CoRR abs/2307.09615 (2023)
[i43]
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Yujia Xie, Xinhui Li, Vince D. Calhoun:
Predictive Sparse Manifold Transform. CoRR abs/2308.14207 (2023)
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Yuda Bi, Anees Abrol, Jing Sui, Vince D. Calhoun:
Cross-Modal Synthesis of Structural MRI and Functional Connectivity Networks via Conditional ViT-GANs. CoRR abs/2309.08160 (2023)
[i41]
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Bishal Thapaliya, Esra Akbas, Jiayu Chen, Ram Sapkota, Bhaskar Ray, Pranav Suresh, Vince D. Calhoun, Jingyu Liu:
Brain Networks and Intelligence: A Graph Neural Network Based Approach to Resting State fMRI Data. CoRR abs/2311.03520 (2023)
[i40]
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Yutong Gao, Charles A. Ellis, Vince D. Calhoun, Robyn L. Miller:
Improving age prediction: Utilizing LSTM-based dynamic forecasting for data augmentation in multivariate time series analysis. CoRR abs/2312.08383 (2023)
2022
[j285]
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Beverly A. Underwood, Linda Yankie, Eric P. Nawrocki, Vasuki Palanigobu, Sergiy Gotvyanskyy, Vincent D. Calhoun, Michael Kornbluh, Thomas G. Smith, Lydia Fleischmann, Denis Sinyakov, Colleen J. Bollin, Ilene Karsch-Mizrachi:
Rapid automated validation, annotation and publication of SARS-CoV-2 sequences to GenBank. Database J. Biol. Databases Curation 2022(2022) (2022)
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Md Abdur Rahaman, Eswar Damaraju, Jessica A. Turner, Theo G. M. van Erp, Daniel H. Mathalon, Jatin G. Vaidya, Bryon A. Mueller, Godfrey D. Pearlson, Vince D. Calhoun:
Tri-Clustering Dynamic Functional Network Connectivity Identifies Significant Schizophrenia Effects Across Multiple States in Distinct Subgroups of Individuals. Brain Connect. 12(1): 61-73 (2022)
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Mustafa S. Salman, Tor D. Wager, Eswar Damaraju, Anees Abrol, Victor M. Vergara, Zening Fu, Vince D. Calhoun:
An Approach to Automatically Label and Order Brain Activity/Component Maps. Brain Connect. 12(1): 85-95 (2022)
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Oktay Agcaoglu, Ryan L. Muetzel, Barnaly Rashid, Tonya White, Henning Tiemeier, Vince D. Calhoun:
Lateralization of Resting-State Networks in Children: Association with Age, Sex, Handedness, Intelligence Quotient, and Behavior. Brain Connect. 12(3): 246-259 (2022)
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Xing Meng, Armin Iraji, Zening Fu, Peter V. Kochunov, Aysenil Belger, Judith M. Ford, Sarah C. McEwen, Daniel H. Mathalon, Bryon A. Mueller, Godfrey D. Pearlson, Steven G. Potkin, Adrian Preda, Jessica A. Turner, Theo G. M. van Erp, Jing Sui, Vince D. Calhoun:
Multimodel Order Independent Component Analysis: A Data-Driven Method for Evaluating Brain Functional Network Connectivity Within and Between Multiple Spatial Scales. Brain Connect. 12(7): 617-628 (2022)
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Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun:
A Systematic Approach for Explaining Time and Frequency Features Extracted by Convolutional Neural Networks From Raw Electroencephalography Data. Frontiers Neuroinformatics 16 (2022)
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Min Zhao, Weizheng Yan, Na Luo, Dongmei Zhi, Zening Fu, Yuhui Du, Shan Yu, Tianzi Jiang, Vince D. Calhoun, Jing Sui:
An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data. Medical Image Anal. 78: 102413 (2022)
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Qiu-Hua Lin, Yan-Wei Niu, Jing Sui, Wen-Da Zhao, Chuanjun Zhuo, Vince D. Calhoun:
SSPNet: An interpretable 3D-CNN for classification of schizophrenia using phase maps of resting-state complex-valued fMRI data. Medical Image Anal. 79: 102430 (2022)
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Kanhao Zhao, Boris Duka, Hua Xie, Desmond J. Oathes, Vince D. Calhoun, Yu Zhang:
A dynamic graph convolutional neural network framework reveals new insights into connectome dysfunctions in ADHD. NeuroImage 246: 118774 (2022)
[j276]
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Brittany K. Taylor, Michaela R. Frenzel, Jacob A. Eastman, Christine M. Embury, Oktay Agcaoglu, Yu-Ping Wang, Julia M. Stephen, Vince D. Calhoun, Tony W. Wilson:
Individual differences in amygdala volumes predict changes in functional connectivity between subcortical and cognitive control networks throughout adolescence. NeuroImage 247: 118852 (2022)
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Armin Iraji, Ashkan Faghiri, Zening Fu, Peter V. Kochunov, Bhim M. Adhikari, Aysenil Belger, Judith M. Ford, Sarah C. McEwen, Daniel H. Mathalon, Godfrey D. Pearlson, Steven G. Potkin, Adrian Preda, Jessica A. Turner, Theo G. M. van Erp, Catie Chang, Vincent D. Calhoun:
Moving beyond the 'CAP' of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping. NeuroImage 251: 119013 (2022)
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Brittany K. Taylor, Elizabeth Heinrichs-Graham, Jacob A. Eastman, Michaela R. Frenzel, Yu-Ping Wang, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson:
Longitudinal changes in the neural oscillatory dynamics underlying abstract reasoning in children and adolescents. NeuroImage 253: 119094 (2022)
[j273]
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Nathan M. Petro, Lauren R. Ott, Samantha H. Penhale, Maggie P. Rempe, Christine M. Embury, Giorgia Picci, Yu-Ping Wang, Julia M. Stephen, Vince D. Calhoun, Tony W. Wilson:
Eyes-closed versus eyes-open differences in spontaneous neural dynamics during development. NeuroImage 258: 119337 (2022)
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Zack Y. Shan, Abdalla Z. Mohamed, Paul Schwenn, Larisa T. McLoughlin, Amanda Boyes, Dashiell D. Sacks, Christina Driver, Vince D. Calhoun, Jim Lagopoulos, Daniel F. Hermens:
A longitudinal study of functional connectome uniqueness and its association with psychological distress in adolescence. NeuroImage 258: 119358 (2022)
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Gemeng Zhang, Biao Cai, Aiying Zhang, Zhuozhuo Tu, Li Xiao, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
Detecting abnormal connectivity in schizophrenia via a joint directed acyclic graph estimation model. NeuroImage 260: 119451 (2022)
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Bhim M. Adhikari, L. Elliot Hong, Zhiwei Zhao, Danny J. J. Wang, Paul M. Thompson, Neda Jahanshad, Alyssa H. Zhu, Stefan Holiga, Jessica A. Turner, Theo G. M. van Erp, Vince D. Calhoun, Kathryn S. Hatch, Heather Bruce, Stephanie M. Hare, Joshua Chiappelli, Eric L. Goldwaser, Mark D. Kvarta, Yizhou Ma, Xiaoming Du, Thomas E. Nichols, Alan R. Shuldiner, Braxton D. Mitchell, Juergen Dukart, Peter V. Kochunov:
Cerebral blood flow and cardiovascular risk effects on resting brain regional homogeneity. NeuroImage 262: 119555 (2022)
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Usman Mahmood, Zening Fu, Satrajit S. Ghosh, Vince D. Calhoun, Sergey M. Plis:
Through the looking glass: Deep interpretable dynamic directed connectivity in resting fMRI. NeuroImage 264: 119737 (2022)
[j268]
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Madison H. Fung, Elizabeth Heinrichs-Graham, Brittany K. Taylor, Michaela R. Frenzel, Jacob A. Eastman, Yu-Ping Wang, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson:
The development of sensorimotor cortical oscillations is mediated by pubertal testosterone. NeuroImage 264: 119745 (2022)
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Nipuna Senanayake, Robert Podschwadt, Daniel Takabi, Vince D. Calhoun, Sergey M. Plis:
NeuroCrypt: Machine Learning Over Encrypted Distributed Neuroimaging Data. Neuroinformatics 20(1): 91-108 (2022)
[j266]
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Jessica A. Turner, Vince D. Calhoun, Paul M. Thompson, Neda Jahanshad, Christopher R. K. Ching, Sophia I. Thomopoulos, Eric Verner, Gregory P. Strauss, Anthony O. Ahmed, Matthew D. Turner, Sunitha Basodi, Judith M. Ford, Daniel H. Mathalon, Adrian Preda, Aysenil Belger, Bryon A. Mueller, Kelvin O. Lim, Theo G. M. van Erp:
ENIGMA + COINSTAC: Improving Findability, Accessibility, Interoperability, and Re-usability. Neuroinformatics 20(1): 261-275 (2022)
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Kelly Rootes-Murdy, Harshvardhan Gazula, Eric Verner, Ross Kelly, Thomas DeRamus, Sergey M. Plis, Anand D. Sarwate, Jessica A. Turner, Vince D. Calhoun:
Federated Analysis of Neuroimaging Data: A Review of the Field. Neuroinformatics 20(2): 377-390 (2022)
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Ishaan Batta, Anees Abrol, Zening Fu, Adrian Preda, Theo G. M. van Erp, Vince D. Calhoun:
Building Models of Functional Interactions Among Brain Domains that Encode Varying Information Complexity: A Schizophrenia Case Study. Neuroinformatics 20(3): 777-791 (2022)
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Sunitha Basodi, Rajikha Raja, Bhaskar Ray, Harshvardhan Gazula, Anand D. Sarwate, Sergey M. Plis, Jingyu Liu, Eric Verner, Vince D. Calhoun:
Decentralized Brain Age Estimation Using MRI Data. Neuroinformatics 20(4): 981-990 (2022)
[j262]
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Mohammad A. B. S. Akhonda, Yuri Levin-Schwartz, Vince D. Calhoun, Tülay Adali:
Association of Neuroimaging Data with Behavioral Variables: A Class of Multivariate Methods and Their Comparison Using Multi-Task FMRI Data. Sensors 22(3): 1224 (2022)
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Marie Roald, Carla Schenker, Vince D. Calhoun, Tülay Adali, Rasmus Bro, Jeremy E. Cohen, Evrim Acar:
An AO-ADMM Approach to Constraining PARAFAC2 on All Modes. SIAM J. Math. Data Sci. 4(3): 1191-1222 (2022)
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Erik Meijering, Vince D. Calhoun, Gloria Menegaz, David J. Miller, Jong Chul Ye:
Deep Learning in Biological Image and Signal Processing [From the Guest Editors]. IEEE Signal Process. Mag. 39(2): 24-26 (2022)
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Weizheng Yan, Gang Qu, Wenxing Hu, Anees Abrol, Biao Cai, Chen Qiao, Sergey M. Plis, Yu-Ping Wang, Jing Sui, Vince D. Calhoun:
Deep Learning in Neuroimaging: Promises and challenges. IEEE Signal Process. Mag. 39(2): 87-98 (2022)
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Tülay Adali, Furkan Kantar, Mohammad Abu Baker Siddique Akhonda, Stephen C. Strother, Vince D. Calhoun, Evrim Acar:
Reproducibility in Matrix and Tensor Decompositions: Focus on model match, interpretability, and uniqueness. IEEE Signal Process. Mag. 39(4): 8-24 (2022)
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Li Xiao, Biao Cai, Gang Qu, Gemeng Zhang, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
Distance Correlation-Based Brain Functional Connectivity Estimation and Non-Convex Multi-Task Learning for Developmental fMRI Studies. IEEE Trans. Biomed. Eng. 69(10): 3039-3050 (2022)
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Peng Peng, Yipu Zhang, Yongfeng Ju, Kaiming Wang, Gang Li, Vince D. Calhoun, Yu-Ping Wang:
Group Sparse Joint Non-Negative Matrix Factorization on Orthogonal Subspace for Multi-Modal Imaging Genetics Data Analysis. IEEE ACM Trans. Comput. Biol. Bioinform. 19(1): 479-490 (2022)
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Yue Han, Qiu-Hua Lin, Li-Dan Kuang, Xiao-Feng Gong, Fengyu Cong, Yu-Ping Wang, Vince D. Calhoun:
Low-Rank Tucker-2 Model for Multi-Subject fMRI Data Decomposition With Spatial Sparsity Constraint. IEEE Trans. Medical Imaging 41(3): 667-679 (2022)
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Yipu Zhang, Haowei Zhang, Li Xiao, Yuntong Bai, Vince D. Calhoun, Yu-Ping Wang:
Multi-Modal Imaging Genetics Data Fusion via a Hypergraph-Based Manifold Regularization: Application to Schizophrenia Study. IEEE Trans. Medical Imaging 41(9): 2263-2272 (2022)
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Reihaneh Hassanzadeh, Anees Abrol, Vince D. Calhoun:
Classification of Schizophrenia and Alzheimer's Disease using Resting-State Functional Network Connectivity. BHI 2022: 1-4
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Hooman Rokham, Haleh Falakshahi, Vince D. Calhoun:
Relationship of Hemodynamic Delay and Sex Differences Among Adolescents Using Resting-state fMRI Data. BHI 2022: 1-4
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Giorgio Dolci, Md Abdur Rahaman, Jiayu Chen, Kuaikuai Duan, Zening Fu, Anees Abrol, Gloria Menegaz, Vince D. Calhoun:
A deep generative multimodal imaging genomics framework for Alzheimer's disease prediction. BIBE 2022: 41-44
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Charles A. Ellis, Martina Lapera Sancho, Mohammad S. Eslampanah Sendi, Robyn L. Miller, Vince D. Calhoun:
Exploring Relationships between Functional Network Connectivity and Cognition with an Explainable Clustering Approach. BIBE 2022: 293-296
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Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun:
An Approach for Estimating Explanation Uncertainty in fMRI dFNC Classification. BIBE 2022: 297-300
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Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, Vince D. Calhoun:
Examining Effects of Schizophrenia on EEG with Explainable Deep Learning Models. BIBE 2022: 301-304
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Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, Vince D. Calhoun:
Examining Reproducibility of EEG Schizophrenia Biomarkers Across Explainable Machine Learning Models. BIBE 2022: 305-308
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Marlena Duda, Ashkan Faghiri, Vince D. Calhoun:
Multimodal Analysis Uncovers Links between Grey Matter Volume and both Low-and High-frequency Dynamic Connectivity States in Schizophrenia. BIBM 2022: 1521-1525
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Khondoker Murad Hossain, Suchita Bhinge, Qunfang Long, Vince D. Calhoun, Tülay Adali:
Data-driven spatio-temporal dynamic brain connectivity analysis using fALFF: Application to sensorimotor task data. CISS 2022: 200-205
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Mohammad S. Eslampanah Sendi, Hossein Dini, Luis Emilio Bruni, Vince D. Calhoun:
Default mode network dynamic functional network connectivity predicts psychotic symptom severity. EMBC 2022: 247-250
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Zening Fu, Mustafa S. Salman, Jingyu Liu, Vince D. Calhoun:
Functional Connectivity Stability: A Signature of Neurocognitive Development and Psychiatric Problems in Children. EMBC 2022: 251-254
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Biozid Bostami, Flor A. Espinoza, Harm J. van der Horn, Joukje van der Naalt, Vince D. Calhoun, Victor M. Vergara:
Multi-Site Mild Traumatic Brain Injury Classification with Machine Learning and Harmonization. EMBC 2022: 537-540
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Xinhui Li, Eloy Geenjaar, Zening Fu, Sergey M. Plis, Vince D. Calhoun:
Mind the gap: functional network connectivity interpolation between schizophrenia patients and controls using a variational autoencoder. EMBC 2022: 1477-1480
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Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun:
A Model Visualization-based Approach for Insight into Waveforms and Spectra Learned by CNNs. EMBC 2022: 1643-1646
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Anees Abrol, Vince D. Calhoun:
Discovery and Replication of Time-Resolved Functional Network Connectivity Differences in Adolescence and Adulthood in over 50K fMRI Datasets. EMBC 2022: 1855-1858
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Weizheng Yan, Zening Fu, Jing Sui, Vince D. Calhoun:
'Harmless' adversarial network harmonization approach for removing site effects and improving reproducibility in neuroimaging studies. EMBC 2022: 1859-1862
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Marlena Duda, Armin Iraji, Vince D. Calhoun:
Spatially Constrained ICA Enables Robust Detection of Schizophrenia from Very Short Resting-state fMRI. EMBC 2022: 1867-1870
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Anees Abrol, Ihab Hajjar, Vince D. Calhoun:
Probing the link between the APOE-ε4 allele and whole-brain gray matter using deep learning. EMBC 2022: 3506-3509
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Poomipat Boonyakitanont, Ben Gabrielson, Irina Belyaeva, Parthan Olikkal, Jitkomut Songsiri, Yu-Ping Wang, Tony W. Wilson, Vince D. Calhoun, Julia M. Stephen, Tülay Adali:
An ICA-based framework for joint analysis of cognitive scores and MEG event-related fields. EMBC 2022: 3594-3598
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Oktay Agcaoglu, Tony W. Wilson, Yu-Ping Wang, Julia M. Stephen, Vince D. Calhoun:
Longitudinal Changes in Resting State FMRI Spectra in Children. EMBC 2022: 3729-3732
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  - conf/embc/KazemivashC22
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Behnam Kazemivash, Vince D. Calhoun:
A 5D approach to study spatio-temporal dynamism of resting-state brain networks in schizophrenia. EMBC 2022: 3737-3740
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  - conf/embc/SendiMSC22
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Mohammad S. Eslampanah Sendi, Robyn L. Miller, David H. Salat, Vince D. Calhoun:
A two-step clustering-based pipeline for big dynamic functional network connectivity data. EMBC 2022: 3741-3744
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Yuda Bi, Anees Abrol, Zening Fu, Vince D. Calhoun:
Deep Learning Prediction and Visualization of Gender Related Brain Changes from Longitudinal Structural MRI Data in the ABCD Study. EMBC 2022: 3814-3817
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Ishaan Batta, Anees Abrol, Zening Fu, Vince D. Calhoun:
Learning Active Multimodal Subspaces in the Brain. EMBC 2022: 3822-3825
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Charles A. Ellis, Mohammad S. Eslampanah Sendi, Robyn L. Miller, Vince D. Calhoun:
An Unsupervised Feature Learning Approach for Elucidating Hidden Dynamics in rs-fMRI Functional Network Connectivity. EMBC 2022: 4449-4452
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Ashkan Faghiri, Armin Iraji, Marlena Duda, Tülay Adali, Vince D. Calhoun:
A Unified Framework for Modularizing and Comparing Time-Resolved Functional Connectivity Methods. EMBC 2022: 4631-4634
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Michael Weeks, Vince D. Calhoun, Robyn L. Miller:
Comparison of Energy Signals from the 4D DWT of Resting State FMRI Data Obtained from a Study on Schizophrenia. EMBC 2022: 4635-4640
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Reihaneh Hassanzadeh, Vince D. Calhoun:
A Supervised Contrastive Learning-based Analysis of rs-tMRI Data Captures Gender Differences in Nonlinear Functional Network Coupling. EMBC 2022: 4641-4644
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Yutong Gao, Vince D. Calhoun, Robyn L. Miller:
Transient Intervals of Significantly Different Whole Brain Connectivity Predict Recovery vs. Progression from Mild Cognitive Impairment: New Insights from Interpretable LSTM Classifiers. EMBC 2022: 4645-4648
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Isabell Lehmann, Evrim Acar, Tanuj Hasija, Mohammad A. B. S. Akhonda, Vince D. Calhoun, Peter J. Schreier, Tülay Adali:
Multi-Task fMRI Data Fusion Using IVA and PARAFAC2. ICASSP 2022: 1466-1470
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Hanlu Yang, Mohammad A. B. S. Akhonda, Fateme Ghayem, Qunfang Long, Vince D. Calhoun, Tülay Adali:
Independent Vector Analysis Based Subgroup Identification from Multisubject fMRI Data. ICASSP 2022: 1471-1475
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Li-Dan Kuang, Biao Wang, Qiu-Hua Lin, Haopeng Zhang, Jianming Zhang, Wenjun Li, Feng Li, Vince D. Calhoun:
An Accelerated Rank-(L, L, 1, 1) Block Term Decomposition Of Multi-Subject Fmri Data Under Spatial Orthonormality Constraint. ICASSP 2022: 3933-3937
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Guang Yang, Arvind Rao, Christine Fernandez-Maloigne, Vince D. Calhoun, Gloria Menegaz:
Explainable AI (XAI) In Biomedical Signal and Image Processing: Promises and Challenges. ICIP 2022: 1531-1535
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Hongkun Yu, Thomas Florian, Vince D. Calhoun, Dong Hye Ye:
Deep Learning From Imaging Genetics for Schizophrenia Classification. ICIP 2022: 3291-3295
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Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis:
Deep Dynamic Effective Connectivity Estimation from Multivariate Time Series. IJCNN 2022: 1-10
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Yaorong Xiao, William Ashbee, Vince D. Calhoun, Sergey M. Plis:
Refacing Defaced MRI with PixelCNN. IJCNN 2022: 1-7
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Ashkan Faghiri, Tülay Adali, Vince D. Calhoun:
Single Sideband Modulation as a Tool To Improve Functional Connectivity Estimation. ISBI 2022: 1-4
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Reihaneh Hassanzadeh, Vince D. Calhoun:
A Contrastive Learning-Based Approach To Measure Spatial Coupling Among Brain Networks: A Schizophrenia Study. ISBI 2022: 1-4
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  - conf/isbi/SahaSBC22
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Debbrata K. Saha, Rogers F. Silva, Bradley T. Baker, Vince D. Calhoun:
Decentralized Spatially Constrained Source-Based Morphometry. ISBI 2022: 1-5
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Rekha Saha, Debbrata K. Saha, Md Abdur Rahaman, Zening Fu, Vince D. Calhoun:
Longitudinal Whole-Brain Functional Network Change Patterns Over A Two-Year Period In The ABCD Data. ISBI 2022: 1-4
[c242]
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Oktay Agcaoglu, Rogers F. Silva, Vince D. Calhoun:
Multimodal fusion of brain imaging data with joint non-linear independent component analysis. IVMSP 2022: 1-5
[c241]
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Ashkan Faghiri, Armin Iraji, Noah Lewis, Kun Yang, Koko Ishizuka, Akira Sawa, Tülay Adali, Vince D. Calhoun:
Going from lines to triangles: A formulation for time-frequency moments of time-series with application to study fMRI. IVMSP 2022: 1-5
[c240]
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  - conf/mlsp/RahamanGIFCC22
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Md Abdur Rahaman, Yash Garg, Armin Iraji, Zening Fu, Jiayu Chen, Vince D. Calhoun:
Two-Dimensional Attentive Fusion for Multi-Modal Learning of Neuroimaging and Genomics Data. MLSP 2022: 1-6
[i39]
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Moo K. Chung, Shih-Gu Huang, Ian C. Carroll, Vince D. Calhoun, H. Hill Goldsmith:
Dynamic Persistent Homology for Brain Networks via Wasserstein Graph Clustering. CoRR abs/2201.00087 (2022)
[i38]
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  - journals/corr/abs-2202-02393
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Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis:
Deep Dynamic Effective Connectivity Estimation from Multivariate Time Series. CoRR abs/2202.02393 (2022)
[i37]
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  - journals/corr/abs-2205-13640
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Eloy Geenjaar, Amrit Kashyap, Noah Lewis, Robyn L. Miller, Vince D. Calhoun:
Spatio-temporally separable non-linear latent factor learning: an application to somatomotor cortex fMRI data. CoRR abs/2205.13640 (2022)
[i36]
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  - journals/corr/abs-2207-04295
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Guang Yang, Arvind Rao, Christine Fernandez-Maloigne, Vince D. Calhoun, Gloria Menegaz:
Explainable AI (XAI) in Biomedical Signal and Image Processing: Promises and Challenges. CoRR abs/2207.04295 (2022)
[i35]
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  - journals/corr/abs-2208-12909
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Xinhui Li, Alex Fedorov, Mrinal Mathur, Anees Abrol, Gregory Kiar, Sergey M. Plis, Vince D. Calhoun:
Pipeline-Invariant Representation Learning for Neuroimaging. CoRR abs/2208.12909 (2022)
[i34]
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  - journals/corr/abs-2209-02876
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Alex Fedorov, Eloy Geenjaar, Lei Wu, Tristan Sylvain, Thomas P. DeRamus, Margaux Luck, Maria B. Misiura, R. Devon Hjelm, Sergey M. Plis, Vince D. Calhoun:
Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes. CoRR abs/2209.02876 (2022)
[i33]
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  - journals/corr/abs-2210-03667
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  - https://dblp.org/rec/journals/corr/abs-2210-03667
Eloy Geenjaar, Noah Lewis, Amrit Kashyap, Robyn L. Miller, Vince D. Calhoun:
CommsVAE: Learning the brain's macroscale communication dynamics using coupled sequential VAEs. CoRR abs/2210.03667 (2022)
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Fateme Ghayem, Hanlu Yang, Furkan Kantar, Seung-Jun Kim, Vince D. Calhoun, Tülay Adali:
New Interpretable Patterns and Discriminative Features from Brain Functional Network Connectivity Using Dictionary Learning. CoRR abs/2211.07374 (2022)
2021
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Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis:
A Deep Learning Model for Data-Driven Discovery of Functional Connectivity. Algorithms 14(3): 75 (2021)
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Debbrata K. Saha, Eswar Damaraju, Barnaly Rashid, Anees Abrol, Sergey M. Plis, Vince D. Calhoun:
A Classification-Based Approach to Estimate the Number of Resting Functional Magnetic Resonance Imaging Dynamic Functional Connectivity States. Brain Connect. 11(2): 132-145 (2021)
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Kaicheng Li, Zening Fu, Xiao Luo, Qingze Zeng, Peiyu Huang, Minming Zhang, Vince D. Calhoun:
The Influence of Cerebral Small Vessel Disease on Static and Dynamic Functional Network Connectivity in Subjects Along Alzheimer's Disease Continuum. Brain Connect. 11(3): 189-200 (2021)
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Qunfang Long, Suchita Bhinge, Vince D. Calhoun, Tülay Adali:
Relationship between Dynamic Blood-Oxygen-Level-Dependent Activity and Functional Network Connectivity: Characterization of Schizophrenia Subgroups. Brain Connect. 11(6): 430-446 (2021)
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Mohammad S. Eslampanah Sendi, Elaheh Zendehrouh, Jing Sui, Zening Fu, Dongmei Zhi, Luxian Lv, Xiaohong Ma, Qing Ke, Xianbin Li, Chuanyue Wang, Christopher C. Abbott, Jessica A. Turner, Robyn L. Miller, Vince D. Calhoun:
Abnormal Dynamic Functional Network Connectivity Estimated from Default Mode Network Predicts Symptom Severity in Major Depressive Disorder. Brain Connect. 11(10): 838-849 (2021)
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Li Zhang, Zening Fu, Wenwen Zhang, Gan Huang, Zhen Liang, Linling Li, Bharat B. Biswal, Vince D. Calhoun, Zhiguo Zhang:
Accessing dynamic functional connectivity using l0-regularized sparse-smooth inverse covariance estimation from fMRI. Neurocomputing 443: 147-161 (2021)
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Chen Qiao, Xin-Yu Hu, Li Xiao, Vince D. Calhoun, Yu-Ping Wang:
A deep autoencoder with sparse and graph Laplacian regularization for characterizing dynamic functional connectivity during brain development. Neurocomputing 456: 97-108 (2021)
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Zening Fu, Armin Iraji, Jessica A. Turner, Jing Sui, Robyn L. Miller, Godfrey D. Pearlson, Vince D. Calhoun:
Dynamic state with covarying brain activity-connectivity: On the pathophysiology of schizophrenia. NeuroImage 224: 117385 (2021)
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Julia M. Stephen, Isabel Solis, J. Janowich, M. Stern, Michaela R. Frenzel, Jacob A. Eastman, Mackenzie S. Mills, Christine M. Embury, N. M. Coolidge, Elizabeth Heinrichs-Graham, Andy R. Mayer, Jingyu Liu, Yu-Ping Wang, Tony W. Wilson, Vince D. Calhoun:
The Developmental Chronnecto-Genomics (Dev-CoG) study: A multimodal study on the developing brain. NeuroImage 225: 117438 (2021)
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Chun Siong Soon, Ksenia Vinogradova, Ju Lynn Ong, Vince D. Calhoun, Thomas Liu, Juan Helen Zhou, Kwun Kei Ng, Michael W. L. Chee:
Respiratory, cardiac, EEG, BOLD signals and functional connectivity over multiple microsleep episodes. NeuroImage 237: 118129 (2021)
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Lei Wu, Arvind Caprihan, Vince D. Calhoun:
Tracking spatial dynamics of functional connectivity during a task. NeuroImage 239: 118310 (2021)
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Steve C. N. Hui, Mark Mikkelsen, Helge J. Zöllner, Vishwadeep Ahluwalia, Sarael Alcauter, Laima Baltusis, Deborah A. Barany, Laura R. Barlow, Robert Becker, Jeffrey I. Berman, Adam Berrington, Pallab K. Bhattacharyya, Jakob Udby Blicher, Wolfgang Bogner, Mark S. Brown, Vince D. Calhoun, Ryan Castillo, Kim M. Cecil, Richard A. E. Edden, Yeo Bi Choi, Winnie C. W. Chu, William T. Clarke, Alexander R. Craven, Koen Cuypers, Michael Dacko, Camilo de la Fuente-Sandoval, Patricia Desmond, Aleksandra Domagalik, Julien Dumont, Niall W. Duncan, Ulrike Dydak, Katherine Dyke, David A. Edmondson, Gabriele Ende, Lars Ersland, C. John Evans, Alan S. R. Fermin, Antonio Ferretti, Ariane Fillmer, Tao Gong, Ian Greenhouse, James T. Grist, Meng Gu, Ashley D. Harris, Katarzyna Hat, Stefanie Heba, Eva Heckova, John P. Hegarty, Kirstin-Friederike Heise, Shiori Honda, Aaron Jacobson, Jacobus F. A. Jansen, Christopher W. Jenkins, Stephen J. Johnston, Christoph Juchem, Alayar Kangarlu, Adam B. Kerr, Karl Landheer, Thomas Lange, Phil Lee, Swati Rane Levendovszky, Catherine Limperopoulos, Feng Liu, William Lloyd, David J. Lythgoe, Maro G. Machizawa, Erin L. MacMillan, Richard J. Maddock, Andrei V. Manzhurtsev, María L. Martinez-Gudino, Jack J. Miller, Heline Mirzakhanian, Marta Moreno-Ortega, Paul G. Mullins, Shinichiro Nakajima, Jamie Near, Ralph Noeske, Wibeke Nordhøy, Georg Oeltzschner, Raul Osorio-Duran, María Concepción García Otaduy, Erick H. Pasaye, Ronald Peeters, Scott J. Peltier, Ulrich Pilatus, Nenad Polomac, Eric C. Porges, Subechhya Pradhan, James Joseph Prisciandaro, Nicolaas A. Puts, Caroline D. Rae, Francisco Reyes-Madrigal, Timothy P. L. Roberts, Caroline E. Robertson, Jens T. Rosenberg, Diana-Georgiana Rotaru, Ruth L. O'Gorman Tuura, Muhammad G. Saleh, Kristian Sandberg, Ryan Sangill, Keith Schembri, Anouk Schrantee, Natalia A. Semenova, Debra Singel, Rouslan Sitnikov, Jolinda Smith, Yulu Song, Craig E. L. Stark, Diederick Stoffers, Stephan P. Swinnen, Rongwen Tain, Costin Tanase, Sofie Tapper, Martin Tegenthoff, Thomas Thiel, Marc Thioux, Peter Truong, Pim van Dijk, Nolan Vella, Rishma Vidyasagar, Andrej Vovk, Guangbin Wang, Lars T. Westlye, Timothy K. Wilbur, William R. Willoughby, Martin Wilson, Hans-Jörg Wittsack, Adam J. Woods, Yen-Chien Wu, Junqian Xu, Maria Yanez Lopez, David Ka Wai Yeung, Qun Zhao, Xiaopeng Zhou, Gasper Zupan:
Frequency drift in MR spectroscopy at 3T. NeuroImage 241: 118430 (2021)
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Kurt G. Schilling, François Rheault, Laurent Petit, Colin B. Hansen, Vishwesh Nath, Fang-Cheng Yeh, Gabriel Girard, Muhamed Barakovic, Jonathan Rafael-Patino, Thomas Yu, Elda Fischi Gomez, Marco Pizzolato, Mario Ocampo-Pineda, Simona Schiavi, Erick Jorge Canales-Rodríguez, Alessandro Daducci, Cristina Granziera, Giorgio M. Innocenti, Jean-Philippe Thiran, Laura Mancini, Stephen J. Wastling, Sirio Cocozza, Maria Petracca, Giuseppe Pontillo, Matteo Mancini, Sjoerd B. Vos, Vejay N. Vakharia, John S. Duncan, Helena Melero, Lidia Manzanedo, Emilio Sanz-Morales, Ángel Peña-Melián, Fernando Calamante, Arnaud Attye, Ryan P. Cabeen, Laura Korobova, Arthur W. Toga, Anupa Ambili Vijayakumari, Drew Parker, Ragini Verma, Ahmed M. Radwan, Stefan Sunaert, Louise Emsell, Alberto De Luca, Alexander Leemans, Claude J. Bajada, Hamied A. Haroon, Hojjatollah Azadbakht, Maxime Chamberland, Sila Genc, Chantal M. W. Tax, Ping Hong Yeh, Rujirutana Srikanchana, Colin D. Mcknight, Joseph Yuan-Mou Yang, Jian Chen, Claire E. Kelly, Chun-Hung Yeh, Jérôme Cochereau, Jerome J. Maller, Thomas Welton, Fabien Almairac, Kiran K. Seunarine, Chris A. Clark, Fan Zhang, Nikos Makris, Alexandra J. Golby, Yogesh Rathi, Lauren J. O'Donnell, Yihao Xia, Dogu Baran Aydogan, Yonggang Shi, Francisco Guerreiro Fernandes, Mathijs Raemaekers, Shaun Warrington, Stijn Michielse, Alonso Ramirez-Manzanares, Luis Concha, Ramón Aranda, Mariano Rivera Meraz, Garikoitz Lerma-Usabiaga, Lucas Roitman, Lucius S. Fekonja, Navona Calarco, Michael Joseph, Hajer Nakua, Aristotle N. Voineskos, Philippe Karan, Gabrielle Grenier, Jon Haitz Legarreta, Nagesh Adluru, Veena A. Nair, Vivek Prabhakaran, Andrew L. Alexander, Koji Kamagata, Yuya Saito, Wataru Uchida, Christina Andica, Masahiro Abe, Roza G. Bayrak, Claudia A. M. Gandini Wheeler-Kingshott, Egidio D'Angelo, Fulvia Palesi, Giovanni Savini, Nicolò Rolandi, Pamela Guevara, Josselin Houenou, Narciso López-López, Jean-François Mangin, Cyril Poupon, Claudio Román, Andrea Vázquez, Chiara Maffei, Mavilde Arantes, José Paulo Andrade, Susana Maria Silva, Vince D. Calhoun, Eduardo Caverzasi, Simone Sacco, Michael Lauricella, Franco Pestilli, Daniel Bullock, Yang Zhan, Edith Brignoni-Pérez, Catherine Lebel, Jess E. Reynolds, Igor Nestrasil, René Labounek, Christophe Lenglet, Amy Paulson, Stefania Aulicka, Sarah R. Heilbronner, Katja Heuer, Bramsh Qamar Chandio, Javier Guaje, Wei Tang, Eleftherios Garyfallidis, Rajikha Raja, Adam W. Anderson, Bennett A. Landman, Maxime Descoteaux:
Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset? NeuroImage 243: 118502 (2021)
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Lauren R. Ott, Samantha H. Penhale, Brittany K. Taylor, Brandon J. Lew, Yu-Ping Wang, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson:
Spontaneous cortical MEG activity undergoes unique age- and sex-related changes during the transition to adolescence. NeuroImage 244: 118552 (2021)
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Harshvardhan Gazula, Bharath Holla, Zuo Zhang, Jiayuan Xu, Eric Verner, Ross Kelly, Sanjeev Jain, Rose Dawn Bharath, Gareth J. Barker, Debasish Basu, Amit Chakrabarti, Kartik Kalyanram, Kalyanaraman Kumaran, Rajkumar Lenin Singh, Rebecca Kuriyan, Pratima Murthy, Vivek Benega, Sergey M. Plis, Anand D. Sarwate, Jessica A. Turner, Gunter Schumann, Vince D. Calhoun:
Decentralized Multisite VBM Analysis During Adolescence Shows Structural Changes Linked to Age, Body Mass Index, and Smoking: a COINSTAC Analysis. Neuroinformatics 19(4): 553-566 (2021)
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Chen Qiao, Lan Yang, Vince D. Calhoun, Zong-Ben Xu, Yu-Ping Wang:
Sparse deep dictionary learning identifies differences of time-varying functional connectivity in brain neuro-developmental study. Neural Networks 135: 91-104 (2021)
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Li Xiao, Aiying Zhang, Biao Cai, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
Correlation Guided Graph Learning to Estimate Functional Connectivity Patterns From fMRI Data. IEEE Trans. Biomed. Eng. 68(4): 1154-1165 (2021)
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Guixia Pan, Li Xiao, Yuntong Bai, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang:
Multiview Diffusion Map Improves Prediction of Fluid Intelligence With Two Paradigms of fMRI Analysis. IEEE Trans. Biomed. Eng. 68(8): 2529-2539 (2021)
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Gang Qu, Li Xiao, Wenxing Hu, Junqi Wang, Kun Zhang, Vince D. Calhoun, Yu-Ping Wang:
Ensemble Manifold Regularized Multi-Modal Graph Convolutional Network for Cognitive Ability Prediction. IEEE Trans. Biomed. Eng. 68(12): 3564-3573 (2021)
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Aiying Zhang, Jian Fang, Wenxing Hu, Vince D. Calhoun, Yu-Ping Wang:
A Latent Gaussian Copula Model for Mixed Data Analysis in Brain Imaging Genetics. IEEE ACM Trans. Comput. Biol. Bioinform. 18(4): 1350-1360 (2021)
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Rogers F. Silva, Sergey M. Plis, Tülay Adali, Marios S. Pattichis, Vince D. Calhoun:
Multidataset Independent Subspace Analysis With Application to Multimodal Fusion. IEEE Trans. Image Process. 30: 588-602 (2021)
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Yipu Zhang, Li Xiao, Gemeng Zhang, Biao Cai, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
Multi-Paradigm fMRI Fusion via Sparse Tensor Decomposition in Brain Functional Connectivity Study. IEEE J. Biomed. Health Informatics 25(5): 1712-1723 (2021)
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Yuntong Bai, Yun Gong, Jianchao Bai, Jingyu Liu, Hong-Wen Deng, Vince D. Calhoun, Yu-Ping Wang:
A Joint Analysis of Multi-Paradigm fMRI Data With Its Application to Cognitive Study. IEEE Trans. Medical Imaging 40(3): 951-962 (2021)
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Wenxing Hu, Xianghe Meng, Yuntong Bai, Aiying Zhang, Gang Qu, Biao Cai, Gemeng Zhang, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang:
Interpretable Multimodal Fusion Networks Reveal Mechanisms of Brain Cognition. IEEE Trans. Medical Imaging 40(5): 1474-1483 (2021)
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Hafiz Imtiaz, Jafar Mohammadi, Rogers F. Silva, Bradley T. Baker, Sergey M. Plis, Anand D. Sarwate, Vince D. Calhoun:
A Correlated Noise-Assisted Decentralized Differentially Private Estimation Protocol, and its Application to fMRI Source Separation. IEEE Trans. Signal Process. 69: 6355-6370 (2021)
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  - conf/bibe/BostamiCHV21
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Biozid Bostami, Vince D. Calhoun, Harm J. van der Horn, Victor M. Vergara:
Harmonization of Multi-site Dynamic Functional Connectivity Network Data. BIBE 2021: 1-4
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Thomas DeRamus, Armin Iraji, Zening Fu, Rogers F. Silva, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang, Yuhui Du, Jingyu Liu, Vince D. Calhoun:
Stability of functional network connectivity (FNC) values across multiple spatial normalization pipelines in spatially constrained independent component analysis. BIBE 2021: 1-6
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Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun:
A Novel Local Explainability Approach for Spectral Insight into Raw EEG-based Deep Learning Classifiers. BIBE 2021: 1-6
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Charles A. Ellis, Rongen Zhang, Vince D. Calhoun, Darwin A. Carbajal, Robyn L. Miller, May D. Wang:
A Gradient-based Approach for Explaining Multimodal Deep Learning Classifiers. BIBE 2021: 1-6
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Charles A. Ellis, Rongen Zhang, Vince D. Calhoun, Darwin A. Carbajal, Mohammad S. Eslampanah Sendi, May D. Wang, Robyn L. Miller:
A Novel Local Ablation Approach for Explaining Multimodal Classifiers. BIBE 2021: 1-6
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Mustafa S. Salman, Eric Verner, Henry Jeremy Bockholt, Zening Fu, Vince D. Calhoun:
Machine Learning Predicts Treatment Response in Bipolar & Major Depression Disorders. BIBE 2021: 1-6
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Eloy Geenjaar, Tonya White, Vince D. Calhoun:
Variational voxelwise rs-fMRI representation learning: Evaluation of sex, age, and neuropsychiatric signatures. BIBM 2021: 1733-1740
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Bishal Thapaliya, Vince D. Calhoun, Jingyu Liu:
Environmental and genome-wide association study on children anxiety and depression. BIBM 2021: 2330-2337
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Charles A. Ellis, Mohammad S. Eslampanah Sendi, Robyn L. Miller, Vince D. Calhoun:
A Novel Activation Maximization-based Approach for Insight into Electrophysiology Classifiers. BIBM 2021: 3358-3365
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  - conf/bibm/FarahdelTSRC021
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Britny Farahdel, Bishal Thapaliya, Pranav Suresh, Bhaskar Ray, Vince D. Calhoun, Jingyu Liu:
Confirmatory Factor Analysis on Mental Health Status using ABCD Cohort. BIBM 2021: 3540-3547
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Victor M. Vergara, Farshad Rafiei, Martijn E. Wokke, Hakwan Lau, Dobromir Rahnev, Vince D. Calhoun:
Evidence for Transcranial Magnetic Stimulation Induced Functional Connectivity Oscillations in the Brain. EMBC 2021: 1407-1411
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Dongmei Zhi, Vince D. Calhoun, Chuanyue Wang, Xianbin Li, Xiaohong Ma, Luxian Lv, Weizheng Yan, Dongren Yao, Shile Qi, Rongtao Jiang, Jianlong Zhao, Xiao Yang, Zheng Lin, Yujin Zhang, Young Chul Chung, Chuanjun Zhuo, Jing Sui:
BNCPL: Brain-Network-based Convolutional Prototype Learning for Discriminating Depressive Disorders. EMBC 2021: 1622-1626
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Mohammad S. Eslampanah Sendi, David H. Salat, Vince D. Calhoun:
Brain age gap difference between healthy and mild dementia subjects: Functional network connectivity analysis. EMBC 2021: 1636-1639
[c226]
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Mohammad S. Eslampanah Sendi, Elaheh Zendehrouh, Jessica A. Turner, Vince D. Calhoun:
Dynamic patterns within the default mode network in schizophrenia subgroups. EMBC 2021: 1640-1643
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  - conf/embc/RahamanRGTC21
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Md Abdur Rahaman, Amanda Rodrigue, David C. Glahn, Jessica A. Turner, Vince D. Calhoun:
Shared sets of correlated polygenic risk scores and voxel-wise grey matter across multiple traits identified via bi-clustering. EMBC 2021: 2201-2206
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Charles A. Ellis, Rongen Zhang, Darwin A. Carbajal, Robyn L. Miller, Vince D. Calhoun, May D. Wang:
Explainable Sleep Stage Classification with Multimodal Electrophysiology Time-series^*. EMBC 2021: 2363-2366
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  - conf/embc/MillerVC21
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Robyn L. Miller, Victor M. Vergara, Vince D. Calhoun:
Multiframe Evolving Dynamic Functional Network Connectivity Motifs (Evodfncs) from Continuity-Preserving Planar Embedding. EMBC 2021: 3066-3069
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Robyn L. Miller, Victor M. Vergara, Vince D. Calhoun:
A Method for Integrative Analysis of Local and Global Brain Dynamics. EMBC 2021: 3189-3192
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Yuhui Du, Hui Hao, Ying Xing, Ju Niu, Vince D. Calhoun:
A Transdiagnostic Biotype Detection Method for Schizophrenia and Autism Spectrum Disorder Based on Graph Kernel. EMBC 2021: 3241-3244
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Yuhui Du, Xingyu He, Vince D. Calhoun:
SMART (splitting-merging assisted reliable) Independent Component Analysis for Brain Functional Networks. EMBC 2021: 3263-3266
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  - conf/embc/RahamanCFLIC21
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Md Abdur Rahaman, Jiayu Chen, Zening Fu, Noah Lewis, Armin Iraji, Vince D. Calhoun:
Multi-modal deep learning of functional and structural neuroimaging and genomic data to predict mental illness. EMBC 2021: 3267-3272
[c218]
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  - conf/embc/GeenjaarLFVPC21
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Eloy Geenjaar, Noah Lewis, Zening Fu, Rohan Venkatdas, Sergey M. Plis, Vince D. Calhoun:
Fusing multimodal neuroimaging data with a variational autoencoder. EMBC 2021: 3630-3633
[c217]
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  - conf/embc/BasodiRRGLVC21
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Sunitha Basodi, Rajikha Raja, Bhaskar Ray, Harshvardhan Gazula, Jingyu Liu, Eric Verner, Vince D. Calhoun:
Federation of Brain Age Estimation in Structural Neuroimaging Data. EMBC 2021: 3854-3857
[c216]
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  - conf/embc/RayDCFSJCL21
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Bhaskar Ray, Kuaikuai Duan, Jiayu Chen, Zening Fu, Pranav Suresh, Sarah Johnson, Vince D. Calhoun, Jingyu Liu:
Multimodal Brain Age Prediction with Feature Selection and Comparison. EMBC 2021: 3858-3864
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Eswar Damaraju, Rogers F. Silva, Tülay Adali, Vince D. Calhoun:
A multimodal IVA fusion approach to identify linked neuroimaging markers. EMBC 2021: 3928-3932
[c214]
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Ishaan Batta, Anees Abrol, Vince D. Calhoun:
Uncovering Active Structural Subspaces Associated with Changes in Indicators for Alzheimer's Disease. EMBC 2021: 3948-3951
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  - conf/embc/AbrolHPC21
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Anees Abrol, Reihaneh Hassanzadeh, Sergey M. Plis, Vince D. Calhoun:
Deep learning in resting-state fMRI^*. EMBC 2021: 3965-3969
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  - conf/embc/LuoLYCSS21
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Na Luo, Xiangsheng Luo, Dongren Yao, Vince D. Calhoun, Li Sun, Jing Sui:
Investigating ADHD subtypes in children using temporal dynamics of the electroencephalogram (EEG) microstates ^*. EMBC 2021: 4358-4361
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  - conf/icassp/SongQLZLC21
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Jia-Yang Song, Miao-Ying Qi, Dun-Pei Lv, Chao-Ying Zhang, Qiu-Hua Lin, Vince D. Calhoun:
Sparse Representation of Complex-Valued fMRI Data Based on Hard Thresholding of Spatial Source Phase. ICASSP 2021: 1105-1109
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Yue Han, Qiu-Hua Lin, Li-Dan Kuang, Xiao-Feng Gong, Fengyu Cong, Vince D. Calhoun:
Tucker Decomposition for Extracting Shared and Individual Spatial Maps from Multi-Subject Resting-State fMRI Data. ICASSP 2021: 1110-1114
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  - conf/ichi/FedorovSGLWDKBC21
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Alex Fedorov, Tristan Sylvain, Eloy Geenjaar, Margaux Luck, Lei Wu, Thomas P. DeRamus, Alex Kirilin, Dmitry Bleklov, Vince D. Calhoun, Sergey M. Plis:
Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease. ICHI 2021: 23-30
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Noah Lewis, Robyn L. Miller, Harshvardhan Gazula, Md Mahfuzur Rahman, Armin Iraji, Vince D. Calhoun, Sergey M. Plis:
Can recurrent models know more than we do? ICHI 2021: 243-247
[c207]
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  - conf/iconip/LiZKHLLC21
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Wei-Xing Li, Chao-Ying Zhang, Li-Dan Kuang, Yue Han, Huan-Jie Li, Qiu-Hua Lin, Vince D. Calhoun:
Marginal Spectrum Modulated Hilbert-Huang Transform: Application to Time Courses Extracted by Independent Vector Analysis of Resting-State fMRI Data. ICONIP (6) 2021: 299-306
[c206]
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Yan-Wei Niu, Chao-Ying Zhang, Yue Qiu, Qiu-Hua Lin, Jing Sui, Vince D. Calhoun:
Fusion of Multiple Spatial Networks Derived from Complex-Valued fMRI Data via CNN Classification. IJCNN 2021: 1-6
[c205]
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  - conf/isbi/ZhaoYXZJJCS21
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Min Zhao, Weizheng Yan, Rongtao Xu, Dongmei Zhi, Rongtao Jiang, Tianzi Jiang, Vince D. Calhoun, Jing Sui:
An Attention-Based Hybrid Deep Learning Framework Integrating Temporal Coherence And Dynamics For Discriminating Schizophrenia. ISBI 2021: 118-121
[c204]
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  - conf/isbi/DuNC21
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Yuhui Du, Ju Niu, Vince D. Calhoun:
A New Hypergraph Clustering Method For Exploring Transdiagnostic Biotypes In Mental Illnesses: Application To Schizophrenia And Psychotic Bipolar Disorder. ISBI 2021: 971-974
[c203]
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Ishaan Batta, Anees Abrol, Zening Fu, Vince D. Calhoun:
A Multimodal Learning Framework to Study Varying Information Complexity in Structural and Functional Sub-Domains in Schizophrenia. ISBI 2021: 994-998
[c202]
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Alex Fedorov, Lei Wu, Tristan Sylvain, Margaux Luck, Thomas P. DeRamus, Dmitry Bleklov, Sergey M. Plis, Vince D. Calhoun:
On Self-Supervised Multimodal Representation Learning: An Application To Alzheimer's Disease. ISBI 2021: 1548-1552
[c201]
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  - conf/isbi/QiPMSVJZSC21
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Shile Qi, Sergey M. Plis, Robyn L. Miller, Rogers F. Silva, Victor M. Vergara, Rongtao Jiang, Dongmei Zhi, Jing Sui, Vince D. Calhoun:
3-way Parallel Fusion of Spatial (sMRI/dMRI) and Spatio-temporal (fMRI) Data with Application to Schizophrenia. ISBI 2021: 1577-1581
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Yuhui Du, Xingyu He, Vince D. Calhoun:
A New Semi-Supervised Non-Negative Matrix Factorization Method For Brain Dynamic Functional Connectivity Analysis. ISBI 2021: 1591-1594
[c199]
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  - conf/isbi/RahamanDSCP21
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Md Abdur Rahaman, Eswar Damaraju, Debbrata Kumar Saha, Vince D. Calhoun, Sergey M. Plis:
Statelets: A Novel Multi-Dimensional State-Shape Representation Of Brain Functional Connectivity Dynamics. ISBI 2021: 1822-1826
[i31]
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  - journals/corr/abs-2101-08316
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Gang Qu, Li Xiao, Wenxing Hu, Kun Zhang, Vince D. Calhoun, Yu-Ping Wang:
Ensemble manifold based regularized multi-modal graph convolutional network for cognitive ability prediction. CoRR abs/2101.08316 (2021)
[i30]
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  - journals/corr/abs-2102-09631
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Bradley T. Baker, Vince D. Calhoun, Barak A. Pearlmutter, Sergey M. Plis:
Efficient Distributed Auto-Differentiation. CoRR abs/2102.09631 (2021)
[i29]
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  - journals/corr/abs-2103-15914
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Alex Fedorov, Eloy Geenjaar, Lei Wu, Thomas P. DeRamus, Vince D. Calhoun, Sergey M. Plis:
Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data. CoRR abs/2103.15914 (2021)
[i28]
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  - journals/corr/abs-2105-01128
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Eloy Geenjaar, Noah Lewis, Zening Fu, Rohan Venkatdas, Sergey M. Plis, Vince D. Calhoun:
Fusing multimodal neuroimaging data with a variational autoencoder. CoRR abs/2105.01128 (2021)
[i27]
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  - journals/corr/abs-2105-08053
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Charles A. Ellis, Mohammad S. Eslampanah Sendi, Sergey M. Plis, Robyn L. Miller, Vince D. Calhoun:
Algorithm-Agnostic Explainability for Unsupervised Clustering. CoRR abs/2105.08053 (2021)
[i26]
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  - journals/corr/abs-2108-12756
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Eloy Geenjaar, Tonya White, Vince D. Calhoun:
Variational voxelwise rs-fMRI representation learning: Evaluation of sex, age, and neuropsychiatric signatures. CoRR abs/2108.12756 (2021)
[i25]
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  - journals/corr/abs-2111-01271
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Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis:
Brain dynamics via Cumulative Auto-Regressive Self-Attention. CoRR abs/2111.01271 (2021)
[i24]
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  - journals/corr/abs-2111-01276
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Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis:
Multi network InfoMax: A pre-training method involving graph convolutional networks. CoRR abs/2111.01276 (2021)
[i23]
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  - journals/corr/abs-2112-04013
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Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis:
A deep learning model for data-driven discovery of functional connectivity. CoRR abs/2112.04013 (2021)
2020
[j228]
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  - journals/access/LiWHZPCW20
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Gang Li, Chao Wang, Depeng Han, Yipu Zhang, Peng Peng, Vince D. Calhoun, Yu-Ping Wang:
Deep Principal Correlated Auto-Encoders With Application to Imaging and Genomics Data Integration. IEEE Access 8: 20093-20107 (2020)
[j227]
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  - journals/brain/ClarkTCBBT20
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Sarah V. Clark, Amber Tannahill, Vince D. Calhoun, Jessica A. Bernard, Juan R. Bustillo, Jessica A. Turner:
Weaker Cerebellocortical Connectivity Within Sensorimotor and Executive Networks in Schizophrenia Compared to Healthy Controls: Relationships with Processing Speed. Brain Connect. 10(9): 490-503 (2020)
[j226]
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  - journals/brain/AgcaogluWWSC20
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Oktay Agcaoglu, Tony W. Wilson, Yu-Ping Wang, Julia M. Stephen, Vince D. Calhoun:
Dynamic Resting-State Connectivity Differences in Eyes Open Versus Eyes Closed Conditions. Brain Connect. 10(9): 504-519 (2020)
[j225]
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  - journals/cmpb/LiHWHCW20
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Gang Li, Depeng Han, Chao Wang, Wenxing Hu, Vince D. Calhoun, Yu-Ping Wang:
Application of deep canonically correlated sparse autoencoder for the classification of schizophrenia. Comput. Methods Programs Biomed. 183 (2020)
[j224]
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  - journals/ijon/QiaoSDCW20
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Chen Qiao, Yan Shi, Yu-Xian Diao, Vince D. Calhoun, Yu-Ping Wang:
Log-sum enhanced sparse deep neural network. Neurocomputing 407: 206-220 (2020)
[j223]
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  - journals/jossw/GazulaKRVBSISRT20
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Harshvardhan Gazula, Ross Kelly, Javier Tomas Romero, Eric Verner, Bradley T. Baker, Rogers F. Silva, Hafiz Imtiaz, Debbrata K. Saha, Rajikha Raja, Jessica A. Turner, Anand D. Sarwate, Sergey M. Plis, Vince D. Calhoun:
COINSTAC: Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation. J. Open Source Softw. 5(54): 2166 (2020)
[j222]
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  - journals/jstsp/BhingeLCA20
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Suchita Bhinge, Qunfang Long, Vince D. Calhoun, Tülay Adali:
Adaptive Constrained Independent Vector Analysis: An Effective Solution for Analysis of Large-Scale Medical Imaging Data. IEEE J. Sel. Top. Signal Process. 14(6): 1255-1264 (2020)
[j221]
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  - journals/neuroimage/JiangZFQZZXFBTC20
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Rongtao Jiang, Nianming Zuo, Judith M. Ford, Shile Qi, Dongmei Zhi, Chuanjun Zhuo, Yong Xu, Zening Fu, Juan R. Bustillo, Jessica A. Turner, Vince D. Calhoun, Jing Sui:
Task-induced brain connectivity promotes the detection of individual differences in brain-behavior relationships. NeuroImage 207 (2020)
[j220]
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  - journals/neuroimage/ColenbierSUPCM20
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Nigel Colenbier, Frederik Van de Steen, Lucina Q. Uddin, Russell A. Poldrack, Vince D. Calhoun, Daniele Marinazzo:
Disambiguating the role of blood flow and global signal with partial information decomposition. NeuroImage 213: 116699 (2020)
[j219]
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  - journals/neuroimage/LongBCA20
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Qunfang Long, Suchita Bhinge, Vince D. Calhoun, Tülay Adali:
Independent vector analysis for common subspace analysis: Application to multi-subject fMRI data yields meaningful subgroups of schizophrenia. NeuroImage 216: 116872 (2020)
[j218]
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  - journals/neuroimage/MoriokaCH20
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Hiroshi Morioka, Vince D. Calhoun, Aapo Hyvärinen:
Nonlinear ICA of fMRI reveals primitive temporal structures linked to rest, task, and behavioral traits. NeuroImage 218: 116989 (2020)
[j217]
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  - journals/neuroimage/DamarajuTLC20
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Eswar Damaraju, Enzo Tagliazucchi, Helmut Laufs, Vince D. Calhoun:
Connectivity dynamics from wakefulness to sleep. NeuroImage 220: 117047 (2020)
[j216]
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  - journals/neuroimage/ZhouCZZCW20
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Zhongxing Zhou, Biao Cai, Gemeng Zhang, Aiying Zhang, Vince D. Calhoun, Yu-Ping Wang:
Prediction and classification of sleep quality based on phase synchronization related whole-brain dynamic connectivity using resting state fMRI. NeuroImage 221: 117190 (2020)
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Abraham D. Killanin, Alex I. Wiesman, Elizabeth Heinrichs-Graham, Boman R. Groff, Michaela R. Frenzel, Jacob A. Eastman, Yu-Ping Wang, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson:
Development and sex modulate visuospatial oscillatory dynamics in typically-developing children and adolescents. NeuroImage 221: 117192 (2020)
[j214]
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Md Abdur Rahaman, Daniel H. Mathalon, Hyo Jong Lee, Wenhao Jiang, Bryon A. Mueller, Ole A. Andreassen, Ingrid Agartz, Scott R. Sponheim, Andrew R. Mayer, Julia M. Stephen, Rex E. Jung, Jessica A. Turner, José M. Cañive, Juan R. Bustillo, Vince D. Calhoun, Cota Navin Gupta, Srinivas Rachakonda, Jiayu Chen, Jingyu Liu, Theo G. M. van Erp, Steven G. Potkin, Judith M. Ford:
N-BiC: A Method for Multi-Component and Symptom Biclustering of Structural MRI Data: Application to Schizophrenia. IEEE Trans. Biomed. Eng. 67(1): 110-121 (2020)
[j213]
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Li Xiao, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
A Manifold Regularized Multi-Task Learning Model for IQ Prediction From Two fMRI Paradigms. IEEE Trans. Biomed. Eng. 67(3): 796-806 (2020)
[j212]
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Yuntong Bai, Pascal Zille, Wenxing Hu, Vince D. Calhoun, Yu-Ping Wang:
Biomarker Identification Through Integrating fMRI and Epigenetics. IEEE Trans. Biomed. Eng. 67(4): 1186-1196 (2020)
[j211]
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Haleh Falakshahi, Victor M. Vergara, Jingyu Liu, Daniel H. Mathalon, Judith M. Ford, James Voyvodic, Bryon A. Mueller, Aysenil Belger, Sarah C. McEwen, Steven G. Potkin, Adrian Preda, Hooman Rokham, Jing Sui, Jessica A. Turner, Sergey M. Plis, Vince D. Calhoun:
Meta-Modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia. IEEE Trans. Biomed. Eng. 67(9): 2572-2584 (2020)
[j210]
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Min Wang, Ting-Zhu Huang, Jian Fang, Vince D. Calhoun, Yu-Ping Wang:
Integration of Imaging (epi)Genomics Data for the Study of Schizophrenia Using Group Sparse Joint Nonnegative Matrix Factorization. IEEE ACM Trans. Comput. Biol. Bioinform. 17(5): 1671-1681 (2020)
[j209]
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Inês Domingues, Henning Müller, Andrés Ortiz, Belur V. Dasarathy, Pedro H. Abreu, Vince D. Calhoun:
Guest Editorial: Information Fusion for Medical Data: Early, Late, and Deep Fusion Methods for Multimodal Data. IEEE J. Biomed. Health Informatics 24(1): 14-16 (2020)
[j208]
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Yipu Zhang, Peng Peng, Yongfeng Ju, Gang Li, Vince D. Calhoun, Yu-Ping Wang:
Canonical Correlation Analysis of Imaging Genetics Data Based on Statistical Independence and Structural Sparsity. IEEE J. Biomed. Health Informatics 24(9): 2621-2629 (2020)
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Aiying Zhang, Biao Cai, Wenxing Hu, Bochao Jia, Faming Liang, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang:
Joint Bayesian-Incorporating Estimation of Multiple Gaussian Graphical Models to Study Brain Connectivity Development in Adolescence. IEEE Trans. Medical Imaging 39(2): 357-365 (2020)
[j206]
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Gemeng Zhang, Biao Cai, Aiying Zhang, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
Estimating Dynamic Functional Brain Connectivity With a Sparse Hidden Markov Model. IEEE Trans. Medical Imaging 39(2): 488-498 (2020)
[j205]
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  - journals/tmi/KuangLGCWC20
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Li-Dan Kuang, Qiu-Hua Lin, Xiao-Feng Gong, Fengyu Cong, Yu-Ping Wang, Vince D. Calhoun:
Shift-Invariant Canonical Polyadic Decomposition of Complex-Valued Multi-Subject fMRI Data With a Phase Sparsity Constraint. IEEE Trans. Medical Imaging 39(4): 844-853 (2020)
[j204]
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Li Xiao, Junqi Wang, Peyman Hosseinzajeh Kassani, Yipu Zhang, Yuntong Bai, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
Multi-Hypergraph Learning-Based Brain Functional Connectivity Analysis in fMRI Data. IEEE Trans. Medical Imaging 39(5): 1746-1758 (2020)
[j203]
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Yuntong Bai, Pascal Zille, Vince D. Calhoun, Yu-Ping Wang:
Optimized Combination of Multiple Graphs With Application to the Integration of Brain Imaging and (epi)Genomics Data. IEEE Trans. Medical Imaging 39(6): 1801-1811 (2020)
[j202]
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Peyman Hosseinzadeh Kassani, Li Xiao, Gemeng Zhang, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
Causality-Based Feature Fusion for Brain Neuro-Developmental Analysis. IEEE Trans. Medical Imaging 39(11): 3290-3299 (2020)
[c198]
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Yuhui Du, Bang Li, Yuliang Hou, Vince D. Calhoun:
A deep learning fusion model for brain disorder classification: Application to distinguishing schizophrenia and autism spectrum disorder. BCB 2020: 56:1-56:7
[c197]
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Haleh Falakshahi, Hooman Rokham, Zening Fu, Daniel H. Mathalon, Judith M. Ford, James Voyvodic, Bryon A. Mueller, Aysenil Belger, Sarah C. McEwen, Steven G. Potkin, Adrian Preda, Armin Iraji, Jessica A. Turner, Sergey M. Plis, Vince D. Calhoun:
Time-varying Graphs: A Method to Identify Abnormal Integration and Disconnection in Functional Brain Connectivity with Application to Schizophrenia. BIBE 2020: 417-424
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Mohammad S. Eslampanah Sendi, Ji Ye Chun, Vince D. Calhoun:
Visualizing functional network connectivity difference between middle adult and older subjects using an explainable machine-learning method. BIBE 2020: 955-960
[c195]
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Ishaan Batta, Anees Abrol, Zening Fu, Vince D. Calhoun:
Varying Information Complexity in Functional Domain Interactions in Schizophrenia. BIBE 2020: 1042-1047
[c194]
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  - conf/bibe/HassanzadehC20
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Reihaneh Hassanzadeh, Vince D. Calhoun:
Individualized Prediction of Brain Network Interactions using Deep Siamese Networks. BIBE 2020: 1065-1070
[c193]
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  - conf/bibe/KazemivashC20
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Behnam Kazemivash, Vince D. Calhoun:
BPARC: A novel spatio-temporal (4D) data-driven brain parcellation scheme based on deep residual networks. BIBE 2020: 1071-1076
[c192]
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  - conf/bibm/SalmanWDAC20
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Mustafa S. Salman, Tor D. Wager, Eswar Damaraju, Anees Abrol, Vince D. Calhoun:
Fully automated ordering and labeling of ICA components. BIBM 2020: 1110-1114
[c191]
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  - conf/embc/ChunSSZC20
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Ji Ye Chun, Mohammad S. Eslampanah Sendi, Jing Sui, Dongmei Zhi, Vince D. Calhoun:
Visualizing Functional Network Connectivity Difference between Healthy Control and Major Depressive Disorder Using an Explainable Machine-learning Method. EMBC 2020: 1424-1427
[c190]
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Elaheh Zendehrouh, Mohammad S. Eslampanah Sendi, Jing Sui, Zening Fu, Dongmei Zhi, Luxian Lv, Xiaohong Ma, Qing Ke, Xianbin Li, Chuanyue Wang, Christopher C. Abbott, Jessica A. Turner, Robyn L. Miller, Vince D. Calhoun:
Aberrant Functional Network Connectivity Transition Probability in Major Depressive Disorder. EMBC 2020: 1493-1496
[c189]
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  - conf/embc/DuanCLS20
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Kuaikuai Duan, Vince D. Calhoun, Jingyu Liu, Rogers F. Silva:
aNy-way Independent Component Analysis. EMBC 2020: 1770-1774
[c188]
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  - conf/icassp/RoaldBJCAA20
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Marie Roald, Suchita Bhinge, Chunying Jia, Vince D. Calhoun, Tülay Adali, Evrim Acar:
Tracing Network Evolution Using The Parafac2 Model. ICASSP 2020: 1100-1104
[c187]
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Armin Iraji, Noah Lewis, Ashkan Faghiri, Zening Fu, Thomas DeRamus, Anees Abrol, Shile Qi, Vince D. Calhoun:
Functional Multi-Connectivity: A Novel Approach To Assess Multi-Way Entanglement Between Networks and Voxels. ISBI 2020: 1698-1701
[c186]
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Gemeng Zhang, Aiying Zhang, Vince D. Calhoun, Yu-Ping Wang:
A causal brain network estimation method leveraging Bayesian analysis and the PC algorithm. Biomedical Applications in Molecular, Structural, and Functional Imaging 2020: 113170X
[c185]
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  - conf/mibam/WangSWCW20
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Junqi Wang, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
Graph Laplacian learning based Fourier Transform for brain network analysis with resting state fMRI. Biomedical Applications in Molecular, Structural, and Functional Imaging 2020: 113171G
[c184]
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  - conf/mibam/KassaniCW20
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Peyman Hosseinzadeh Kassani, Vince D. Calhoun, Yu-Ping Wang:
Reduced sine hyperbolic polynomial model for brain neuro-developmental analysis. Biomedical Applications in Molecular, Structural, and Functional Imaging 2020: 1131706
[c183]
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  - conf/mibam/RajaCRC20
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Rajikha Raja, Arvind Caprihan, Gary A. Rosenberg, Vince D. Calhoun:
Identification of dementia subtypes based on a diffusion MRI multi-model approach. Biomedical Applications in Molecular, Structural, and Functional Imaging 2020: 1131709
[c182]
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  - conf/mibam/XiaoSWCW20
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Li Xiao, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
A hypergraph learning method for brain functional connectivity network construction from fMRI data. Biomedical Applications in Molecular, Structural, and Functional Imaging 2020: 1131710
[c181]
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  - conf/mibam/BaiCW20
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Yuntong Bai, Vince D. Calhoun, Yu-Ping Wang:
Integration of multi-task fMRI for cognitive study by structure-enforced collaborative regression. Biomedical Applications in Molecular, Structural, and Functional Imaging 2020: 1131722
[c180]
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  - conf/micad/GaoCS20
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Shuang Gao, Vince D. Calhoun, Jing Sui:
Multi-modal component subspace-similarity-based multi-kernel SVM for schizophrenia classification. Computer-Aided Diagnosis 2020
[c179]
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  - conf/micad/RokhamFC20
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Hooman Rokham, Haleh Falakshahi, Vince D. Calhoun:
A data-driven approach for stratifying psychotic and mood disorders subjects using structural magnitude resonance imaging data. Computer-Aided Diagnosis 2020
[c178]
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  - conf/miccai/MahmoodRFLFCP20
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Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Noah Lewis, Zening Fu, Vince D. Calhoun, Sergey M. Plis:
Whole MILC: Generalizing Learned Dynamics Across Tasks, Datasets, and Populations. MICCAI (7) 2020: 407-417
[c177]
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  - conf/miip/MilerC20
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Robyn L. Miller, Vince D. Calhoun:
Hybrid dictionary learning-ICA approaches built on novel instantaneous dynamic connectivity metric provide new multiscale insights into dynamic brain connectivity. Image Processing 2020: 113131V
[c176]
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Biao Cai, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
A GICA-TVGL framework to study sex differences in resting state fMRI dynamic connectivity. Image Processing 2020: 113132F
[c175]
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  - conf/ssiai/VergaraC20
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Victor M. Vergara, Vince D. Calhoun:
Nicotine Addiction Decreases Dynamic Connectivity Frequency In Functional Magnetic Resonance Imaging. SSIAI 2020: 34-37
[c174]
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Robyn L. Miller, Vince D. Calhoun:
Transient Spectral Peak Analysis Reveals Distinct Temporal Activation Profiles for Different Functional Brain Networks. SSIAI 2020: 108-111
[c173]
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  - conf/ssiai/SendiZFMMC20
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Mohammad S. Eslampanah Sendi, Elaheh Zendehrouh, Zening Fu, Babak Mahmoudi, Robyn L. Miller, Vince D. Calhoun:
A Machine Learning Model for Exploring Aberrant Functional Network Connectivity Transition in Schizophrenia. SSIAI 2020: 112-115
[i22]
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  - journals/corr/abs-2001-01707
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Haleh Falakshahi, Victor M. Vergara, Jingyu Liu, Daniel H. Mathalon, Judith M. Ford, James Voyvodic, Bryon A. Mueller, Aysenil Belger, Sarah C. McEwen, Steven G. Potkin, Adrian Preda, Hooman Rokham, Jing Sui, Jessica A. Turner, Sergey M. Plis, Vince D. Calhoun:
Meta-modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia. CoRR abs/2001.01707 (2020)
[i21]
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  - journals/corr/abs-2001-08173
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Peyman Hosseinzadeh Kassani, Li Xiao, Gemeng Zhang, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
Causality based Feature Fusion for Brain Neuro-Developmental Analysis. CoRR abs/2001.08173 (2020)
[i20]
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  - journals/corr/abs-2006-09454
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Wenxing Hu, Xianghe Meng, Yuntong Bai, Aiying Zhang, Biao Cai, Gemeng Zhang, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang:
Interpretable multimodal fusion networks reveal mechanisms of brain cognition. CoRR abs/2006.09454 (2020)
[i19]
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  - journals/corr/abs-2006-09536
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Aiying Zhang, Gemeng Zhang, Biao Cai, Wenxing Hu, Li Xiao, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang:
Causal inference of brain connectivity from fMRI with ψ-Learning Incorporated Linear non-Gaussian Acyclic Model (ψ-LiNGAM). CoRR abs/2006.09536 (2020)
[i18]
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  - journals/corr/abs-2006-12618
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Aiying Zhang, Gemeng Zhang, Biao Cai, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang:
A Bayesian incorporated linear non-Gaussian acyclic model for multiple directed graph estimation to study brain emotion circuit development in adolescence. CoRR abs/2006.12618 (2020)
[i17]
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  - journals/corr/abs-2007-16041
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Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Noah Lewis, Zening Fu, Vince D. Calhoun, Sergey M. Plis:
Whole MILC: generalizing learned dynamics across tasks, datasets, and populations. CoRR abs/2007.16041 (2020)
[i16]
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  - journals/corr/abs-2012-13619
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Alex Fedorov, Lei Wu, Tristan Sylvain, Margaux Luck, Thomas P. DeRamus, Dmitry Bleklov, Sergey M. Plis, Vince D. Calhoun:
On self-supervised multi-modal representation learning: An application to Alzheimer's disease. CoRR abs/2012.13619 (2020)
[i15]
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  - journals/corr/abs-2012-13623
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Alex Fedorov, Tristan Sylvain, Margaux Luck, Lei Wu, Thomas P. DeRamus, Alex Kirilin, Dmitry Bleklov, Vince D. Calhoun, Sergey M. Plis:
Taxonomy of multimodal self-supervised representation learning. CoRR abs/2012.13623 (2020)

2010 – 2019

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2019
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Eva Mennigen, Susanna Fryer, Barnaly Rashid, Eswar Damaraju, Yuhui Du, Rachel L. Loewy, Barbara Stuart, Vince D. Calhoun, Daniel H. Mathalon:
Transient Patterns of Functional Dysconnectivity in Clinical High Risk and Early Illness Schizophrenia Individuals Compared with Healthy Controls. Brain Connect. 9(1): 60-76 (2019)
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Lori Sanfratello, Jon M. Houck, Vince D. Calhoun:
Dynamic Functional Network Connectivity in Schizophrenia with Magnetoencephalography and Functional Magnetic Resonance Imaging: Do Different Timescales Tell a Different Story? Brain Connect. 9(3): 251-262 (2019)
[j199]
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Ashkan Faghiri, Julia M. Stephen, Yu-Ping Wang, Tony W. Wilson, Vince D. Calhoun:
Brain Development Includes Linear and Multiple Nonlinear Trajectories: A Cross-Sectional Resting-State Functional Magnetic Resonance Imaging Study. Brain Connect. 9(10): 777-788 (2019)
[j198]
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Md. Ashad Alam, Osamu Komori, Hong-Wen Deng, Vince D. Calhoun, Yu-Ping Wang:
Robust kernel canonical correlation analysis to detect gene-gene co-associations: A case study in genetics. J. Bioinform. Comput. Biol. 17(4): 1950028:1-1950028:23 (2019)
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  - journals/neuroimage/TrevarrowKMWMWC19
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Michael P. Trevarrow, Max J. Kurz, Timothy J. McDermott, Alex I. Wiesman, Mackenzie S. Mills, Yu-Ping Wang, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson:
The developmental trajectory of sensorimotor cortical oscillations. NeuroImage 184: 455-461 (2019)
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  - journals/neuroimage/RashidCRDLMAELT19
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Barnaly Rashid, Jiayu Chen, Ishtiaque Rashid, Eswar Damaraju, Jingyu Liu, Robyn L. Miller, Oktay Agcaoglu, Theo G. M. van Erp, Kelvin O. Lim, Jessica A. Turner, Daniel H. Mathalon, Judith M. Ford, James Voyvodic, Bryon A. Mueller, Aysenil Belger, Sarah C. McEwen, Steven G. Potkin, Adrian Preda, Vince D. Calhoun:
A framework for linking resting-state chronnectome/genome features in schizophrenia: A pilot study. NeuroImage 184: 843-854 (2019)
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Christine M. Embury, Alex I. Wiesman, Amy L. Proskovec, Mackenzie S. Mills, Elizabeth Heinrichs-Graham, Yu-Ping Wang, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson:
Neural dynamics of verbal working memory processing in children and adolescents. NeuroImage 185: 191-197 (2019)
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  - journals/neuroimage/BakerASDSCP19
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Bradley T. Baker, Anees Abrol, Rogers F. Silva, Eswar Damaraju, Anand D. Sarwate, Vince D. Calhoun, Sergey M. Plis:
Decentralized temporal independent component analysis: Leveraging fMRI data in collaborative settings. NeuroImage 186: 557-569 (2019)
[j193]
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  - journals/neuroimage/XieZHBCMG19
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Hua Xie, Charles Y. Zheng, Daniel A. Handwerker, Peter A. Bandettini, Vince D. Calhoun, Sunanda Mitra, Javier Gonzalez-Castillo:
Efficacy of different dynamic functional connectivity methods to capture cognitively relevant information. NeuroImage 188: 502-514 (2019)
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  - journals/neuroimage/PremiCDGCAAPGSG19
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Enrico Premi, Vince D. Calhoun, Matteo Diano, Stefano Gazzina, Maura Cosseddu, Antonella Alberici, Silvana Archetti, Donata Paternicò, Roberto Gasparotti, John van Swieten, Daniela Galimberti, Raquel Sánchez-Valle, Robert Laforce Jr., Fermin Moreno, Matthis Synofzik, Caroline Graff, Mario Masellis, Maria Carmela Tartaglia, Miren Zulaica:
The inner fluctuations of the brain in presymptomatic Frontotemporal Dementia: The chronnectome fingerprint. NeuroImage 189: 645-654 (2019)
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Zening Fu, Yiheng Tu, Xin Di, Yuhui Du, Jing Sui, Bharat B. Biswal, Zhiguo Zhang, Nina de Lacy, Vincent D. Calhoun:
Transient increased thalamic-sensory connectivity and decreased whole-brain dynamism in autism. NeuroImage 190: 191-204 (2019)
[j190]
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  - journals/neuroimage/LinHPVELKCC19
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Dongdong Lin, Kent Hutchison, Salvador Portillo, Victor Vegara, Jarrod M. Ellingson, Jingyu Liu, Kenneth S. Krauter, Amanda Carroll-Portillo, Vince D. Calhoun:
Association between the oral microbiome and brain resting state connectivity in smokers. NeuroImage 200: 121-131 (2019)
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  - journals/neuroimage/LacyMKC19
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Nina de Lacy, Elizabeth McCauley, J. Nathan Kutz, Vince D. Calhoun:
Sex-related differences in intrinsic brain dynamism and their neurocognitive correlates. NeuroImage 202 (2019)
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  - journals/pieee/AkyildizPBZCZWZ19
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Ian F. Akyildiz, Massimiliano Pierobon, Sasitharan Balasubramaniam, Jiankang Zhang, Taihai Chen, Shida Zhong, Jingjing Wang, Wenbo Zhang, Xin Zuo, Robert G. Maunder, Lajos Hanzo, Jiayu Chen, Jingyu Liu, Vince D. Calhoun, Alexander B. Magoun:
Scanning the Issue. Proc. IEEE 107(5): 866-867 (2019)
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Jiayu Chen, Jingyu Liu, Vince D. Calhoun:
Translational Potential of Neuroimaging Genomic Analyses to Diagnosis and Treatment in Mental Disorders. Proc. IEEE 107(5): 912-927 (2019)
[j186]
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Biao Cai, Gemeng Zhang, Aiying Zhang, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
Capturing Dynamic Connectivity From Resting State fMRI Using Time-Varying Graphical Lasso. IEEE Trans. Biomed. Eng. 66(7): 1852-1862 (2019)
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Li Xiao, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
Alternating Diffusion Map Based Fusion of Multimodal Brain Connectivity Networks for IQ Prediction. IEEE Trans. Biomed. Eng. 66(8): 2140-2151 (2019)
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Wenxing Hu, Biao Cai, Aiying Zhang, Vince D. Calhoun, Yu-Ping Wang:
Deep Collaborative Learning With Application to the Study of Multimodal Brain Development. IEEE Trans. Biomed. Eng. 66(12): 3346-3359 (2019)
[j183]
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Aiying Zhang, Jian Fang, Faming Liang, Vince D. Calhoun, Yu-Ping Wang:
Aberrant Brain Connectivity in Schizophrenia Detected via a Fast Gaussian Graphical Model. IEEE J. Biomed. Health Informatics 23(4): 1479-1489 (2019)
[j182]
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  - journals/tmi/BhingeMCA19
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Suchita Bhinge, Rami Mowakeaa, Vince D. Calhoun, Tülay Adali:
Extraction of Time-Varying Spatiotemporal Networks Using Parameter-Tuned Constrained IVA. IEEE Trans. Medical Imaging 38(7): 1715-1725 (2019)
[c172]
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  - conf/bhi/FedorovHAFDPC19
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Alex Fedorov, R. Devon Hjelm, Anees Abrol, Zening Fu, Yuhui Du, Sergey M. Plis, Vince D. Calhoun:
Prediction of Progression to Alzheimer's disease with Deep InfoMax. BHI 2019: 1-5
[c171]
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  - conf/ciss/AkhondaLBCA19
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Mohammad A. B. S. Akhonda, Qunfang Long, Suchita Bhinge, Vince D. Calhoun, Tülay Adali:
Disjoint Subspaces for Common and Distinct Component Analysis: Application to Task FMRI Data. CISS 2019: 1-6
[c170]
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  - conf/ciss/JiaALCWA19
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Chunying Jia, Mohammad A. B. S. Akhonda, Qunfang Long, Vince D. Calhoun, Shari Waldstein, Tülay Adali:
C-ICT for Discovery of Multiple Associations in Multimodal Imaging Data: Application to Fusion of fMRI and DTI Data. CISS 2019: 1-5
[c169]
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  - conf/embc/VergaraAEC19
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Victor M. Vergara, Anees Abrol, Flor A. Espinoza, Vince D. Calhoun:
Selection of Efficient Clustering Index to Estimate the Number of Dynamic Brain States from Functional Network Connectivity. EMBC 2019: 632-635
[c168]
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  - conf/embc/AbrolRC19
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Anees Abrol, Hooman Rokham, Vince D. Calhoun:
Diagnostic and Prognostic Classification of Brain Disorders Using Residual Learning on Structural MRI Data. EMBC 2019: 4084-4088
[c167]
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  - conf/embc/AbrolFDC19
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Anees Abrol, Zening Fu, Yuhui Du, Vince D. Calhoun:
Multimodal Data Fusion of Deep Learning and Dynamic Functional Connectivity Features to Predict Alzheimer's Disease Progression. EMBC 2019: 4409-4413
[c166]
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  - conf/isbi/LiFLQCS19
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Tiantian Li, Zening Fu, Xia Liu, Shile Qi, Vince D. Calhoun, Jing Sui:
Multimodal Neuroimaging Patterns Associated with Social Responsiveness Impairment in Autism: A Replication Study. ISBI 2019: 409-413
[c165]
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  - conf/isbi/DuanSCLCL19
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Kuaikuai Duan, Rogers F. Silva, Jiayu Chen, Dongdong Lin, Vince D. Calhoun, Jingyu Liu:
Sparse Infomax Based on Hoyer Projection and its Application to Simulated Structural MRI and SNP Data. ISBI 2019: 418-421
[c164]
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  - conf/isbi/YaoSGCSS19
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Dongren Yao, Hailun Sun, Xiaojie Guo, Vince D. Calhoun, Li Sun, Jing Sui:
ADHD Classification Within and Cross Cohort Using an Ensembled Feature Selection Framework. ISBI 2019: 1265-1269
[c163]
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  - conf/isbi/SahaADRPC19
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Debbrata K. Saha, Anees Abrol, Eswar Damaraju, Barnaly Rashid, Sergey M. Plis, Vince D. Calhoun:
Classification As a Criterion to Select Model Order For Dynamic Functional Connectivity States in Rest-fMRI Data. ISBI 2019: 1602-1605
[c162]
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  - conf/isbi/FaghiriSWWC19
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Ashkan Faghiri, Julia M. Stephen, Yu-Ping Wang, Tony W. Wilson, Vince D. Calhoun:
Using Gradient as a New Metric for Dynamic Connectivity Estimation from Resting fMRI Data. ISBI 2019: 1805-1808
[c161]
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  - conf/isnn/QiuLKZGCC19
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Yue Qiu, Qiu-Hua Lin, Li-Dan Kuang, Wen-Da Zhao, Xiao-Feng Gong, Fengyu Cong, Vince D. Calhoun:
Classification of Schizophrenia Patients and Healthy Controls Using ICA of Complex-Valued fMRI Data and Convolutional Neural Networks. ISNN (2) 2019: 540-547
[c160]
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  - conf/mibam/BaiZCW19
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Yuntong Bai, Pascal Zille, Vince D. Calhoun, Yu-Ping Wang:
Extraction of co-expressed discriminative features of Schizophrenia in imaging epigenetics framework. Biomedical Applications in Molecular, Structural, and Functional Imaging 2019: 109530X
[c159]
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  - conf/mibam/ChenC19
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Zikuan Chen, Vince D. Calhoun:
Phase fMRI reveals sparser function connectivity than magnitude fMRI. Biomedical Applications in Molecular, Structural, and Functional Imaging 2019: 109530D
[c158]
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  - conf/miip/CaiSWCW19
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Biao Cai, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
Improved estimation of dynamic connectivity from resting-state fMRI data. Image Processing 2019: 109490P
[i14]
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  - journals/corr/abs-1904-10931
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Alex Fedorov, R. Devon Hjelm, Anees Abrol, Zening Fu, Yuhui Du, Sergey M. Plis, Vince D. Calhoun:
Prediction of Progression to Alzheimer's disease with Deep InfoMax. CoRR abs/1904.10931 (2019)
[i13]
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  - journals/corr/abs-1910-12913
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Hafiz Imtiaz, Jafar Mohammadi, Rogers F. Silva, Bradley T. Baker, Sergey M. Plis, Anand D. Sarwate, Vince D. Calhoun:
Improved Differentially Private Decentralized Source Separation for fMRI Data. CoRR abs/1910.12913 (2019)
[i12]
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  - journals/corr/abs-1911-02926
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Marie Roald, Suchita Bhinge, Chunying Jia, Vince D. Calhoun, Tülay Adali, Evrim Acar:
Tracing Network Evolution Using the PARAFAC2 Model. CoRR abs/1911.02926 (2019)
[i11]
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  - journals/corr/abs-1911-04048
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Rogers F. Silva, Sergey M. Plis, Tülay Adali, Marios S. Pattichis, Vince D. Calhoun:
Multidataset Independent Subspace Analysis with Application to Multimodal Fusion. CoRR abs/1911.04048 (2019)
[i10]
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  - journals/corr/abs-1912-03130
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Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Zening Fu, Vince D. Calhoun, Sergey M. Plis:
Learnt dynamics generalizes across tasks, datasets, and populations. CoRR abs/1912.03130 (2019)
2018
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  - journals/brain/EspinozaTVMMLMC18
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Flor A. Espinoza, Jessica A. Turner, Victor M. Vergara, Robyn L. Miller, Eva Mennigen, Jingyu Liu, Maria B. Misiura, Jennifer Ciarochi, Hans J. Johnson, Jeffrey D. Long, Henry Jeremy Bockholt, Vincent A. Magnotta, Jane S. Paulsen, Vince D. Calhoun:
Whole-Brain Connectivity in a Large Study of Huntington's Disease Gene Mutation Carriers and Healthy Controls. Brain Connect. 8(3): 166-178 (2018)
[j180]
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  - journals/csda/AlamCW18
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Md. Ashad Alam, Vince D. Calhoun, Yu-Ping Wang:
Identifying outliers using multiple kernel canonical correlation analysis with application to imaging genetics. Comput. Stat. Data Anal. 125: 70-85 (2018)
[j179]
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  - journals/fini/GazulaBDPPSC18
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Harshvardhan Gazula, Bradley T. Baker, Eswar Damaraju, Sergey M. Plis, Sandeep R. Panta, Rogers F. Silva, Vince D. Calhoun:
Decentralized Analysis of Brain Imaging Data: Voxel-Based Morphometry and Dynamic Functional Network Connectivity. Frontiers Neuroinformatics 12: 55 (2018)
[j178]
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  - journals/jfi/BoukouvalasLCA18
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Zois Boukouvalas, Yuri Levin-Schwartz, Vince D. Calhoun, Tülay Adali:
Sparsity and Independence: Balancing Two Objectives in Optimization for Source Separation with Application to fMRI Analysis. J. Frankl. Inst. 355(4): 1873-1887 (2018)
[j177]
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  - journals/neuroimage/AgcaogluMMHC18
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Oktay Agcaoglu, Robyn L. Miller, Andrew R. Mayer, Kenneth Hugdahl, Vince D. Calhoun:
Corrigendum to "Lateralization of resting state networks and relationship to age and gender" [NeuroImage 104 (2015) 310-325]. NeuroImage 167: 504 (2018)
[j176]
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  - journals/neuroimage/WuCBMC18
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Lei Wu, Arvind Caprihan, Juan R. Bustillo, Andy R. Mayer, Vince D. Calhoun:
An approach to directly link ICA and seed-based functional connectivity: Application to schizophrenia. NeuroImage 179: 448-470 (2018)
[j175]
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  - journals/neuroimage/XieCGDMBM18
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Hua Xie, Vince D. Calhoun, Javier Gonzalez-Castillo, Eswar Damaraju, Robyn L. Miller, Peter A. Bandettini, Sunanda Mitra:
Whole-brain connectivity dynamics reflect both task-specific and individual-specific modulation: A multitask study. NeuroImage 180(Part): 495-504 (2018)
[j174]
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Zening Fu, Yiheng Tu, Xin Di, Yuhui Du, Godfrey D. Pearlson, Jessica A. Turner, Bharat B. Biswal, Zhiguo Zhang, Vince D. Calhoun:
Characterizing dynamic amplitude of low-frequency fluctuation and its relationship with dynamic functional connectivity: An application to schizophrenia. NeuroImage 180(Part): 619-631 (2018)
[j173]
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Yuhui Du, Susanna Fryer, Zening Fu, Dongdong Lin, Jing Sui, Jiayu Chen, Eswar Damaraju, Eva Mennigen, Barbara Stuart, Rachel L. Loewy, Daniel H. Mathalon, Vince D. Calhoun:
Dynamic functional connectivity impairments in early schizophrenia and clinical high-risk for psychosis. NeuroImage 180(Part): 632-645 (2018)
[j172]
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Sergey M. Plis, Md Faijul Amin, Adam Chekroud, R. Devon Hjelm, Eswar Damaraju, Hyo Jong Lee, Juan R. Bustillo, KyungHyun Cho, Godfrey D. Pearlson, Vince D. Calhoun:
Reading the (functional) writing on the (structural) wall: Multimodal fusion of brain structure and function via a deep neural network based translation approach reveals novel impairments in schizophrenia. NeuroImage 181: 734-747 (2018)
[j171]
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Rongtao Jiang, Vince D. Calhoun, Nianming Zuo, Dongdong Lin, Jin Li, Lingzhong Fan, Shile Qi, Hailun Sun, Zening Fu, Ming Song, Tianzi Jiang, Jing Sui:
Connectome-based individualized prediction of temperament trait scores. NeuroImage 183: 366-374 (2018)
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Qingbao Yu, Yuhui Du, Jiayu Chen, Jing Sui, Tülay Adali, Godfrey D. Pearlson, Vince D. Calhoun:
Application of Graph Theory to Assess Static and Dynamic Brain Connectivity: Approaches for Building Brain Graphs. Proc. IEEE 106(5): 886-906 (2018)
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Tülay Adali, H. Joel Trussell, Lars Kai Hansen, Vince D. Calhoun:
The Dangers of Following Trends in Research: Sparsity and Other Examples of Hammers in Search of Nails. Proc. IEEE 106(6): 1014-1018 (2018)
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Wenxing Hu, Dongdong Lin, Shaolong Cao, Jingyu Liu, Jiayu Chen, Vince D. Calhoun, Yu-Ping Wang:
Adaptive Sparse Multiple Canonical Correlation Analysis With Application to Imaging (Epi)Genomics Study of Schizophrenia. IEEE Trans. Biomed. Eng. 65(2): 390-399 (2018)
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Su-Ping Deng, Wenxing Hu, Vince D. Calhoun, Yu-Ping Wang:
Integrating Imaging Genomic Data in the Quest for Biomarkers of Schizophrenia Disease. IEEE ACM Trans. Comput. Biol. Bioinform. 15(5): 1480-1491 (2018)
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Shile Qi, Vince D. Calhoun, Theo G. M. van Erp, Juan R. Bustillo, Eswar Damaraju, Jessica A. Turner, Yuhui Du, Jian Yang, Jiayu Chen, Qingbao Yu, Daniel H. Mathalon, Judith M. Ford, James Voyvodic, Bryon A. Mueller, Aysenil Belger, Sarah C. McEwen, Steven G. Potkin, Adrian Preda, Tianzi Jiang, Jing Sui:
Multimodal Fusion With Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia. IEEE Trans. Medical Imaging 37(1): 93-105 (2018)
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Jian Fang, Chao Xu, Pascal Zille, Dongdong Lin, Hong-Wen Deng, Vince D. Calhoun, Yu-Ping Wang:
Fast and Accurate Detection of Complex Imaging Genetics Associations Based on Greedy Projected Distance Correlation. IEEE Trans. Medical Imaging 37(4): 860-870 (2018)
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Biao Cai, Pascal Zille, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
Estimation of Dynamic Sparse Connectivity Patterns From Resting State fMRI. IEEE Trans. Medical Imaging 37(5): 1224-1234 (2018)
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Alexej Gossmann, Pascal Zille, Vince D. Calhoun, Yu-Ping Wang:
FDR-Corrected Sparse Canonical Correlation Analysis With Applications to Imaging Genomics. IEEE Trans. Medical Imaging 37(8): 1761-1774 (2018)
[j162]
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Pascal Zille, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang:
Fused Estimation of Sparse Connectivity Patterns From Rest fMRI - Application to Comparison of Children and Adult Brains. IEEE Trans. Medical Imaging 37(10): 2165-2175 (2018)
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Pascal Zille, Vince D. Calhoun, Yu-Ping Wang:
Enforcing Co-Expression Within a Brain-Imaging Genomics Regression Framework. IEEE Trans. Medical Imaging 37(12): 2561-2571 (2018)
[j160]
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Nan-Feng Jie, Elizabeth A. Osuch, Mao-Hu Zhu, Michael Wammes, Xiao-Ying Ma, Tian-Zi Jiang, Jing Sui, Vince D. Calhoun:
Discriminating Bipolar Disorder from Major Depression using Whole-Brain Functional Connectivity: a Feature Selection Analysis with SVM-FoBa Algorithm. J. Signal Process. Syst. 90(2): 259-271 (2018)
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Mustafa S. Salman, Victor M. Vergara, Eswar Damaraju, Vince D. Calhoun:
Weak Mutual Information Between Functional Domains in Schizophrenia. ACSSC 2018: 1362-1366
[c156]
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Dongmei Zhi, Xiaohong Ma, Luxian Lv, Qing Ke, Yongfeng Yang, Xiao Yang, Miao Pan, Shile Qi, Rongtao Jiang, Yuhui Du, Qingbao Yu, Vince D. Calhoun, Tianzi Jiang, Jing Sui:
Abnormal Dynamic Functional Network Connectivity and Graph Theoretical Analysis in Major Depressive Disorder. EMBC 2018: 558-561
[c155]
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Na Luo, Lin Tian, Vince D. Calhoun, Jiayu Chen, Dongdong Lin, Victor M. Vergara, Shuquan Rao, Fuquan Zhang, Jing Sui:
Exploring different impaired speed of genetic-related brain function and structures in schizophrenic progress using multimodal analysis. EMBC 2018: 4126-4129
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Dongren Yao, Xiaojie Guo, Qihua Zhao, Lu Liu, Qingjiu Cao, Yufeng Wang, Vince D. Calhoun, Li Sun, Jing Sui:
Discriminating ADHD From Healthy Controls Using a Novel Feature Selection Method Based on Relative Importance and Ensemble Learning. EMBC 2018: 4632-4635
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Suchita Bhinge, Vince D. Calhoun, Tülay Adali:
IVA-Based Spatio-Temporal Dynamic Connectivity Analysis in Large-Scale FMRI Data. ICASSP 2018: 965-969
[c152]
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Mohammad A. B. S. Akhonda, Yuri Levin-Schwartz, Suchita Bhinge, Vince D. Calhoun, Tülay Adali:
Consecutive Independence and Correlation Transform for Multimodal Fusion: Application to Eeg and Fmri Data. ICASSP 2018: 2311-2315
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Søren Føns Vind Nielsen, Yuri Levin-Schwartz, Diego Vidaurre, Tülay Adali, Vince D. Calhoun, Kristoffer Hougaard Madsen, Lars Kai Hansen, Morten Mørup:
Evaluating Models of Dynamic Functional Connectivity Using Predictive Classification Accuracy. ICASSP 2018: 2566-2570
[c150]
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Jian Fang, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
Detection of differentially developed functional connectivity patterns in adolescents based on tensor discriminative analysis. ISBI 2018: 10-14
[c149]
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Junqi Wang, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang:
Integration of network topological features and graph Fourier transform for fMRI data analysis. ISBI 2018: 92-96
[c148]
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Aiying Zhang, Jian Fang, Vince D. Calhoun, Yu-Ping Wang:
High dimensional latent Gaussian copula model for mixed data in imaging genetics. ISBI 2018: 105-109
[c147]
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Zikuan Chen, Vince D. Calhoun:
Brain functional mapping and network connectivity of reconstructed susceptibility data. Biomedical Applications in Molecular, Structural, and Functional Imaging 2018: 1057803
[c146]
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Wenxing Hu, Biao Cai, Vince D. Calhoun, Yu-Ping Wang:
Multi-modal Brain Connectivity Study Using Deep Collaborative Learning. GRAIL/Beyond-MIC@MICCAI 2018: 66-73
[c145]
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  - conf/prni/MillerC18
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Robyn L. Miller, Vince D. Calhoun:
Dynamic Whole Brain Polarity Regimes Strongly Distinguish Controls from Schizophrenia Patients. PRNI 2018: 1-4
[c144]
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Victor M. Vergara, Qingbao Yu, Vince D. Calhoun:
Graph Modularity and Randomness Measures : A Comparative Study. SSIAI 2018: 33-36
[c143]
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Maziar Yaesoubi, Rogers F. Silva, Vince D. Calhoun:
In-between and cross-frequency dependence-based summarization of resting-state fMRI data. SSIAI 2018: 93-96
[i9]
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Alvaro Ulloa, Sergey M. Plis, Vince D. Calhoun:
Improving Classification Rate of Schizophrenia Using a Multimodal Multi-Layer Perceptron Model with Structural and Functional MR. CoRR abs/1804.04591 (2018)
2017
[j159]
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Shella D. Keilholz, César Caballero-Gaudes, Peter A. Bandettini, Gustavo Deco, Vince D. Calhoun:
Time-Resolved Resting-State Functional Magnetic Resonance Imaging Analysis: Current Status, Challenges, and New Directions. Brain Connect. 7(8): 465-481 (2017)
[j158]
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Sreenath P. Kyathanahally, Yun Wang, Vince D. Calhoun, Gopikrishna Deshpande:
Investigation of True High Frequency Electrical Substrates of fMRI-Based Resting State Networks Using Parallel Independent Component Analysis of Simultaneous EEG/fMRI Data. Frontiers Neuroinformatics 11: 74 (2017)
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Jon M. Houck, Mustafa S. Çetin, Andrew R. Mayer, Juan R. Bustillo, Julia M. Stephen, Cheryl J. Aine, José M. Cañive, Nora I. Perrone-Bizzozero, Robert J. Thoma, Matthew J. Brookes, Vince D. Calhoun:
Magnetoencephalographic and functional MRI connectomics in schizophrenia via intra- and inter-network connectivity. NeuroImage 145: 96-106 (2017)
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Vince D. Calhoun, Stephen M. Lawrie, Janaina Mourão Miranda, Klaas E. Stephan:
Prediction of Individual Differences from Neuroimaging Data. NeuroImage 145: 135-136 (2017)
[j155]
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Mohammad R. Arbabshirani, Sergey M. Plis, Jing Sui, Vince D. Calhoun:
Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls. NeuroImage 145: 137-165 (2017)
[j154]
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Xing Meng, Rongtao Jiang, Dongdong Lin, Juan R. Bustillo, Thomas R. Jones, Jiayu Chen, Qingbao Yu, Yuhui Du, Yu Zhang, Tianzi Jiang, Jing Sui, Vince D. Calhoun:
Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data. NeuroImage 145: 218-229 (2017)
[j153]
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Vaughn R. Steele, Vikram Rao, Vince D. Calhoun, Kent A. Kiehl:
Machine learning of structural magnetic resonance imaging predicts psychopathic traits in adolescent offenders. NeuroImage 145: 265-273 (2017)
[j152]
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Hojin Jang, Sergey M. Plis, Vince D. Calhoun, Jong-Hwan Lee:
Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks. NeuroImage 145: 314-328 (2017)
[j151]
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Victor M. Vergara, Andrew R. Mayer, Eswar Damaraju, Kent Hutchison, Vince D. Calhoun:
The effect of preprocessing pipelines in subject classification and detection of abnormal resting state functional network connectivity using group ICA. NeuroImage 145: 365-376 (2017)
[j150]
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Amalia R. McDonald, Jordan Muraskin, Nicholas T. Van Dam, Caroline Froehlich, Benjamin Puccio, John Pellman, Clemens C. C. Bauer, Alexis Akeyson, Melissa M. Breland, Vince D. Calhoun, Steven Carter, Tiffany P. Chang, Chelsea Gessner, Alyssa Gianonne, Steven Giavasis, Jamie Glass, Steven Homann, Margaret D. King, Melissa Kramer, Drew Landis, Alexis Lieval:
The real-time fMRI neurofeedback based stratification of Default Network Regulation Neuroimaging data repository. NeuroImage 146: 157-170 (2017)
[j149]
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Jason S. Nomi, Shruti Gopal Vij, Dina R. Dajani, Rosa Steimke, Eswar Damaraju, Srinivas Rachakonda, Vince D. Calhoun, Lucina Q. Uddin:
Chronnectomic patterns and neural flexibility underlie executive function. NeuroImage 147: 861-871 (2017)
[j148]
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  - journals/neuroimage/WorhunskyMGGNAC17
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Patrick D. Worhunsky, David Matuskey, Jean-Dominique Gallezot, Edward Gaiser, Nabeel Nabulsi, Gustavo A. Angarita, Vince D. Calhoun, Robert Malison, Marc N. Potenza, Richard E. Carson:
Regional and source-based patterns of [¹¹C]-(+)-PHNO binding potential reveal concurrent alterations in dopamine D₂ and D₃ receptor availability in cocaine-use disorder. NeuroImage 148: 343-351 (2017)
[j147]
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Victor M. Vergara, Jingyu Liu, Eric D. Claus, Kent Hutchison, Vince D. Calhoun:
Alterations of resting state functional network connectivity in the brain of nicotine and alcohol users. NeuroImage 151: 45-54 (2017)
[j146]
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  - journals/neuroimage/Lerman-SinkoffS17
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Dov B. Lerman-Sinkoff, Jing Sui, Srinivas Rachakonda, Sridhar Kandala, Vince D. Calhoun, Deanna M. Barch:
Multimodal neural correlates of cognitive control in the Human Connectome Project. NeuroImage 163: 41-54 (2017)
[j145]
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  - journals/neuroimage/AbrolDMSCMC17
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Anees Abrol, Eswar Damaraju, Robyn L. Miller, Julia M. Stephen, Eric D. Claus, Andrew R. Mayer, Vince D. Calhoun:
Replicability of time-varying connectivity patterns in large resting state fMRI samples. NeuroImage 163: 160-176 (2017)
[j144]
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C. J. Aine, Henry Jeremy Bockholt, Juan R. Bustillo, José M. Cañive, Arvind Caprihan, Charles Gasparovic, Faith M. Hanlon, Jon M. Houck, Rex E. Jung, John Lauriello, Jingyu Liu, Andy R. Mayer, Nora I. Perrone-Bizzozero, Stefan Posse, Julia M. Stephen, Jessica A. Turner, Vincent P. Clark, Vince D. Calhoun:
Multimodal Neuroimaging in Schizophrenia: Description and Dissemination. Neuroinformatics 15(4): 343-364 (2017)
[j143]
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  - journals/titb/KyathanahallyFZ17
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Sreenath P. Kyathanahally, Ana Franco-Watkins, Xiaoxia Zhang, Vince D. Calhoun, Gopikrishna Deshpande:
A Realistic Framework for Investigating Decision Making in the Brain With High Spatiotemporal Resolution Using Simultaneous EEG/fMRI and Joint ICA. IEEE J. Biomed. Health Informatics 21(3): 814-825 (2017)
[j142]
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Yuri Levin-Schwartz, Vince D. Calhoun, Tülay Adali:
Quantifying the Interaction and Contribution of Multiple Datasets in Fusion: Application to the Detection of Schizophrenia. IEEE Trans. Medical Imaging 36(7): 1385-1395 (2017)
[c142]
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Victor M. Vergara, Vince D. Calhoun:
Brain language: Uncovering functional connectivity codes. ACSSC 2017: 1309-1312
[c141]
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  - conf/ciss/LongBLCA17
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Qunfang Long, Suchita Bhinge, Yuri Levin-Schwartz, Vince D. Calhoun, Tülay Adali:
A graph theoretical approach for performance comparison of ICA for fMRI analysis. CISS 2017: 1-6
[c140]
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  - conf/eusipco/AcarLCA17
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Evrim Acar, Yuri Levin-Schwartz, Vince D. Calhoun, Tülay Adali:
ACMTF for fusion of multi-modal neuroimaging data and identification of biomarkers. EUSIPCO 2017: 643-647
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Nikolas P. Wojtalewicz, Rogers F. Silva, Vince D. Calhoun, Anand D. Sarwate, Sergey M. Plis:
Decentralized independent vector analysis. ICASSP 2017: 826-830
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Li-Dan Kuang, Qiu-Hua Lin, Xiao-Feng Gong, Fengyu Cong, Vince D. Calhoun:
Post-ICA phase de-noising for resting-state complex-valued FMRI data. ICASSP 2017: 856-860
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Mustafa S. Salman, Yuhui Du, Vince D. Calhoun:
Identifying FMRI dynamic connectivity states using affinity propagation clustering method: Application to schizophrenia. ICASSP 2017: 904-908
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