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ORCIDVince D. Calhoun
Vincent D. Calhoun
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- affiliation: University of New Mexico, Albuquerque, USA
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2020 – today
- 2022
[j269]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)- [j268]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) - [j267]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) - [j266]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) - [j265]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) - [j264]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) - [j263]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) - [j262]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) - [j261]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) - [j260]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) - [j259]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) - [j258]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) - [j257]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) - [j256]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) - [j255]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) - [j254]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) - [j253]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) - [c244]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 - [c243]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 - [c242]H. Yang, Mohammad A. B. S. Akhonda, F. Ghayem, Qunfang Long, Vince D. Calhoun, Tülay Adali:
Independent Vector Analysis Based Subgroup Identification from Multisubject fMRI Data. ICASSP 2022: 1471-1475 - [c241]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 - [c240]Ashkan Faghiri, Tülay Adali, Vince D. Calhoun:
Single Sideband Modulation as a Tool To Improve Functional Connectivity Estimation. ISBI 2022: 1-4 - [c239]Reihaneh Hassanzadeh, Vince D. Calhoun:
A Contrastive Learning-Based Approach To Measure Spatial Coupling Among Brain Networks: A Schizophrenia Study. ISBI 2022: 1-4 - [c238]Debbrata K. Saha, Rogers F. Silva, Bradley T. Baker, Vince D. Calhoun:
Decentralized Spatially Constrained Source-Based Morphometry. ISBI 2022: 1-5 - [c237]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 - [c236]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 - [c235]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 - [i34]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) - [i33]Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis:
Deep Dynamic Effective Connectivity Estimation from Multivariate Time Series. CoRR abs/2202.02393 (2022) - [i32]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) - [i31]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) - 2021
- [j252]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) - [j251]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) - [j250]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) - [j249]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) - [j248]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) - [j247]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) - [j246]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) - [j245]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) - [j244]Julia M. Stephen, I. 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, J. 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) - [j243]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) - [j242]Lei Wu, Arvind Caprihan, Vince D. Calhoun:
Tracking spatial dynamics of functional connectivity during a task. NeuroImage 239: 118310 (2021) - [j241]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, Maria C. G. 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) - [j240]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) - [j239]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) - [j238]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, 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) - [j237]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) - [j236]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) - [j235]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) - [j234]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) - [j233]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) - [j232]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) - [j231]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) - [j230]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) - [j229]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) - [j228]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) - [c234]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 - [c233]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 - [c232]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 - [c231]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 - [c230]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 - [c229]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 - [c228]Eloy Geenjaar, Tonya White, Vince D. Calhoun:
Variational voxelwise rs-fMRI representation learning: Evaluation of sex, age, and neuropsychiatric signatures. BIBM 2021: 1733-1740 - [c227]Bishal Thapaliya, Vince D. Calhoun, Jingyu Liu:
Environmental and genome-wide association study on children anxiety and depression. BIBM 2021: 2330-2337 - [c226]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 - [c225]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 - [c224]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 - [c223]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 - [c222]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 - [c221]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 - [c220]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 - [c219]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 - [c218]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 - [c217]Robyn L. Miller, Victor M. Vergara, Vince D. Calhoun:
A Method for Integrative Analysis of Local and Global Brain Dynamics. EMBC 2021: 3189-3192 - [c216]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 - [c215]Yuhui Du, Xingyu He, Vince D. Calhoun:
SMART (splitting-merging assisted reliable) Independent Component Analysis for Brain Functional Networks. EMBC 2021: 3263-3266 - [c214]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 - [c213]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 - [c212]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 - [c211]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 - [c210]Eswar Damaraju, Rogers F. Silva, Tülay Adali, Vince D. Calhoun:
A multimodal IVA fusion approach to identify linked neuroimaging markers. EMBC 2021: 3928-3932 - [c209]Ishaan Batta, Anees Abrol, Vince D. Calhoun:
Uncovering Active Structural Subspaces Associated with Changes in Indicators for Alzheimer's Disease. EMBC 2021: 3948-3951 - [c208]Anees Abrol, Reihaneh Hassanzadeh, Sergey M. Plis, Vince D. Calhoun:
Deep learning in resting-state fMRI*. EMBC 2021: 3965-3969 - [c207]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 - [c206]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 - [c205]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 - [c204]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 - [c203]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 - [c202]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 - [c201]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 - [c200]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 - [c199]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 - [c198]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 - [c197]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 - [c196]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 - [c195]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 - [c194]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 - [i30]