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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
- 2023
[j299]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)- [j298]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) - [j297]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) - [j296]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) - [j295]Dylan Martin, Sunitha Basodi, Sandeep R. Panta, Kelly Rootes-Murdy, Paul Prae, Anand D. Sarwate, Ross Kelly, Javier 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) - [j294]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) - [j293]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) - [j292]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) - [j291]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) - [j290]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) - [j289]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) - [j288]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) - [j287]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) - [j286]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) - [j285]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) - [j284]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) - [c301]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 - [c300]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 - [c299]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 - [c298]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 - [c297]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 - [c296]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 - [c295]Meenu Ajith, Vince D. Calhoun:
Functional Network Connectivity Based Mental Health Category Prediction from Rest-fMRI Data. ISBI 2023: 1-5 - [c294]Sunitha Basodi, Rajikha Raja, Harshvardhan Gazula, Javier Romero, Sandeep R. Panta, Vince D. Calhoun:
Federated Linear Mixed Effects Modeling for Voxel-Based Morphometry. ISBI 2023: 1-4 - [c293]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 - [c292]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 - [c291]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 - [c290]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 - [c289]Kuaikuai Duan, Rogers F. Silva, Jingyu Liu, Oktay Agcaoglu, Vince D. Calhoun:
Any-Way Independent Component Analysis with Reference. ISBI 2023: 1-4 - [c288]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 - [c287]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 - [c286]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 - [c285]Noah Lewis, Armin Iraji, Robyn L. Miller, Vince D. Calhoun:
Topological Correction of Subject-Level Intrinsic Connectivity Networks. ISBI 2023: 1-4 - [c284]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 - [c283]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 - [c282]Mustafa S. Salman, Armin Iraji, Noah Lewis, Vince D. Calhoun:
Topological Characteristics of 5d Spatially Dynamic Brain Networks in Schizophrenia. ISBI 2023: 1-5 - [c281]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 - [i45]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) - [i44]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) - [i43]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) - [i42]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) - [i41]Yujia Xie, Xinhui Li, Vince D. Calhoun:
Predictive Sparse Manifold Transform. CoRR abs/2308.14207 (2023) - [i40]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) - 2022
- [j283]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) - [j282]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) - [j281]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) - [j280]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) - [j279]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) - [j278]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) - [j277]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) - [j276]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) - [j275]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) - [j274]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) - [j273]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) - [j272]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) - [j271]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) - [j270]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) - [j269]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) - [j268]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) - [j267]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) - [j266]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) - [j265]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) - [j264]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) - [j263]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) - [j262]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) - [j261]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) - [j260]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) - [j259]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) - [j258]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) - [j257]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) - [j256]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) - [j255]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) - [j254]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) - [c280]Reihaneh Hassanzadeh, Anees Abrol, Vince D. Calhoun:
Classification of Schizophrenia and Alzheimer's Disease using Resting-State Functional Network Connectivity. BHI 2022: 1-4 - [c279]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 - [c278]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 - [c277]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 - [c276]Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun:
An Approach for Estimating Explanation Uncertainty in fMRI dFNC Classification. BIBE 2022: 297-300 - [c275]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 - [c274]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 - [c273]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 - [c272]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 - [c271]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 - [c270]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 - [c269]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 - [c268]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 - [c267]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 - [c266]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 - [c265]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 - [c264]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 - [c263]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 - [c262]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 - [c261]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 - [c260]Behnam Kazemivash, Vince D. Calhoun:
A 5D approach to study spatio-temporal dynamism of resting-state brain networks in schizophrenia. EMBC 2022: 3737-3740 - [c259]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 - [c258]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 - [c257]Ishaan Batta, Anees Abrol, Zening Fu, Vince D. Calhoun:
Learning Active Multimodal Subspaces in the Brain. EMBC 2022: 3822-3825 - [c256]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 - [c255]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 - [c254]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 - [c253]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 - [c252]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 - [c251]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 - [c250]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 - [c249]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 - [c248]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 - [c247]