Vince D. Calhoun - researchr alias

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Viewing Publication 1 - 100 from 557

2023

Multi-Subject Analysis for Brain Developmental Patterns Discovery via Tensor Decomposition of MEG DataIrina Belyaeva, Ben Gabrielson, Yu-Ping Wang 0002, Tony W. Wilson, Vince D. Calhoun, Julia M. Stephen, Tülay Adali. ni, 21(1):115-141, January 2023. [doi]

Correction to: Multi-Subject Analysis for Brain Developmental Patterns Discovery via Tensor Decomposition of MEG DataIrina Belyaeva, Ben Gabrielson, Yu-Ping Wang 0002, Tony W. Wilson, Vince D. Calhoun, Julia M. Stephen, Tülay Adali. ni, 21(1):143, January 2023. [doi]

Federated Analysis in COINSTAC Reveals Functional Network Connectivity and Spectral Links to Smoking and Alcohol Consumption in Nearly 2,000 Adolescent BrainsHarshvardhan 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 Desrivieres, 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 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. ni, 21(2):287-301, April 2023. [doi]

The Individualized Prediction of Neurocognitive Function in People Living With HIV Based on Clinical and Multimodal Connectome DataXiang Li, Sheri L. Towe, Ryan P. Bell, Rongtao Jiang, Shana A. Hall, Vince D. Calhoun, Christina S. Meade, Jing Sui. titb, 27(4):2094-2104, April 2023. [doi]

A Novel Neighborhood Rough Set-Based Feature Selection Method and Its Application to Biomarker Identification of SchizophreniaYing Xing, Peter V. Kochunov, Theo G. M. van Erp, Tianzhou Ma, Vince D. Calhoun, Yuhui Du. titb, 27(1):215-226, 2023. [doi]

An explainable autoencoder with multi-paradigm fMRI fusion for identifying differences in dynamic functional connectivity during brain developmentFaming Xu, Chen Qiao, Huiyu Zhou, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang 0002. NN, 159:185-197, February 2023. [doi]

Identification of Homogeneous Subgroups from Resting-State fMRI DataHanLu Yang, Trung Vu, Qunfang Long, Vince D. Calhoun, Tülay Adali. sensors, 23(6):3264, March 2023. [doi]

2022

Distance Correlation-Based Brain Functional Connectivity Estimation and Non-Convex Multi-Task Learning for Developmental fMRI StudiesLi Xiao 0002, Biao Cai, Gang Qu 0002, Gemeng Zhang, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang 0002. tbe, 69(10):3039-3050, 2022. [doi]

Discovery and Replication of Time-Resolved Functional Network Connectivity Differences in Adolescence and Adulthood in over 50K fMRI DatasetsAnees Abrol, Vince D. Calhoun. embc 2022: 1855-1858 [doi]

Probing the link between the APOE-ε4 allele and whole-brain gray matter using deep learningAnees Abrol, Ihab Hajjar, Vince D. Calhoun. embc 2022: 3506-3509 [doi]

Reproducibility in Matrix and Tensor Decompositions: Focus on model match, interpretability, and uniquenessTülay Adali, Furkan Kantar, Mohammad Abu Baker Siddique Akhonda, Stephen C. Strother, Vince D. Calhoun, Evrim Acar. spm, 39(4):8-24, 2022. [doi]

Lateralization of Resting-State Networks in Children: Association with Age, Sex, Handedness, Intelligence Quotient, and BehaviorOktay Agcaoglu, Ryan L. Muetzel, Barnaly Rashid, Tonya White, Henning Tiemeier, Vince D. Calhoun. brain, 12(3):246-259, 2022. [doi]

Multimodal fusion of brain imaging data with joint non-linear independent component analysisOktay Agcaoglu, Rogers F. Silva, Vince D. Calhoun. ivmsp 2022: 1-5 [doi]

Longitudinal Changes in Resting State FMRI Spectra in ChildrenOktay Agcaoglu, Tony W. Wilson, Yu-Ping Wang 0002, Julia M. Stephen, Vince D. Calhoun. embc 2022: 3729-3732 [doi]

Association of Neuroimaging Data with Behavioral Variables: A Class of Multivariate Methods and Their Comparison Using Multi-Task FMRI DataMohammad A. B. S. Akhonda, Yuri Levin-Schwartz, Vince D. Calhoun, Tülay Adali. sensors, 22(3):1224, 2022. [doi]

Decentralized Brain Age Estimation Using MRI DataSunitha Basodi, Rajikha Raja, Bhaskar Ray, Harshvardhan Gazula, Anand D. Sarwate, Sergey M. Plis, Jingyu Liu 0001, Eric Verner, Vince D. Calhoun. ni, 20(4):981-990, 2022. [doi]

Building Models of Functional Interactions Among Brain Domains that Encode Varying Information Complexity: A Schizophrenia Case StudyIshaan Batta, Anees Abrol, Zening Fu, Adrian Preda, Theo G. M. van Erp, Vince D. Calhoun. ni, 20(3):777-791, 2022. [doi]

Learning Active Multimodal Subspaces in the BrainIshaan Batta, Anees Abrol, Zening Fu, Vince D. Calhoun. embc 2022: 3822-3825 [doi]

Deep Learning Prediction and Visualization of Gender Related Brain Changes from Longitudinal Structural MRI Data in the ABCD StudyYuda Bi, Anees Abrol, Zening Fu, Vince D. Calhoun. embc 2022: 3814-3817 [doi]

An ICA-based framework for joint analysis of cognitive scores and MEG event-related fieldsPoomipat Boonyakitanont, Ben Gabrielson, Irina Belyaeva, Parthan Olikkal, Jitkomut Songsiri, Yu-Ping Wang, Tony W. Wilson, Vince D. Calhoun, Julia M. Stephen, Tülay Adali. embc 2022: 3594-3598 [doi]

Multi-Site Mild Traumatic Brain Injury Classification with Machine Learning and HarmonizationBiozid Bostami, Flor A. Espinoza, Harm J. van der Horn, Joukje van der Naalt, Vince D. Calhoun, Victor M. Vergara. embc 2022: 537-540 [doi]

A deep generative multimodal imaging genomics framework for Alzheimer's disease predictionGiorgio Dolci, Md Abdur Rahaman, Jiayu Chen 0003, Kuaikuai Duan, Zening Fu, Anees Abrol, Gloria Menegaz, Vince D. Calhoun. bibe 2022: 41-44 [doi]

Multimodal Analysis Uncovers Links between Grey Matter Volume and both Low-and High-frequency Dynamic Connectivity States in SchizophreniaMarlena Duda, Ashkan Faghiri, Vince D. Calhoun. bibm 2022: 1521-1525 [doi]

Spatially Constrained ICA Enables Robust Detection of Schizophrenia from Very Short Resting-state fMRIMarlena Duda, Armin Iraji, Vince D. Calhoun. embc 2022: 1867-1870 [doi]

Examining Reproducibility of EEG Schizophrenia Biomarkers Across Explainable Machine Learning ModelsCharles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, Vince D. Calhoun. bibe 2022: 305-308 [doi]

Examining Effects of Schizophrenia on EEG with Explainable Deep Learning ModelsCharles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, Vince D. Calhoun. bibe 2022: 301-304 [doi]

An Unsupervised Feature Learning Approach for Elucidating Hidden Dynamics in rs-fMRI Functional Network ConnectivityCharles A. Ellis, Mohammad S. Eslampanah Sendi, Robyn L. Miller, Vince D. Calhoun. embc 2022: 4449-4452 [doi]

An Approach for Estimating Explanation Uncertainty in fMRI dFNC ClassificationCharles A. Ellis, Robyn L. Miller, Vince D. Calhoun. bibe 2022: 297-300 [doi]

A Model Visualization-based Approach for Insight into Waveforms and Spectra Learned by CNNsCharles A. Ellis, Robyn L. Miller, Vince D. Calhoun. embc 2022: 1643-1646 [doi]

Exploring Relationships between Functional Network Connectivity and Cognition with an Explainable Clustering ApproachCharles A. Ellis, Martina Lapera Sancho, Mohammad S. Eslampanah Sendi, Robyn L. Miller, Vince D. Calhoun. bibe 2022: 293-296 [doi]

Single Sideband Modulation as a Tool To Improve Functional Connectivity EstimationAshkan Faghiri, Tülay Adali, Vince D. Calhoun. isbi 2022: 1-4 [doi]

Going from lines to triangles: A formulation for time-frequency moments of time-series with application to study fMRIAshkan Faghiri, Armin Iraji, Noah Lewis, Kun Yang, Koko Ishizuka, Akira Sawa, Tülay Adali, Vince D. Calhoun. ivmsp 2022: 1-5 [doi]

A Unified Framework for Modularizing and Comparing Time-Resolved Functional Connectivity MethodsAshkan Faghiri, Armin Iraji, Marlena Duda, Tülay Adali, Vince D. Calhoun. embc 2022: 4631-4634 [doi]

Functional Connectivity Stability: A Signature of Neurocognitive Development and Psychiatric Problems in ChildrenZening Fu, Mustafa S. Salman, Jingyu Liu 0001, Vince D. Calhoun. embc 2022: 251-254 [doi]

The development of sensorimotor cortical oscillations is mediated by pubertal testosteroneMadison H. Fung, Elizabeth Heinrichs-Graham, Brittany K. Taylor, Michaela R. Frenzel, Jacob A. Eastman, Yu-Ping Wang 0002, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson. neuroimage, 264:119745, 2022. [doi]

Transient Intervals of Significantly Different Whole Brain Connectivity Predict Recovery vs. Progression from Mild Cognitive Impairment: New Insights from Interpretable LSTM ClassifiersYutong Gao, Vince D. Calhoun, Robyn L. Miller. embc 2022: 4645-4648 [doi]

Low-Rank Tucker-2 Model for Multi-Subject fMRI Data Decomposition With Spatial Sparsity ConstraintYue Han, Qiu-Hua Lin, Li-Dan Kuang, Xiao-Feng Gong, Fengyu Cong, Yu-Ping Wang 0002, Vince D. Calhoun. tmi, 41(3):667-679, 2022. [doi]

A Contrastive Learning-Based Approach To Measure Spatial Coupling Among Brain Networks: A Schizophrenia StudyReihaneh Hassanzadeh, Vince D. Calhoun. isbi 2022: 1-4 [doi]

Classification of Schizophrenia and Alzheimer's Disease using Resting-State Functional Network ConnectivityReihaneh Hassanzadeh, Anees Abrol, Vince D. Calhoun. bhi 2022: 1-4 [doi]

A Supervised Contrastive Learning-based Analysis of rs-tMRI Data Captures Gender Differences in Nonlinear Functional Network CouplingReihaneh Hassanzadeh, Vince D. Calhoun. embc 2022: 4641-4644 [doi]

Data-driven spatio-temporal dynamic brain connectivity analysis using fALFF: Application to sensorimotor task dataKhondoker Murad Hossain, Suchita Bhinge, Qunfang Long, Vince D. Calhoun, Tülay Adali. ciss 2022: 200-205 [doi]

A 5D approach to study spatio-temporal dynamism of resting-state brain networks in schizophreniaBehnam Kazemivash, Vince D. Calhoun. embc 2022: 3737-3740 [doi]

An Accelerated Rank-(L, L, 1, 1) Block Term Decomposition Of Multi-Subject Fmri Data Under Spatial Orthonormality ConstraintLi-Dan Kuang, Biao Wang, Qiu-Hua Lin, Hao-Peng Zhang, Jianming Zhang, Wenjun Li, Feng Li, Vince D. Calhoun. icassp 2022: 3933-3937 [doi]

Multi-Task fMRI Data Fusion Using IVA and PARAFAC2Isabell Lehmann, Evrim Acar, Tanuj Hasija, Mohammad A. B. S. Akhonda, Vince D. Calhoun, Peter J. Schreier, Tülay Adali. icassp 2022: 1466-1470 [doi]

Mind the gap: functional network connectivity interpolation between schizophrenia patients and controls using a variational autoencoderXinhui Li, Eloy Geenjaar, Zening Fu, Sergey M. Plis, Vince D. Calhoun. embc 2022: 1477-1480 [doi]

SSPNet: An interpretable 3D-CNN for classification of schizophrenia using phase maps of resting-state complex-valued fMRI dataQiu-Hua Lin, Yan-Wei Niu, Jing Sui, Wen-Da Zhao, Chuanjun Zhuo, Vince D. Calhoun. mia, 79:102430, 2022. [doi]

Through the looking glass: Deep interpretable dynamic directed connectivity in resting fMRIUsman Mahmood, Zening Fu, Satrajit S. Ghosh, Vince D. Calhoun, Sergey M. Plis. neuroimage, 264:119737, 2022. [doi]

Deep Dynamic Effective Connectivity Estimation from Multivariate Time SeriesUsman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis. ijcnn 2022: 1-10 [doi]

Deep Learning in Biological Image and Signal Processing [From the Guest Editors]Erik Meijering, Vince D. Calhoun, Gloria Menegaz, David J. Miller 0001, Jong Chul Ye. spm, 39(2):24-26, 2022. [doi]

Multimodel Order Independent Component Analysis: A Data-Driven Method for Evaluating Brain Functional Network Connectivity Within and Between Multiple Spatial ScalesXing 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. brain, 12(7):617-628, 2022. [doi]

Group Sparse Joint Non-Negative Matrix Factorization on Orthogonal Subspace for Multi-Modal Imaging Genetics Data AnalysisPeng Peng, Yipu Zhang, Yongfeng Ju, Kaiming Wang, Gang Li 0029, Vince D. Calhoun, Yu-Ping Wang 0002. tcbb, 19(1):479-490, 2022. [doi]

Eyes-closed versus eyes-open differences in spontaneous neural dynamics during developmentNathan M. Petro, Lauren R. Ott, Samantha H. Penhale, Maggie P. Rempe, Christine M. Embury, Giorgia Picci, Yu-Ping Wang 0002, Julia M. Stephen, Vince D. Calhoun, Tony W. Wilson. neuroimage, 258:119337, 2022. [doi]

Tri-Clustering Dynamic Functional Network Connectivity Identifies Significant Schizophrenia Effects Across Multiple States in Distinct Subgroups of IndividualsMd 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. brain, 12(1):61-73, 2022. [doi]

Two-Dimensional Attentive Fusion for Multi-Modal Learning of Neuroimaging and Genomics DataMd Abdur Rahaman, Yash Garg, Armin Iraji, Zening Fu, Jiayu Chen 0003, Vince D. Calhoun. mlsp 2022: 1-6 [doi]

Relationship of Hemodynamic Delay and Sex Differences Among Adolescents Using Resting-state fMRI DataHooman Rokham, Haleh Falakshahi, Vince D. Calhoun. bhi 2022: 1-4 [doi]

Federated Analysis of Neuroimaging Data: A Review of the FieldKelly Rootes-Murdy, Harshvardhan Gazula, Eric Verner, Ross Kelly, Thomas DeRamus, Sergey M. Plis, Anand D. Sarwate, Jessica A. Turner, Vince D. Calhoun. ni, 20(2):377-390, 2022. [doi]

Decentralized Spatially Constrained Source-Based MorphometryDebbrata K. Saha, Rogers F. Silva, Bradley T. Baker, Vince D. Calhoun. isbi 2022: 1-5 [doi]

Longitudinal Whole-Brain Functional Network Change Patterns Over A Two-Year Period In The ABCD DataRekha Saha, Debbrata K. Saha, Md Abdur Rahaman, Zening Fu, Vince D. Calhoun. isbi 2022: 1-4 [doi]

An Approach to Automatically Label and Order Brain Activity/Component MapsMustafa S. Salman, Tor D. Wager, Eswar Damaraju, Anees Abrol, Victor M. Vergara, Zening Fu, Vince D. Calhoun. brain, 12(1):85-95, 2022. [doi]

NeuroCrypt: Machine Learning Over Encrypted Distributed Neuroimaging DataNipuna Senanayake, Robert Podschwadt, Daniel Takabi, Vince D. Calhoun, Sergey M. Plis. ni, 20(1):91-108, 2022. [doi]

Default mode network dynamic functional network connectivity predicts psychotic symptom severityMohammad S. Eslampanah Sendi, Hossein Dini, Luis Emilio Bruni, Vince D. Calhoun. embc 2022: 247-250 [doi]

A two-step clustering-based pipeline for big dynamic functional network connectivity dataMohammad S. Eslampanah Sendi, Robyn L. Miller, David H. Salat, Vince D. Calhoun. embc 2022: 3741-3744 [doi]

A longitudinal study of functional connectome uniqueness and its association with psychological distress in adolescenceZack 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. neuroimage, 258:119358, 2022. [doi]

Longitudinal changes in the neural oscillatory dynamics underlying abstract reasoning in children and adolescentsBrittany K. Taylor, Elizabeth Heinrichs-Graham, Jacob A. Eastman, Michaela R. Frenzel, Yu-Ping Wang 0002, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson. neuroimage, 253:119094, 2022. [doi]

Individual differences in amygdala volumes predict changes in functional connectivity between subcortical and cognitive control networks throughout adolescenceBrittany K. Taylor, Michaela R. Frenzel, Jacob A. Eastman, Christine M. Embury, Oktay Agcaoglu, Yu-Ping Wang 0002, Julia M. Stephen, Vince D. Calhoun, Tony W. Wilson. neuroimage, 247:118852, 2022. [doi]

Comparison of Energy Signals from the 4D DWT of Resting State FMRI Data Obtained from a Study on SchizophreniaMichael Weeks, Vince D. Calhoun, Robyn L. Miller. embc 2022: 4635-4640 [doi]

Refacing Defaced MRI with PixelCNNYaorong Xiao, William Ashbee, Vince D. Calhoun, Sergey M. Plis. ijcnn 2022: 1-7 [doi]

Deep Learning in Neuroimaging: Promises and challengesWeizheng Yan, Gang Qu 0002, Wenxing Hu, Anees Abrol, Biao Cai, Chen Qiao, Sergey M. Plis, Yu-Ping Wang 0002, Jing Sui, Vince D. Calhoun. spm, 39(2):87-98, 2022. [doi]

'Harmless' adversarial network harmonization approach for removing site effects and improving reproducibility in neuroimaging studiesWeizheng Yan, Zening Fu, Jing Sui, Vince D. Calhoun. embc 2022: 1859-1862 [doi]

Independent Vector Analysis Based Subgroup Identification from Multisubject fMRI DataH. Yang, Mohammad A. B. S. Akhonda, F. Ghayem, Qunfang Long, Vince D. Calhoun, Tülay Adali. icassp 2022: 1471-1475 [doi]

Explainable AI (XAI) In Biomedical Signal and Image Processing: Promises and ChallengesGuang Yang, Arvind Rao, Christine Fernandez-Maloigne, Vince D. Calhoun, Gloria Menegaz. icip 2022: 1531-1535 [doi]

Deep Learning From Imaging Genetics for Schizophrenia ClassificationHongkun Yu, Thomas Florian, Vince D. Calhoun, Dong Hye Ye. icip 2022: 3291-3295 [doi]

Detecting abnormal connectivity in schizophrenia via a joint directed acyclic graph estimation modelGemeng Zhang, Biao Cai, Aiying Zhang, Zhuozhuo Tu, Li Xiao 0002, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang 0002. neuroimage, 260:119451, 2022. [doi]

Multi-Modal Imaging Genetics Data Fusion via a Hypergraph-Based Manifold Regularization: Application to Schizophrenia StudyYipu Zhang, Haowei Zhang, Li Xiao 0002, Yuntong Bai, Vince D. Calhoun, Yu-Ping Wang. tmi, 41(9):2263-2272, 2022. [doi]

An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI dataMin Zhao, Weizheng Yan, Na Luo, Dongmei Zhi, Zening Fu, Yuhui Du, Shan Yu, Tianzi Jiang, Vince D. Calhoun, Jing Sui. mia, 78:102413, 2022. [doi]

A dynamic graph convolutional neural network framework reveals new insights into connectome dysfunctions in ADHDKanhao Zhao, Boris Duka, Hua Xie, Desmond J. Oathes, Vince D. Calhoun, Yu Zhang. neuroimage, 246:118774, 2022. [doi]

2021

Correlation Guided Graph Learning to Estimate Functional Connectivity Patterns From fMRI DataLi Xiao 0002, Aiying Zhang, Biao Cai, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang 0002. tbe, 68(4):1154-1165, 2021. [doi]

Accessing dynamic functional connectivity using l0-regularized sparse-smooth inverse covariance estimation from fMRILi Zhang 0041, Zening Fu, Wenwen Zhang, Gan Huang, Zhen Liang, Linling Li, Bharat B. Biswal, Vince D. Calhoun, Zhiguo Zhang 0001. ijon, 443:147-161, 2021. [doi]

A Joint Analysis of Multi-Paradigm fMRI Data With Its Application to Cognitive StudyYuntong Bai, Yun Gong, Jianchao Bai, Jingyu Liu, Hong-Wen Deng, Vince D. Calhoun, Yu-Ping Wang 0002. tmi, 40(3):951-962, 2021. [doi]

A Transdiagnostic Biotype Detection Method for Schizophrenia and Autism Spectrum Disorder Based on Graph KernelYuhui Du, Hui Hao, Ying Xing, Ju Niu, Vince D. Calhoun. embc 2021: 3241-3244 [doi]

Dynamic state with covarying brain activity-connectivity: On the pathophysiology of schizophreniaZening Fu, Armin Iraji, Jessica A. Turner, Jing Sui, Robyn L. Miller, Godfrey D. Pearlson, Vince D. Calhoun. neuroimage, 224:117385, 2021. [doi]

Interpretable Multimodal Fusion Networks Reveal Mechanisms of Brain CognitionWenxing 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 0002. tmi, 40(5):1474-1483, 2021. [doi]

Frequency drift in MR spectroscopy at 3TSteve 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 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 K. W. Yeung, Qun Zhao, Xiaopeng Zhou, Gasper Zupan. neuroimage, 241:118430, 2021. [doi]

The Influence of Cerebral Small Vessel Disease on Static and Dynamic Functional Network Connectivity in Subjects Along Alzheimer's Disease ContinuumKaicheng Li, Zening Fu, Xiao Luo, Qingze Zeng, Peiyu Huang, Minming Zhang, Vince D. Calhoun. brain, 11(3):189-200, 2021. [doi]

Relationship between Dynamic Blood-Oxygen-Level-Dependent Activity and Functional Network Connectivity: Characterization of Schizophrenia SubgroupsQunfang Long, Suchita Bhinge, Vince D. Calhoun, Tülay Adali. brain, 11(6):430-446, 2021. [doi]

A Deep Learning Model for Data-Driven Discovery of Functional ConnectivityUsman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis. algorithms, 14(3):75, 2021. [doi]

Spontaneous cortical MEG activity undergoes unique age- and sex-related changes during the transition to adolescenceLauren R. Ott, Samantha H. Penhale, Brittany K. Taylor, Brandon J. Lew, Yu-Ping Wang, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson. neuroimage, 244:118552, 2021. [doi]

Multiview Diffusion Map Improves Prediction of Fluid Intelligence With Two Paradigms of fMRI AnalysisGuixia Pan, Li Xiao 0002, Yuntong Bai, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang 0002. tbe, 68(8):2529-2539, 2021. [doi]

Sparse deep dictionary learning identifies differences of time-varying functional connectivity in brain neuro-developmental studyChen Qiao, Lan Yang, Vince D. Calhoun, Zong-Ben Xu, Yu-Ping Wang 0002. NN, 135:91-104, 2021. [doi]

A deep autoencoder with sparse and graph Laplacian regularization for characterizing dynamic functional connectivity during brain developmentChen Qiao, Xin-Yu Hu, Li Xiao 0002, Vince D. Calhoun, Yu-Ping Wang 0002. ijon, 456:97-108, 2021. [doi]

Statelets: A Novel Multi-Dimensional State-Shape Representation Of Brain Functional Connectivity DynamicsMd Abdur Rahaman, Eswar Damaraju, Debbrata Kumar Saha, Vince D. Calhoun, Sergey M. Plis. isbi 2021: 1822-1826 [doi]

A Classification-Based Approach to Estimate the Number of Resting Functional Magnetic Resonance Imaging Dynamic Functional Connectivity StatesDebbrata K. Saha, Eswar Damaraju, Barnaly Rashid, Anees Abrol, Sergey M. Plis, Vince D. Calhoun. brain, 11(2):132-145, 2021. [doi]

Abnormal Dynamic Functional Network Connectivity Estimated from Default Mode Network Predicts Symptom Severity in Major Depressive DisorderMohammad 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. brain, 11(10):838-849, 2021. [doi]

Multidataset Independent Subspace Analysis With Application to Multimodal FusionRogers F. Silva, Sergey M. Plis, Tülay Adali, Marios S. Pattichis, Vince D. Calhoun. TIP, 30:588-602, 2021. [doi]

Respiratory, cardiac, EEG, BOLD signals and functional connectivity over multiple microsleep episodesChun Siong Soon, Ksenia Vinogradova, Ju Lynn Ong, Vince D. Calhoun, Thomas Liu, Juan Helen Zhou, Kwun Kei Ng, Michael W. L. Chee. neuroimage, 237:118129, 2021. [doi]

The Developmental Chronnecto-Genomics (Dev-CoG) study: A multimodal study on the developing brainJulia 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, Y. P. Wang, Tony W. Wilson, Vince D. Calhoun. neuroimage, 225:117438, 2021. [doi]

A Latent Gaussian Copula Model for Mixed Data Analysis in Brain Imaging GeneticsAiying Zhang, Jian Fang 0001, Wenxing Hu, Vince D. Calhoun, Yu-Ping Wang 0002. tcbb, 18(4):1350-1360, 2021. [doi]

Multi-Paradigm fMRI Fusion via Sparse Tensor Decomposition in Brain Functional Connectivity StudyYipu Zhang, Li Xiao 0002, Gemeng Zhang, Biao Cai, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang 0002. titb, 25(5):1712-1723, 2021. [doi]

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