Adaptive Filtering of Visual Evoked Responses in FMRI: Variability of Response. - Vince D. Calhoun; Tülay Adali; Godfrey D. Pearlson (SIP, 1999)

fMRI Activation in a Visual-Perception Task: Network of Areas Detected Using the General Linear Model and Independent Components Analysis. - Vince D. Calhoun; Tülay Adali; V. B. McGinty; James J. Pekar; T. D. Watson; Godfrey D. Pearlson (NeuroImage, 2001)

On complex infomax applied to functional MRI data. - Vince D. Calhoun; Tülay Adali; Godfrey D. Pearlson; James J. Pekar (ICASSP, 2002)

Complex ICA for fMRI analysis: performance of several approaches. - Vince D. Calhoun; Tülay Adali (ICASSP (2), 2003)

Latency (in)sensitive ICA: Group independent component analysis of fMRI data in the temporal frequency domain. - Vince D. Calhoun; Tülay Adali; James J. Pekar; Godfrey D. Pearlson (NeuroImage, 2003)

Independent component analysis by complex nonlinearities. - Tülay Adali; Taehwan Kim 002; Vince D. Calhoun (ICASSP (5), 2004)

Independent Component Analysis of Complex-Valued Functional Magnetic Resonance Imaging Data by Complex Nonlinearities. - Vince D. Calhoun; Tülay Adali; Yi-Ou Li (ISBI, 2004)

fMRI analysis with the general linear model: removal of latency-induced amplitude bias by incorporation of hemodynamic derivative terms. - Vince D. Calhoun; Michael C. Stevens 001; Godfrey D. Pearlson; Kent A. Kiehl (NeuroImage, 2004)

Independent Component Analysis Applied to fMRI Data: A Generative Model for Validating Results. - Vince D. Calhoun; Godfrey D. Pearlson; Tülay Adali (J. VLSI Signal Process., 2004)

Comparison of blind source separation algorithms for FMRI using a new Matlab toolbox: GIFT. - Nicolle M. Correa; Tülay Adali; Yi-Ou Li; Vince D. Calhoun (ICASSP (5), 2005)

Feature-selective ICA and its convergence properties. - Yi-Ou Li; Tülay Adali; Vince D. Calhoun (ICASSP (5), 2005)

Bayesian blind source separation for brain imaging. - Hicham Snoussi; Vince D. Calhoun (ICIP (3), 2005)

Semi-blind ICA of fMRI: A method for utilizing hypothesis-derived time courses in a spatial ICA analysis. - Vince D. Calhoun; Tülay Adali; Michael C. Stevens 001; Kent A. Kiehl; James J. Pekar (NeuroImage, 2005)

An adaptive reflexive processing model of neurocognitive function: supporting evidence from a large scale (n = 100) fMRI study of an auditory oddball task. - Kent A. Kiehl; Michael C. Stevens 001; Kristin R. Laurens; Godfrey D. Pearlson; Vince D. Calhoun; Peter F. Liddle (NeuroImage, 2005)

Hemispheric differences in hemodynamics elicited by auditory oddball stimuli. - Michael C. Stevens 001; Vince D. Calhoun; Kent A. Kiehl (NeuroImage, 2005)

Regularized spectral matching for blind source separation. Application to fMRI imaging. - Hicham Snoussi; Vince D. Calhoun (IEEE Trans. Signal Process., 2005)

Functional Magnetic Resonance Imaging (fMRI). - Vince D. Calhoun (Neuroergonomics, 2006)

A feature-based approach to combine functional MRI, structural MRI and EEG brain imaging data. - Vince D. Calhoun; Tülay Adali; Jingyu Liu 001 (EMBC, 2006)

Functional Classification of Schizophrenia Using Feed Forward Neural Networks. - Madiha J. Jafri; Vince D. Calhoun (EMBC (Supplement), 2006)

Fusion of Multisubject Hemodynamic and Event-Related Potential Data Using Independent Component Analysis. - Vince D. Calhoun; Tülay Adali (ICASSP (5), 2006)

Sample dependence correction for order selection in fMRI analysis. - Yi-Ou Li; Tülay Adali; Vince D. Calhoun (ISBI, 2006)

Neuroanatomic Organization of Sound Memory in Humans. - Michael A. Kraut; Jeffery A. Pitcock; Vince D. Calhoun; Juan Li; Thomas Freeman; John Hart Jr. (J. Cogn. Neurosci., 2006)

Neuronal chronometry of target detection: Fusion of hemodynamic and event-related potential data. - Vince D. Calhoun; Tülay Adali; Godfrey D. Pearlson; Kent A. Kiehl (NeuroImage, 2006)

Complex Infomax: Convergence and Approximation of Infomax with Complex Nonlinearities. - Vince D. Calhoun; Tülay Adali (J. VLSI Signal Process., 2006)

A Maximal-Correlation Approach Using Ica for Testing Functional Network Connectivity Applied to Schizophrenia. - Madiha J. Jafri; Godfrey D. Pearlson; Vince D. Calhoun (ISBI, 2007)

Parallel Independent Component Analysis for Multimodal Analysis: Application to FMRI and EEG Data. - Jingyu Liu 001; Vince D. Calhoun (ISBI, 2007)

A Feature-Selective Independent Component Analysis Method for Functional MRI. - Yi-Ou Li; Tülay Adali; Vince D. Calhoun (Int. J. Biomed. Imaging, 2007)

A fast algorithm for one-unit ICA-R. - Qiu-Hua Lin; Yong-Rui Zheng; Fuliang Yin; Hualou Liang; Vince D. Calhoun (Inf. Sci., 2007)

Complex ICA of Brain Imaging Data [Life Sciences]. - Tülay Adali; Vince D. Calhoun (IEEE Signal Process. Mag., 2007)

Session TP2: Analysis methods for functional and structural brain imaging. - Vince D. Calhoun (ACSCC, 2008)

Optimal sampling geometries for TV-norm reconstruction of fMRI data. - Oliver M. Jeromin; Vince D. Calhoun; Marios S. Pattichis (ACSCC, 2008)

Exploration of the optimal group-discriminating features using CC-ICA. - Jing Sui; Vince D. Calhoun (ACSCC, 2008)

CCA for joint blind source separation of multiple datasets with application to group FMRI analysis. - Yi-Ou Li; Wei Wang 018; Tülay Adali; Vince D. Calhoun (ICASSP, 2008)

Extracting principle components for discriminant analysis of FMRI images. - Jingyu Liu 001; Lai Xu 002; Arvind Caprihan; Vince D. Calhoun (ICASSP, 2008)

A constrained coefficient ica algorithm for group difference enhancement. - Jing Sui; Jingyu Liu 001; Lei Wu 013; Andrew Michael; Lai Xu 002; Tülay Adali; Vince D. Calhoun (ICASSP, 2008)

On ICA of complex-valued fMRI: Advantages and order selection. - Wei Xiong; Yi-Ou Li; Hualiang Li; Tülay Adali; Vince D. Calhoun (ICASSP, 2008)

Source based morphometry using structural MRI phase images to identify sources of gray matter and white matter relative differences in schizophrenia versus controls. - Lai Xu 002; Jingyu Liu 001; Tülay Adali; Vince D. Calhoun (ICASSP, 2008)

Examining associations between FMRI and EEG data using canonical correlation analysis. - Nicolle M. Correa; Yi-Ou Li; Tülay Adali; Vince D. Calhoun (ISBI, 2008)

Group learning using contrast NMF : Application to functional and structural MRI of schizophrenia. - Vamsi K. Potluru; Vince D. Calhoun (ISCAS, 2008)

Introduction to the Issue on fMRI Analysis for Human Brain Mapping. - Tülay Adali; Z. Jane Wang 001; Martin J. McKeown; Philippe Ciuciu; Lars Kai Hansen; Andrzej Cichocki; Vincent D. Calhoun (IEEE J. Sel. Top. Signal Process., 2008)

Canonical Correlation Analysis for Feature-Based Fusion of Biomedical Imaging Modalities and Its Application to Detection of Associative Networks in Schizophrenia. - Nicolle M. Correa; Yi-Ou Li; Tülay Adali; Vincent D. Calhoun (IEEE J. Sel. Top. Signal Process., 2008)

Multimodal and Multi-Tissue Measures of Connectivity Revealed by Joint Independent Component Analysis. - Alexandre R. Franco; Josef Ling; Arvind Caprihan; Vincent D. Calhoun; Rex E. Jung; Gregory L. Heileman; Andy R. Mayer (IEEE J. Sel. Top. Signal Process., 2008)

Application of principal component analysis to distinguish patients with schizophrenia from healthy controls based on fractional anisotropy measurements. - Arvind Caprihan; Godfrey D. Pearlson; Vincent D. Calhoun (NeuroImage, 2008)

A projection pursuit algorithm to classify individuals using fMRI data: Application to schizophrenia. - Oguz Demirci; Vincent P. Clark; Vince D. Calhoun (NeuroImage, 2008)

A method for functional network connectivity among spatially independent resting-state components in schizophrenia. - Madiha J. Jafri; Godfrey D. Pearlson; Michael C. Stevens 001; Vince D. Calhoun (NeuroImage, 2008)

Hybrid ICA-Bayesian network approach reveals distinct effective connectivity differences in schizophrenia. - D. Kim; John Burge; Terran Lane; Godfrey D. Pearlson; Kent A. Kiehl; Vincent D. Calhoun (NeuroImage, 2008)

A method for multi-group inter-participant correlation: Abnormal synchrony in patients with schizophrenia during auditory target detection. - D. Kim; Godfrey D. Pearlson; Kent A. Kiehl; Edward J. Bedrick; Oguz Demirci; Vince D. Calhoun (NeuroImage, 2008)

Measuring brain connectivity: Diffusion tensor imaging validates resting state temporal correlations. - Pawel Skudlarski; Kanchana Jagannathan; Vince D. Calhoun; Michelle Hampson; Beata A. Skudlarska; Godfrey D. Pearlson (NeuroImage, 2008)

A Parallel Independent Component Analysis Approach to Investigate Genomic Influence on Brain Function. - Jingyu Liu 001; Oguz Demirci; Vincent D. Calhoun (IEEE Signal Process. Lett., 2008)

Fusion of fMRI, sMRI, and EEG data using canonical correlation analysis. - Nicolle M. Correa; Yi-Ou Li; Tülay Adali; Vince D. Calhoun (ICASSP, 2009)

An ICA Framework for Integrating fMRI, ERP and Genetic Data. - Vince D. Calhoun (ISBI, 2009)

Efficient Multiplicative Updates for Support Vector Machines. - Vamsi K. Potluru; Sergey M. Plis; Morten Mørup; Vincent D. Calhoun; Terran Lane (SDM, 2009)

Multiplicative updates For Non-Negative Kernel SVM - Vamsi K. Potluru; Sergey M. Plis; Morten Mørup; Vince D. Calhoun; Terran Lane (CoRR, 2009)

Mining the mind research network: a novel framework for exploring large scale, heterogeneous translational neuroscience research data sources. - Henry Jeremy Bockholt; Mark Scully; William Courtney; Srinivas Rachakonda; Adam Scott; Arvind Caprihan; Jill Fries; Ravi Kalyanam; Judith M. Segall; Raul de la Garza; Susan R. Lane; Vince D. Calhoun (Frontiers Neuroinformatics, 2009)

A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data. - Vince D. Calhoun; Jingyu Liu 001; Tülay Adali (NeuroImage, 2009)

Investigation of relationships between fMRI brain networks in the spectral domain using ICA and Granger causality reveals distinct differences between schizophrenia patients and healthy controls. - Oguz Demirci; Michael C. Stevens 001; Nancy Andreasen; Andrew Michael; Jingyu Liu 001; Tonya White; Godfrey D. Pearlson; Vincent P. Clark; Vince D. Calhoun (NeuroImage, 2009)

Biophysical modeling of phase changes in BOLD fMRI. - Zhaomei Feng; Arvind Caprihan; Krastan B. Blagoev; Vince D. Calhoun (NeuroImage, 2009)

Genetic determinants of target and novelty-related event-related potentials in the auditory oddball response. - Jingyu Liu 001; Kent A. Kiehl; Godfrey D. Pearlson; Nora I. Perrone-Bizzozero; Tom Eichele; Vince D. Calhoun (NeuroImage, 2009)

Age-related cognitive gains are mediated by the effects of white matter development on brain network integration. - Michael C. Stevens 001; Pawel Skudlarski; Godfrey D. Pearlson; Vince D. Calhoun (NeuroImage, 2009)

An ICA-based method for the identification of optimal FMRI features and components using combined group-discriminative techniques. - Jing Sui; Tülay Adali; Godfrey D. Pearlson; Vince D. Calhoun (NeuroImage, 2009)

Joint source based morphometry identifies linked gray and white matter group differences. - Lai Xu 002; Godfrey D. Pearlson; Vince D. Calhoun (NeuroImage, 2009)

Feature-Based Fusion of Medical Imaging Data. - Vince D. Calhoun; Tülay Adali (IEEE Trans. Inf. Technol. Biomed., 2009)

Joint blind source separation by multiset canonical correlation analysis. - Yi-Ou Li; Tülay Adali; Wei Wang 018; Vince D. Calhoun (IEEE Trans. Signal Process., 2009)

Correction of copy number variation data using principal component analysis. - Jiayu Chen 003; Jingyu Liu 001; Vince D. Calhoun (BIBM Workshops, 2010)

Fusion of concurrent single trial EEG data and fMRI data using multi-set canonical correlation analysis. - Nicolle M. Correa; Tom Eichele; Tülay Adali; Yi-Ou Li; Vince D. Calhoun (ICASSP, 2010)

Flexible complex ICA of fMRI data. - Hualiang Li; Tülay Adali; Nicolle M. Correa; Pedro A. Rodriguez; Vince D. Calhoun (ICASSP, 2010)

Independent subspace analysis with prior information for fMRI data. - Sai Ma; Xi-Lin Li; Nicolle M. Correa; Tülay Adali; Vince D. Calhoun (ICASSP, 2010)

Phase correction and denoising for ICA of complex FMRI data. - Pedro Rodriguez; Tülay Adali; Hualiang Li; Nicolle M. Correa; Vince D. Calhoun (ICASSP, 2010)

Permutations as Angular Data: Efficient Inference in Factorial Spaces. - Sergey M. Plis; Terran Lane; Vince D. Calhoun (ICDM, 2010)

MEG and fMRI fusion for nonlinear estimation of neural and BOLD signal changes. - Sergey M. Plis; Vince D. Calhoun; Tom Eichele; Michael P. Weisend; Terran Lane (Frontiers Neuroinformatics, 2010)

Changes in fMRI magnitude data and phase data observed in block-design and event-related tasks. - Sunil Kumar Arja; Zhaomei Feng; Zikuan Chen; Arvind Caprihan; Kent A. Kiehl; Tülay Adali; Vince D. Calhoun (NeuroImage, 2010)

Abnormal functional connectivity of default mode sub-networks in autism spectrum disorder patients. - Michal Assaf; Kanchana Jagannathan; Vince D. Calhoun; Laura Miller; Michael C. Stevens 001; Robert Sahl; Jacqueline G. O'Boyle; Robert T. Schultz; Godfrey D. Pearlson (NeuroImage, 2010)

Multi-set canonical correlation analysis for the fusion of concurrent single trial ERP and functional MRI. - Nicolle M. Correa; Tom Eichele; Tülay Adali; Yi-Ou Li; Vince D. Calhoun (NeuroImage, 2010)

The COMT Val108/158Met polymorphism and medial temporal lobe volumetry in patients with schizophrenia and healthy adults. - Stefan Ehrlich; Eric M. Morrow; Joshua L. Roffman; Stuart R. Wallace; Melissa Naylor; Henry Jeremy Bockholt; Antonia Lundquist; Anastasia Yendiki; Beng-Choon Ho; Tonya White; Dara S. Manoach; Vincent P. Clark; et al. (NeuroImage, 2010)

Anomalous neural circuit function in schizophrenia during a virtual Morris water task. - Bradley S. Folley; Robert Astur; Kanchana Jagannathan; Vince D. Calhoun; Godfrey D. Pearlson (NeuroImage, 2010)

Dynamic Granger causality based on Kalman filter for evaluation of functional network connectivity in fMRI data. - Martin Havlicek; Jirí Jan; Milan Brazdil; Vince D. Calhoun (NeuroImage, 2010)

A pilot multivariate parallel ICA study to investigate differential linkage between neural networks and genetic profiles in schizophrenia. - Shashwath A. Meda; Kanchana Jagannathan; Joel Gelernter; Vince D. Calhoun; Jingyu Liu 001; Michael C. Stevens 001; Godfrey D. Pearlson (NeuroImage, 2010)

Does function follow form?: Methods to fuse structural and functional brain images show decreased linkage in schizophrenia. - Andrew Michael; Stefi A. Baum; Tonya White; Oguz Demirci; Nancy Andreasen; Judith M. Segall; Rex E. Jung; Godfrey D. Pearlson; Vincent P. Clark; Randy L. Gollub; S. Charles Schulz; Joshua L. Roffman; et al. (NeuroImage, 2010)

A CCA + ICA based model for multi-task brain imaging data fusion and its application to schizophrenia. - Jing Sui; Tülay Adali; Godfrey D. Pearlson; Honghui Yang; Scott R. Sponheim; Tonya White; Vince D. Calhoun (NeuroImage, 2010)

Reactivity of hemodynamic responses and functional connectivity to different states of alpha synchrony: A concurrent EEG-fMRI study. - Lei Wu 013; Tom Eichele; Vince D. Calhoun (NeuroImage, 2010)

Identification of Imaging Biomarkers in Schizophrenia: A Coefficient-constrained Independent Component Analysis of the Mind Multi-site Schizophrenia Study. - Dae Il Kim; Jing Sui; Srinivas Rachakonda; Tonya White; Dara S. Manoach; Vincent P. Clark; Beng-Choon Ho; S. Charles Schulz; Vince D. Calhoun (Neuroinformatics, 2010)

Canonical Correlation Analysis for Data Fusion and Group Inferences. - Nicolle M. Correa; Tülay Adali; Yi-Ou Li; Vince D. Calhoun (IEEE Signal Process. Mag., 2010)

Automatic Bayesian Classification of Healthy Controls, Bipolar Disorder, and Schizophrenia Using Intrinsic Connectivity Maps From fMRI Data. - Juan Ignacio Arribas; Vince D. Calhoun; Tülay Adali (IEEE Trans. Biomed. Eng., 2010)

On entropy rate for the complex domain and its application to i.i.d. sampling. - Wei Xiong; Hualiang Li; Tülay Adali; Yi-Ou Li; Vince D. Calhoun (IEEE Trans. Signal Process., 2010)

Guest Editorial: Special Issue on Machine Learning for Signal Processing. - Ioannis Pitas; Vince D. Calhoun; Konstantinos I. Diamantaras (J. Signal Process. Syst., 2010)

Classification of Schizophrenia Patients with Combined Analysis of SNP and fMRI Data Based on Sparse Representation. - Dongdong Lin; Hongbao Cao; Yu-Ping Wang 002; Vince D. Calhoun (BIBM, 2011)

Functional network connectivity during rest and task: Comparison of healthy controls and schizophrenic patients. - Mohammad R. Arbabshirani; Vince D. Calhoun (EMBC, 2011)

A pipeline for copy number variation detection based on principal component analysis. - Jiayu Chen 003; Jingyu Liu 001; David Boutte; Vince D. Calhoun (EMBC, 2011)

Estimation of neuronal responses from fMRI data. - Martin Havlicek; Jirí Jan; Milan Brazdil; Vince D. Calhoun (EMBC, 2011)

Parallel independent component analysis using an optimized neurovascular coupling for concurrent EEG-fMRI sources. - Lei Wu 013; Tom Eichele; Vince D. Calhoun (EMBC, 2011)

Deconvolution of neuronal signal from hemodynamic response. - Martin Havlicek; Jirí Jan; Milan Brazdil; Vince D. Calhoun (ICASSP, 2011)

A quantitative analysis of noncircularity for complex-valued fMRI based on semi-blind ICA. - Jia-Chen Wang; Qiu-Hua Lin; Fengyu Cong; Vince D. Calhoun (iCAST, 2011)

Sparseness and a reduction from Totally Nonnegative Least Squares to SVM. - Vamsi K. Potluru; Sergey M. Plis; Shuang Luan; Vince D. Calhoun; Thomas P. Hayes (IJCNN, 2011)

ICA of fMRI data: Performance of three ICA algorithms and the importance of taking correlation information into account. - Wei Du; Hualiang Li; Xi-Lin Li; Vince D. Calhoun; Tülay Adali (ISBI, 2011)

Wavelet-based denoising and independent component analysis for improving multi-group inference in fMRI data. - Siddharth Khullar; Andrew Michael; Nicolle M. Correa; Tülay Adali; Stefi A. Baum; Vince D. Calhoun (ISBI, 2011)

Order detection for fMRI analysis: Joint estimation of downsampling depth and order by information theoretic criteria. - Xi-Lin Li; Sai Ma; Vince D. Calhoun; Tülay Adali (ISBI, 2011)

Hierarchical and graphical analysis of fMRI network connectivity in healthy and schizophrenic groups. - Sai Ma; Tom Eichele; Nicolle M. Correa; Vince D. Calhoun; Tülay Adali (ISBI, 2011)

Improved 3D wavelet-based de-noising of fMRI data. - Siddharth Khullar; Andrew Michael; Nicolle M. Correa; Tülay Adali; Stefi A. Baum; Vince D. Calhoun (Image Processing, 2011)

A new metric to measure shape differences in fMRI activity. - Siddharth Khullar; Andrew Michael; Nicolle M. Correa; Tülay Adali; Nathan D. Cahill; Stefi A. Baum; Vince D. Calhoun (Image Processing, 2011)

IVA for multi-subject FMRI analysis: A comparative study using a new simulation toolbox. - Josselin T. Dea; Matthew Anderson 001; Elena A. Allen; Vince D. Calhoun; Tülay Adali (MLSP, 2011)

Semi-blind kurtosis maximization algorithm applied to complex-valued fMRI data. - Qiu-Hua Lin; Jia-Cheng Wang; Xiao-Feng Gong; Jian-Lin Wu; Jun-Yu Chen; Vince D. Calhoun (MLSP, 2011)

Source-Based Morphometry Analysis of Group Differences in Fractional Anisotropy in Schizophrenia. - Arvind Caprihan; Christopher C. Abbott; Jeremy Yamamoto; Godfrey D. Pearlson; Nora I. Perrone-Bizzozero; Jing Sui; Vince D. Calhoun (Brain Connect., 2011)

On Network Derivation, Classification, and Visualization: A Response to Habeck and Moeller. - Erik B. Erhardt; Elena A. Allen; Eswar Damaraju; Vince D. Calhoun (Brain Connect., 2011)

Effective connectivity analysis of fMRI and MEG data collected under identical paradigms. - Sergey M. Plis; Michael P. Weisend; Eswar Damaraju; Tom Eichele; Andy R. Mayer; Vincent P. Clark; Terran Lane; Vince D. Calhoun (Comput. Biol. Medicine, 2011)

EEGIFT: Group Independent Component Analysis for Event-Related EEG Data. - Tom Eichele; Srinivas Rachakonda; Brage Brakedal; Rune Eikeland; Vince D. Calhoun (Comput. Intell. Neurosci., 2011)

COINS: An Innovative Informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets. - Adam Scott; William Courtney; Dylan Wood; Raul de la Garza; Susan R. Lane; Margaret D. King; Runtang Wang; Jody Roberts; Jessica A. Turner; Vince D. Calhoun (Frontiers Neuroinformatics, 2011)

The Clinical Assessment and Remote Administration Tablet. - Jessica A. Turner; Susan R. Lane; Henry Jeremy Bockholt; Vince D. Calhoun (Frontiers Neuroinformatics, 2011)

Directional Statistics on Permutations. - Sergey M. Plis; Stephen McCracken; Terran Lane; Vince D. Calhoun (AISTATS, 2011)

Characterization of groups using composite kernels and multi-source fMRI analysis data: Application to schizophrenia. - Eduardo Castro; Manel Martínez-Ramón; Godfrey D. Pearlson; Jing Sui; Vince D. Calhoun (NeuroImage, 2011)

Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering. - Martin Havlicek; Karl J. Friston; Jirí Jan; Milan Brazdil; Vince D. Calhoun (NeuroImage, 2011)

Wavelet-based fMRI analysis: 3-D denoising, signal separation, and validation metrics. - Siddharth Khullar; Andrew Michael; Nicolle M. Correa; Tülay Adali; Stefi A. Baum; Vince D. Calhoun (NeuroImage, 2011)

Discriminating schizophrenia and bipolar disorder by fusing fMRI and DTI in a multimodal CCA+ joint ICA model. - Jing Sui; Godfrey D. Pearlson; Arvind Caprihan; Tülay Adali; Kent A. Kiehl; Jingyu Liu 001; Jeremy Yamamoto; Vince D. Calhoun (NeuroImage, 2011)

Neuropsychological Testing and Structural Magnetic Resonance Imaging as Diagnostic Biomarkers Early in the Course of Schizophrenia and Related Psychoses. - Elissaios Karageorgiou; S. Charles Schulz; Randy L. Gollub; Nancy Andreasen; Beng-Choon Ho; John Lauriello; Vince D. Calhoun; Henry Jeremy Bockholt; Scott R. Sponheim; Apostolos P. Georgopoulos (Neuroinformatics, 2011)

A Computational Multiresolution BOLD fMRI Model. - Zikuan Chen; Vince D. Calhoun (IEEE Trans. Biomed. Eng., 2011)

Application of Independent Component Analysis With Adaptive Density Model to Complex-Valued fMRI Data. - Hualiang Li; Nicolle M. Correa; Pedro A. Rodriguez; Vince D. Calhoun; Tülay Adali (IEEE Trans. Biomed. Eng., 2011)

Automatic Identification of Functional Clusters in fMRI Data Using Spatial Dependence. - Sai Ma; Nicolle M. Correa; Xi-Lin Li; Tom Eichele; Vince D. Calhoun; Tülay Adali (IEEE Trans. Biomed. Eng., 2011)

Integrated Analysis of Gene Expression and Copy Number Data on Gene Shaving Using Independent Component Analysis. - Jinhua Sheng; Hong-Wen Deng; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE ACM Trans. Comput. Biol. Bioinform., 2011)

Correlated Noise: How it Breaks NMF, and What to Do About it. - Sergey M. Plis; Vamsi K. Potluru; Terran Lane; Vince D. Calhoun (J. Signal Process. Syst., 2011)

Quality Map Thresholding for De-noising of Complex-Valued fMRI Data and Its Application to ICA of fMRI. - Pedro A. Rodriguez; Nicolle M. Correa; Tom Eichele; Vince D. Calhoun; Tülay Adali (J. Signal Process. Syst., 2011)

Bio marker identification for diagnosis of schizophrenia with integrated analysis of fMRI and SNPs. - Hongbao Cao; Dongdong Lin; Junbo Duan; Yu-Ping Wang 002; Vince D. Calhoun (BIBM, 2012)

ICA order selection based on consistency: Application to genotype data. - Jiayu Chen 003; Vince D. Calhoun; Jingyu Liu 001 (EMBC, 2012)

Three-way FMRI-DTI-methylation data fusion based on mCCA+jICA and its application to schizophrenia. - Jing Sui; Hao He 002; Jingyu Liu 001; Qingbao Yu; Tülay Adali; Godfrey D. Pearlson; Vince D. Calhoun (EMBC, 2012)

The eighth annual MLSP competition: Overview. - Ken Montanez; Weifeng Liu 001; Vince D. Calhoun; Catherine Huang; Kenneth E. Hild II (MLSP, 2012)

Complex-valued analysis and visualization of fMRI data for event-related and block-design paradigms. - Pedro A. Rodriguez; Tülay Adali; Vince D. Calhoun (MLSP, 2012)

Volumetric BOLD fMRI simulation: from neurovascular coupling to multivoxel imaging. - Zikuan Chen; Vince D. Calhoun (BMC Medical Imaging, 2012)

Constrained Source-Based Morphometry Identifies Structural Networks Associated with Default Mode Network. - Li Luo; Lai Xu 002; Rex E. Jung; Godfrey D. Pearlson; Tülay Adali; Vince D. Calhoun (Brain Connect., 2012)

Correspondence between structure and function in the human brain at rest. - Judith M. Segall; Elena A. Allen; Rex E. Jung; Erik B. Erhardt; Sunil Kumar Arja; Kent A. Kiehl; Vince D. Calhoun (Frontiers Neuroinformatics, 2012)

Capturing inter-subject variability with group independent component analysis of fMRI data: A simulation study. - Elena A. Allen; Erik B. Erhardt; Yonghua Wei; Tom Eichele; Vince D. Calhoun (NeuroImage, 2012)

A selective review of simulated driving studies: Combining naturalistic and hybrid paradigms, analysis approaches, and future directions. - Vince D. Calhoun; Godfrey D. Pearlson (NeuroImage, 2012)

Multifaceted genomic risk for brain function in schizophrenia. - Jiayu Chen 003; Vince D. Calhoun; Godfrey D. Pearlson; Stefan Ehrlich; Jessica A. Turner; Beng-Choon Ho; Thomas H. Wassink; Andrew Michael; Jingyu Liu 001 (NeuroImage, 2012)

TDCS guided using fMRI significantly accelerates learning to identify concealed objects. - Vincent P. Clark; Brian A. Coffman; Andy R. Mayer; Michael P. Weisend; Terran Lane; Vince D. Calhoun; Elaine M. Raybourn; Christopher M. Garcia; Eric M. Wassermann (NeuroImage, 2012)

Joint ICA of ERP and fMRI during error-monitoring. - Bethany G. Edwards; Vince D. Calhoun; Kent A. Kiehl (NeuroImage, 2012)

SimTB, a simulation toolbox for fMRI data under a model of spatiotemporal separability. - Erik B. Erhardt; Elena A. Allen; Yonghua Wei; Tom Eichele; Vince D. Calhoun (NeuroImage, 2012)

Modulations of functional connectivity in the healthy and schizophrenia groups during task and rest. - Sai Ma; Vince D. Calhoun; Tom Eichele; Wei Du; Tülay Adali (NeuroImage, 2012)

A large scale multivariate parallel ICA method reveals novel imaging-genetic relationships for Alzheimer's disease in the ADNI cohort. - Shashwath A. Meda; Balaji Narayanan 002; Jingyu Liu 001; Nora I. Perrone-Bizzozero; Michael C. Stevens 001; Vince D. Calhoun; David C. Glahn; Li Shen 001; Shannon L. Risacher; Andrew J. Saykin; Godfrey D. Pearlson (NeuroImage, 2012)

Erratum to "A large scale multivariate parallel ICA method reveals novel imaging-genetic relationships for Alzheimer's Disease in the ADNI cohort" [Neuroimage 60/3(2012) 1608-1621]. - Shashwath A. Meda; Balaji Narayanan 002; Jingyu Liu 001; Nora I. Perrone-Bizzozero; Michael C. Stevens 001; Vince D. Calhoun; David C. Glahn; Li Shen 001; Shannon L. Risacher; Andrew J. Saykin; Godfrey D. Pearlson (NeuroImage, 2012)

De-noising, phase ambiguity correction and visualization techniques for complex-valued ICA of group fMRI data. - Pedro A. Rodriguez; Vince D. Calhoun; Tülay Adali (Pattern Recognit., 2012)

Group Study of Simulated Driving fMRI Data by Multiset Canonical Correlation Analysis. - Yi-Ou Li; Tom Eichele; Vince D. Calhoun; Tülay Adali (J. Signal Process. Syst., 2012)

Order Selection of the Linear Mixing Model for Complex-Valued FMRI Data. - Wei Xiong; Yi-Ou Li; Nicolle M. Correa; Xi-Lin Li; Vince D. Calhoun; Tülay Adali (J. Signal Process. Syst., 2012)

Network-based investigation of genetic modules associated with functional brain networks in schizophrenia. - Dongdong Lin; Hao He 002; Jingyao Li; Hong-Wen Deng; Vince D. Calhoun; Yu-Ping Wang 002 (BIBM, 2013)

Multi-subject fMRI data analysis: Shift-invariant tensor factorization vs. group independent component analysis. - Li-Dan Kuang; Qiu-Hua Lin; Xiao-Feng Gong; Jing Fan; Fengyu Cong; Vince D. Calhoun (ChinaSIP, 2013)

Characterization of connectivity dynamics in intrinsic brain networks. - Vince D. Calhoun; Maziar Yaesoubi; Barnaly Rashid; Robyn L. Miller (GlobalSIP, 2013)

MIGRAINE: MRI Graph Reliability Analysis and Inference for Connectomics. - William R. Gray Roncal; Zachary H. Koterba; Disa Mhembere; Dean M. Kleissas; Joshua T. Vogelstein; Randal C. Burns; Anita R. Bowles; Dimitrios K. Donavos; Sephira Ryman; Rex E. Jung; Lei Wu 013; Vince D. Calhoun; et al. (GlobalSIP, 2013)

Capturing group variability using IVA: A simulation study and graph-theoretical analysis. - Sai Ma; Ronald Phlypo; Vince D. Calhoun; Tülay Adali (ICASSP, 2013)

Sparse representation based biomarker selection for schizophrenia with integrated analysis of fMRI and SNP data. - Hongbao Cao; Junbo Duan; Dongdong Lin; Vincent D. Calhoun; Yu-Ping Wang 002 (ISBI, 2013)

Identifying genetic connections with brain functions in schizophrenia using group sparse canonical correlation analysis. - Dongdong Lin; Ji-Gang Zhang; Jingyao Li; Vince D. Calhoun; Yu-Ping Wang 002 (ISBI, 2013)

Group sparse canonical correlation analysis for genomic data integration. - Dongdong Lin; Ji-Gang Zhang; Jingyao Li; Vince D. Calhoun; Hong-Wen Deng; Yu-Ping Wang 002 (BMC Bioinform., 2013)

Impact of Analysis Methods on the Reproducibility and Reliability of Resting-State Networks. - Alexandre R. Franco; Maggie V. Mannell; Vince D. Calhoun; Andrew R. Mayer (Brain Connect., 2013)

Block Coordinate Descent for Sparse NMF - Vamsi K. Potluru; Sergey M. Plis; Jonathan Le Roux; Barak A. Pearlmutter; Vince D. Calhoun; Thomas P. Hayes (ICLR (Poster), 2013)

The spatiospectral characterization of brain networks: Fusing concurrent EEG spectra and fMRI maps. - David A. Bridwell; Lei Wu 013; Tom Eichele; Vince D. Calhoun (NeuroImage, 2013)

Guided exploration of genomic risk for gray matter abnormalities in schizophrenia using parallel independent component analysis with reference. - Jiayu Chen 003; Vince D. Calhoun; Godfrey D. Pearlson; Nora I. Perrone-Bizzozero; Jing Sui; Jessica A. Turner; Juan R. Bustillo; Stefan Ehrlich; Scott R. Sponheim; José M. Cañive; Beng-Choon Ho; Jingyu Liu 001 (NeuroImage, 2013)

Dynamic functional connectivity: Promise, issues, and interpretations. - R. Matthew Hutchison; Thilo Womelsdorf; Elena A. Allen; Peter A. Bandettini; Vince D. Calhoun; Maurizio Corbetta; Stefania Della Penna; Jeff H. Duyn; Gary H. Glover; Javier Gonzalez-Castillo; Daniel A. Handwerker; Shella D. Keilholz; et al. (NeuroImage, 2013)

Mind over chatter: Plastic up-regulation of the fMRI salience network directly after EEG neurofeedback. - Tomas Ros; Jean Théberge; Paul A. Frewen; Rosemarie Kluetsch; Maria Densmore; Vince D. Calhoun; Ruth A. Lanius (NeuroImage, 2013)

Using joint ICA to link function and structure using MEG and DTI in schizophrenia. - Julia M. Stephen; Brian A. Coffman; Rex E. Jung; Juan R. Bustillo; C. J. Aine; Vincent D. Calhoun (NeuroImage, 2013)

Three-way (N-way) fusion of brain imaging data based on mCCA + jICA and its application to discriminating schizophrenia. - Jing Sui; Hao He 002; Godfrey D. Pearlson; Tülay Adali; Kent A. Kiehl; Qingbao Yu; Vincent P. Clark; Eduardo Castro; Tonya White; Bryon A. Mueller; Beng-Choon Ho; Nancy Andreasen; et al. (NeuroImage, 2013)

Task-related concurrent but opposite modulations of overlapping functional networks as revealed by spatial ICA. - Jiansong Xu; Sheng Zhang 005; Vince D. Calhoun; John R. Monterosso; Chiang-shan Ray Li; Patrick D. Worhunsky; Michael C. Stevens 001; Godfrey D. Pearlson; Marc N. Potenza (NeuroImage, 2013)

The MCIC Collection: A Shared Repository of Multi-Modal, Multi-Site Brain Image Data from a Clinical Investigation of Schizophrenia. - Randy L. Gollub; Jody M. Shoemaker; Margaret D. King; Tonya White; Stefan Ehrlich; Scott R. Sponheim; Vincent P. Clark; Jessica A. Turner; Bryon A. Mueller; Vincent Magnotta; Daniel S. O'Leary; Beng-Choon Ho; et al. (Neuroinformatics, 2013)

Guest Editorial for Special Section on Multimodal Biomedical Imaging: Algorithms and Applications. - Tülay Adali; Z. Jane Wang 001; Vince D. Calhoun; Tom Eichele; Martin J. McKeown; Dimitri Van De Ville (IEEE Trans. Multim., 2013)

Data-driven fusion of EEG, functional and structural MRI: A comparison of two models. - Yuri Levin-Schwartz; Vince D. Calhoun; Tülay Adali (CISS, 2014)

Accurate classification of schizophrenia patients based on novel resting-state fMRI features. - Mohammad R. Arbabshirani; Eduardo Castro; Vince D. Calhoun (EMBC, 2014)

Detecting volumetric changes in fMRI connectivity networks in schizophrenia patients. - Mohammad R. Arbabshirani; Marios S. Pattichis; Alvaro Ulloa; Vince D. Calhoun (EMBC, 2014)

Identification of patterns of gray matter abnormalities in schizophrenia using source-based morphometry and bagging. - Eduardo Castro; Cota Navin Gupta; Manel Martínez-Ramón; Vince D. Calhoun; Mohammad R. Arbabshirani; Jessica A. Turner (EMBC, 2014)

Parallel ICA with multiple references: A semi-blind multivariate approach. - Jiayu Chen 003; Vince D. Calhoun; Alvaro E. Ulloa; Jingyu Liu 001 (EMBC, 2014)

Brain functional networks extraction based on fMRI artifact removal: Single subject and group approaches. - Yuhui Du; Elena A. Allen; Hao He 002; Jing Sui; Vince D. Calhoun (EMBC, 2014)

Exploring difference and overlap between schizophrenia, schizoaffective and bipolar disorders using resting-state brain functional networks. - Yuhui Du; Jingyu Liu 001; Jing Sui; Hao He 002; Godfrey D. Pearlson; Vince D. Calhoun (EMBC, 2014)

Higher dimensional analysis shows reduced dynamism of time-varying network connectivity in schizophrenia patients. - Robyn L. Miller; Maziar Yaesoubi; Vince D. Calhoun (EMBC, 2014)

Combination of FMRI-SMRI-EEG data improves discrimination of schizophrenia patients by ensemble feature selection. - Jing Sui; Eduardo Castro; Hao He 002; David A. Bridwell; Yuhui Du; Godfrey D. Pearlson; Tianzi Jiang; Vince D. Calhoun (EMBC, 2014)

Three-way parallel independent component analysis for imaging genetics using multi-objective optimization. - Alvaro Ulloa; Jingyu Liu 001; Victor M. Vergara; Jiayu Chen 003; Vince D. Calhoun; Marios S. Pattichis (EMBC, 2014)

A quasi-local method for instantaneous frequency estimation with application to structural magnetic resonance images. - Alvaro Ulloa; Paul Rodríguez 001; Jingyu Liu 001; Vince D. Calhoun; Marios S. Pattichis (EMBC, 2014)

Gradient artifact removal in concurrently acquired EEG data using independent vector analysis. - Partha Pratim Acharjee; Ronald Phlypo; Lei Wu 013; Vince D. Calhoun; Tülay Adali (ICASSP, 2014)

A novel approach for assessing reliability of ICA for FMRI analysis. - Wei Du; Sai Ma; Gengshen Fu; Vince D. Calhoun; Tülay Adali (ICASSP, 2014)

Performance of complex-valued ICA algorithms for fMRI analysis: Importance of taking full diversity into account. - Wei Du; Gengshen Fu; Vince D. Calhoun; Tülay Adali (ICIP, 2014)

Multidataset independent subspace analysis extends independent vector analysis. - Rogers F. Silva; Sergey M. Plis; Tülay Adali; Vince D. Calhoun (ICIP, 2014)

Semi-supervised learning of brain functional networks. - Yuhui Du; Jing Sui; Qingbao Yu; Hao He 002; Vince D. Calhoun (ISBI, 2014)

The tenth annual MLSP competition: Schizophrenia classification challenge. - Rogers F. Silva; Eduardo Castro; Cota Navin Gupta; Mustafa S. Çetin; Mohammad Arbabshirani; Vamsi K. Potluru; Sergey M. Plis; Vince D. Calhoun (MLSP, 2014)

A study of spatial variation in fMRI brain networks via independent vector analysis: Application to schizophrenia. - Shruti Gopal; Robyn L. Miller; Andrew Michael; Tülay Adali; Stefi A. Baum; Vince D. Calhoun (PRNI, 2014)

Higher dimensional fMRI connectivity dynamics show reduced dynamism in schizophrenia patients. - Robyn L. Miller; Maziar Yaesoubi; Vince D. Calhoun; Shruti Gopal (PRNI, 2014)

Save the Global: Global Signal Connectivity as a Tool for Studying Clinical Populations with Functional Magnetic Resonance Imaging. - Avital Hahamy-Dubossarsky; Vince D. Calhoun; Godfrey D. Pearlson; Michal Harel; Nachum Stern; Fanny Attar; Rafael Malach; Roy Salomon (Brain Connect., 2014)

Time of Acquisition and Network Stability in Pediatric Resting-State Functional Magnetic Resonance Imaging. - Tonya White; Ryan L. Muetzel; Marcus Schmidt; Sandra J. E. Langeslag; Vincent Jaddoe; Albert Hofman; Vince D. Calhoun; Frank C. Verhulst; Henning Tiemeier (Brain Connect., 2014)

Deep learning for neuroimaging: a validation study. - Sergey M. Plis; R. Devon Hjelm; Ruslan Salakhutdinov; Vince D. Calhoun (ICLR (Workshop Poster), 2014)

Automated collection of imaging and phenotypic data to centralized and distributed data repositories. - Margaret D. King; Dylan Wood; Brittny Miller; Ross Kelly; William Courtney; Drew Landis; Runtang Wang; Jessica A. Turner; Vince D. Calhoun (Frontiers Neuroinformatics, 2014)

A review of multivariate analyses in imaging genetics. - Jingyu Liu 001; Vince D. Calhoun (Frontiers Neuroinformatics, 2014)

Sharing privacy-sensitive access to neuroimaging and genetics data: a review and preliminary validation. - Anand D. Sarwate; Sergey M. Plis; Jessica A. Turner; Mohammad Arbabshirani; Vince D. Calhoun (Frontiers Neuroinformatics, 2014)

Harnessing modern web application technology to create intuitive and efficient data visualization and sharing tools. - Dylan Wood; Margaret D. King; Drew Landis; William Courtney; Runtang Wang; Ross Kelly; Jessica A. Turner; Vince D. Calhoun (Frontiers Neuroinformatics, 2014)

Correspondence between fMRI and SNP data by group sparse canonical correlation analysis. - Dongdong Lin; Vince D. Calhoun; Yu-Ping Wang 002 (Medical Image Anal., 2014)

Impact of autocorrelation on functional connectivity. - Mohammad R. Arbabshirani; Eswar Damaraju; Ronald Phlypo; Sergey M. Plis; Elena A. Allen; Sai Ma; Daniel H. Mathalon; Adrian Preda; Jatin G. Vaidya; Tülay Adali; Vince D. Calhoun (NeuroImage, 2014)

Neuroimage: Special issue on multimodal data fusion. - Vince D. Calhoun; Louis Lemieux (NeuroImage, 2014)

Sparse representation based biomarker selection for schizophrenia with integrated analysis of fMRI and SNPs. - Hongbao Cao; Junbo Duan; Dongdong Lin; Yin Yao Shugart; Vince D. Calhoun; Yu-Ping Wang 002 (NeuroImage, 2014)

A multiple kernel learning approach to perform classification of groups from complex-valued fMRI data analysis: Application to schizophrenia. - Eduardo Castro; Vanessa Gómez-Verdejo; Manel Martínez-Ramón; Kent A. Kiehl; Vince D. Calhoun (NeuroImage, 2014)

Thalamus and posterior temporal lobe show greater inter-network connectivity at rest and across sensory paradigms in schizophrenia. - Mustafa S. Çetin; Fletcher Christensen; Christopher C. Abbott; Julia M. Stephen; Andrew R. Mayer; José M. Cañive; Juan R. Bustillo; Godfrey D. Pearlson; Vince D. Calhoun (NeuroImage, 2014)

Functional connectivity in the developing brain: A longitudinal study from 4 to 9 months of age. - Eswar Damaraju; Arvind Caprihan; Jean R. Lowe; Elena A. Allen; Vince D. Calhoun; John P. Phillips (NeuroImage, 2014)

Bipolar and borderline patients display differential patterns of functional connectivity among resting state networks. - Pritha Das; Vince D. Calhoun; Gin S. Malhi (NeuroImage, 2014)

Restricted Boltzmann machines for neuroimaging: An application in identifying intrinsic networks. - R. Devon Hjelm; Vince D. Calhoun; Ruslan Salakhutdinov; Elena A. Allen; Tülay Adali; Sergey M. Plis (NeuroImage, 2014)

Functional and effective connectivity of stopping. - René J. Huster; Sergey M. Plis; Christina F. Lavallee; Vince D. Calhoun; Christoph S. Herrmann (NeuroImage, 2014)

Dynamic changes of spatial functional network connectivity in healthy individuals and schizophrenia patients using independent vector analysis. - Sai Ma; Vince D. Calhoun; Ronald Phlypo; Tülay Adali (NeuroImage, 2014)

High-order interactions observed in multi-task intrinsic networks are dominant indicators of aberrant brain function in schizophrenia. - Sergey M. Plis; Jing Sui; Terran Lane; Sushmita Roy; Vincent P. Clark; Vamsi K. Potluru; René J. Huster; Andrew Michael; Scott R. Sponheim; Michael P. Weisend; Vince D. Calhoun (NeuroImage, 2014)

A statistically motivated framework for simulation of stochastic data fusion models applied to multimodal neuroimaging. - Rogers F. Silva; Sergey M. Plis; Tülay Adali; Vince D. Calhoun (NeuroImage, 2014)

Function-structure associations of the brain: Evidence from multimodal connectivity and covariance studies. - Jing Sui; René J. Huster; Qingbao Yu; Judith M. Segall; Vince D. Calhoun (NeuroImage, 2014)

A three-way parallel ICA approach to analyze links among genetics, brain structure and brain function. - Victor M. Vergara; Alvaro Ulloa; Vince D. Calhoun; David Boutte; Jiayu Chen 003; Jingyu Liu 001 (NeuroImage, 2014)

Parallel group ICA for multimodal biomedical data analyses. - Jingyu Liu 001; Jiayu Chen 003; Vince D. Calhoun (BIBM, 2015)

SchizConnect: Virtual Data Integration in Neuroimaging. - José Luis Ambite; Marcelo Tallis; Kathryn I. Alpert; David B. Keator; Margaret D. King; Drew Landis; George Konstantinidis 001; Vince D. Calhoun; Steven G. Potkin; Jessica A. Turner; Lei Wang 032 (DILS, 2015)

Terminology Development Towards Harmonizing Multiple Clinical Neuroimaging Research Repositories. - Jessica A. Turner; Danielle Pasquerello; Matthew D. Turner; David B. Keator; Kathryn I. Alpert; Margaret D. King; Drew Landis; Vince D. Calhoun; Steven G. Potkin; Marcelo Tallis; José Luis Ambite; Lei Wang 032 (DILS, 2015)

Multimodal based classification of schizophrenia patients. - Mustafa S. Çetin; Jon M. Houck; Victor M. Vergara; Robyn L. Miller; Vince D. Calhoun (EMBC, 2015)

Large scale fusion of brain imaging modalities and features using Markov-style dynamics in a feature meta-space. - Robyn L. Miller; Victor M. Vergara; Vince D. Calhoun (EMBC, 2015)

The impact of data preprocessing in traumatic brain injury detection using functional magnetic resonance imaging. - Victor M. Vergara; Eswar Damaraju; Andrew B. Mayer; Robyn L. Miller; Mustafa S. Çetin; Vince D. Calhoun (EMBC, 2015)

Multivariate Fusion of EEG and Functional MRI Data Using ICA: Algorithm Choice and Performance Analysis. - Yuri Levin-Schwartz; Vince D. Calhoun; Tülay Adali (LVA/ICA, 2015)

Sensory load hierarchy-based classification of schizophrenia patients. - Mustafa S. Çetin; Julia M. Stephen; Vince D. Calhoun (ICIP, 2015)

Generation of synthetic structural magnetic resonance images for deep learning pre-training. - Eduardo Castro; Alvaro Ulloa; Sergey M. Plis; Jessica A. Turner; Vince D. Calhoun (ISBI, 2015)

Dynamic default mode network connectivity diminished in patients with schizophrenia. - Yuhui Du; Hao He 002; Lei Wu 013; Qingbao Yu; Jing Sui; Vince D. Calhoun (ISBI, 2015)

Identifying brain dynamic network states via GIG-ICA: Application to schizophrenia, bipolar and schizoaffective disorders. - Yuhui Du; Godfrey D. Pearlson; Hao He 002; Lei Wu 013; Jiayu Chen 003; Vince D. Calhoun (ISBI, 2015)

Detection of genetic factors associated with multiple correlated imaging phenotypes by a sparse regression model. - Dongdong Lin; Jingyao Li; Vince D. Calhoun; Yu-Ping Wang 002 (ISBI, 2015)

Classification of schizophrenia and bipolar patients using static and time-varying resting-state FMRI brain connectivity. - Barnaly Rashid; Mohammad R. Arbabshirani; Eswar Damaraju; Robyn L. Miller; Mustafa S. Çetin; Godfrey D. Pearlson; Vince D. Calhoun (ISBI, 2015)

Resting fMRI measures are associated with cognitive deficits in schizophrenia assessed by the MATRICS consensus cognitive battery. - Hao He 002; Juan R. Bustillo; Yuhui Du; Qingbao Yu; Thomas R. Jones; Tianzi Jiang; Vince D. Calhoun; Jing Sui (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2015)

Large scale collaboration with autonomy: Decentralized data ICA. - Bradley T. Baker; Rogers F. Silva; Vince D. Calhoun; Anand D. Sarwate; Sergey M. Plis (MLSP, 2015)

Deep independence network analysis of structural brain imaging: A simulation study. - Eduardo Castro; R. Devon Hjelm; Sergey M. Plis; Laurent Dinh; Jessica A. Turner; Vince D. Calhoun (MLSP, 2015)

Synthetic structural magnetic resonance image generator improves deep learning prediction of schizophrenia. - Alvaro Ulloa; Sergey M. Plis; Erik B. Erhardt; Vince D. Calhoun (MLSP, 2015)

Rate-Agnostic (Causal) Structure Learning. - Sergey M. Plis; David Danks; Cynthia Freeman; Vince D. Calhoun (NIPS, 2015)

Shapelet Ensemble for Multi-dimensional Time Series. - Mustafa S. Çetin; Abdullah Mueen; Vince D. Calhoun (SDM, 2015)

Iterative Refinement of Approximate Posterior for Training Directed Belief Networks. - R. Devon Hjelm; Kyunghyun Cho; Junyoung Chung; Ruslan Salakhutdinov; Vince D. Calhoun; Nebojsa Jojic (CoRR, 2015)

Lateralization of resting state networks and relationship to age and gender. - Oktay Agcaoglu; Robyn L. Miller; Andy R. Mayer; Kenneth Hugdahl; Vince D. Calhoun (NeuroImage, 2015)

Comparison of PCA approaches for very large group ICA. - Vince D. Calhoun; Rogers F. Silva; Tülay Adali; Srinivas Rachakonda (NeuroImage, 2015)

A group ICA based framework for evaluating resting fMRI markers when disease categories are unclear: application to schizophrenia, bipolar, and schizoaffective disorders. - Yuhui Du; Godfrey D. Pearlson; Jingyu Liu 001; Jing Sui; Qingbao Yu; Hao He 002; Eduardo Castro; Vince D. Calhoun (NeuroImage, 2015)

Dynamic coherence analysis of resting fMRI data to jointly capture state-based phase, frequency, and time-domain information. - Maziar Yaesoubi; Elena A. Allen; Robyn L. Miller; Vince D. Calhoun (NeuroImage, 2015)

Mutually temporally independent connectivity patterns: A new framework to study the dynamics of brain connectivity at rest with application to explain group difference based on gender. - Maziar Yaesoubi; Robyn L. Miller; Vince D. Calhoun (NeuroImage, 2015)

Assessing dynamic brain graphs of time-varying connectivity in fMRI data: Application to healthy controls and patients with schizophrenia. - Qingbao Yu; Erik B. Erhardt; Jing Sui; Yuhui Du; Hao He 002; R. Devon Hjelm; Mustafa S. Çetin; Srinivas Rachakonda; Robyn L. Miller; Godfrey D. Pearlson; Vince D. Calhoun (NeuroImage, 2015)

Multimodal Data Fusion Using Source Separation: Application to Medical Imaging. - Tülay Adali; Yuri Levin-Schwartz; Vince D. Calhoun (Proc. IEEE, 2015)

Multimodal Data Fusion Using Source Separation: Two Effective Models Based on ICA and IVA and Their Properties. - Tülay Adali; Yuri Levin-Schwartz; Vince D. Calhoun (Proc. IEEE, 2015)

Discriminating Bipolar Disorder From Major Depression Based on SVM-FoBa: Efficient Feature Selection With Multimodal Brain Imaging Data. - Nan-Feng Jie; Mao-Hu Zhu; Xiao-Ying Ma; Elizabeth A. Osuch; Michael Wammes; Jean Théberge; Huan-Dong Li; Yu Zhang; Tian-Zi Jiang; Jing Sui; Vince D. Calhoun (IEEE Trans. Auton. Ment. Dev., 2015)

Independent Vector Analysis for Gradient Artifact Removal in Concurrent EEG-fMRI Data. - Partha Pratim Acharjee; Ronald Phlypo; Lei Wu 013; Vince D. Calhoun; Tülay Adali (IEEE Trans. Biomed. Eng., 2015)

General Nonunitary Constrained ICA and its Application to Complex-Valued fMRI Data. - Pedro A. Rodriguez; Matthew Anderson 001; Vince D. Calhoun; Tülay Adali (IEEE Trans. Biomed. Eng., 2015)

Influence Function of Multiple Kernel Canonical Analysis to Identify Outliers in Imaging Genetics Data. - Md. Ashad Alam; Vince D. Calhoun; Yu-Ping Wang 002 (BCB, 2016)

Robust Kernel Canonical Correlation Analysis to Detect Gene-Gene Interaction for Imaging Genetics Data. - Md. Ashad Alam; Osamu Komori; Vince D. Calhoun; Yu-Ping Wang 002 (BCB, 2016)

Diagnosing schizophrenia by integrating genomic and imaging data through network fusion. - Su-Ping Deng; Dongdong Lin; Vince D. Calhoun; Yu-Ping Wang 002 (BIBM, 2016)

Schizophrenia genes discovery by mining the minimum spanning trees from multi-dimensional imaging genomic data integration. - Su-Ping Deng; Dongdong Lin; Vince D. Calhoun; Yu-Ping Wang 002 (BIBM, 2016)

Learning schizophrenia imaging genetics data via Multiple Kernel Canonical Correlation Analysis. - Owen Richfield; Md. Ashad Alam; Vince D. Calhoun; Yu-Ping Wang 002 (BIBM, 2016)

Privacy-preserving source separation for distributed data using independent component analysis. - Hafiz Imtiaz; Rogers F. Silva; Bradley T. Baker; Sergey M. Plis; Anand D. Sarwate; Vince D. Calhoun (CISS, 2016)

The chronnectome: Evaluating replicability of dynamic connectivity patterns in 7500 resting fMRI datasets. - Anees Abrol; Charlotte Chaze; Eswar Damaraju; Vince D. Calhoun (EMBC, 2016)

Predicting schizophrenia by fusing networks from SNPs, DNA methylation and fMRI data. - Su-Ping Deng; Dongdong Lin; Vince D. Calhoun; Yu-Ping Wang 002 (EMBC, 2016)

Integration of SNPs-FMRI-methylation data with sparse multi-CCA for schizophrenia study. - Wenxing Hu; Dongdong Lin; Vince D. Calhoun; Yu-Ping Wang 002 (EMBC, 2016)

Supervised multimodal fusion and its application in searching joint neuromarkers of working memory deficits in schizophrenia. - Shile Qi; Vince D. Calhoun; Theo G. M. van Erp; Eswar Damaraju; Juan R. Bustillo; Yuhui Du; Jessica A. Turner; Daniel H. Mathalon; Judith M. Ford; James Voyvodic; Bryon A. Mueller; Aysenil Belger; et al. (EMBC, 2016)

Randomness in resting state functional connectivity matrices. - Victor M. Vergara; Vince D. Calhoun (EMBC, 2016)

An adaptive fixed-point IVA algorithm applied to multi-subject complex-valued FMRI data. - Li-Dan Kuang; Qiu-Hua Lin; Xiao-Feng Gong; Fengyu Cong; Vince D. Calhoun (ICASSP, 2016)

Time-varying frequency modes of resting fMRI brain networks reveal significant gender differences. - Maziar Yaesoubi; Robyn L. Miller; Tülay Adali; Vince D. Calhoun (ICASSP, 2016)

Iterative Refinement of the Approximate Posterior for Directed Belief Networks. - R. Devon Hjelm; Russ Salakhutdinov; Kyunghyun Cho; Nebojsa Jojic; Vince D. Calhoun; Junyoung Chung (NIPS, 2016)

Multimodal fusion of brain structural and functional imaging with a deep neural machine translation approach. - Md Faijul Amin; Sergey M. Plis; Eswar Damaraju; R. Devon Hjelm; Kyunghyun Cho; Vince D. Calhoun (SSIAI, 2016)

Joint sparse canonical correlation analysis for detecting differential imaging genetics modules. - Jian Fang 001; Dongdong Lin; S. Charles Schulz; Zongben Xu; Vince D. Calhoun; Yu-Ping Wang 002 (Bioinform., 2016)

Intrinsic Connectivity Provides the Baseline Framework for Variability in Motor Performance: A Multivariate Fusion Analysis of Low- and High-Frequency Resting-State Oscillations and Antisaccade Performance. - Sharna D. Jamadar; Gary F. Egan; Vince D. Calhoun; Beth Johnson; Joanne Fielding (Brain Connect., 2016)

Variational Autoencoders for Feature Detection of Magnetic Resonance Imaging Data. - R. Devon Hjelm; Sergey M. Plis; Vince D. Calhoun (CoRR, 2016)

Recurrent Neural Networks for Spatiotemporal Dynamics of Intrinsic Networks from fMRI Data. - R. Devon Hjelm; Sergey M. Plis; Vince D. Calhoun (CoRR, 2016)

A Tool for Interactive Data Visualization: Application to Over 10, 000 Brain Imaging and Phantom MRI Data Sets. - Sandeep R. Panta; Runtang Wang; Jill Fries; Ravi Kalyanam; Nicole K. Speer; Marie T. Banich; Kent A. Kiehl; Margaret D. King; Michael P. Milham; Tor D. Wager; Jessica A. Turner; Sergey M. Plis; et al. (Frontiers Neuroinformatics, 2016)

Blind Source Separation for Unimodal and Multimodal Brain Networks: A Unifying Framework for Subspace Modeling. - Rogers F. Silva; Sergey M. Plis; Jing Sui; Marios S. Pattichis; Tülay Adali; Vince D. Calhoun (IEEE J. Sel. Top. Signal Process., 2016)

SchizConnect: Mediating neuroimaging databases on schizophrenia and related disorders for large-scale integration. - Lei Wang 032; Kathryn I. Alpert; Vince D. Calhoun; Derin J. Cobia; David B. Keator; Margaret D. King; Alexander Kogan; Drew Landis; Marcelo Tallis; Matthew D. Turner; Steven G. Potkin; Jessica A. Turner; et al. (NeuroImage, 2016)

The connectivity domain: Analyzing resting state fMRI data using feature-based data-driven and model-based methods. - Armin Iraji; Vince D. Calhoun; Natalie M. Wiseman; Esmaeil Davoodi-Bojd; Mohammad R. N. Avanaki; E. Mark Haacke; Zhifeng Kou (NeuroImage, 2016)

The Function Biomedical Informatics Research Network Data Repository. - David B. Keator; Theo G. M. van Erp; Jessica A. Turner; Gary H. Glover; Bryon A. Mueller; Thomas T. Liu; James T. Voyvodic; Jerod Rasmussen; Vince D. Calhoun; Hyo Jong Lee; Arthur W. Toga; Sarah C. McEwen; et al. (NeuroImage, 2016)

Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia. - JungHoe Kim; Vince D. Calhoun; Eunsoo Shim; Jong-Hwan Lee (NeuroImage, 2016)

COINS Data Exchange: An open platform for compiling, curating, and disseminating neuroimaging data. - Drew Landis; William Courtney; Christopher Dieringer; Ross Kelly; Margaret D. King; Brittny Miller; Runtang Wang; Dylan Wood; Jessica A. Turner; Vince D. Calhoun (NeuroImage, 2016)

Sample-poor estimation of order and common signal subspace with application to fusion of medical imaging data. - Yuri Levin-Schwartz; Yang Song 012; Peter J. Schreier; Vince D. Calhoun; Tülay Adali (NeuroImage, 2016)

Classification of schizophrenia and bipolar patients using static and dynamic resting-state fMRI brain connectivity. - Barnaly Rashid; Mohammad R. Arbabshirani; Eswar Damaraju; Mustafa S. Çetin; Robyn L. Miller; Godfrey D. Pearlson; Vince D. Calhoun (NeuroImage, 2016)

Genes influence the amplitude and timing of brain hemodynamic responses. - Zuyao Y. Shan; Anna A. E. Vinkhuyzen; Paul M. Thompson; Katie L. McMahon; Gabriëlla A. M. Blokland; Greig I. de Zubicaray; Vince D. Calhoun; Nicholas G. Martin; Peter M. Visscher; Margaret J. Wright; David C. Reutens (NeuroImage, 2016)

Neuroimaging measures of error-processing: Extracting reliable signals from event-related potentials and functional magnetic resonance imaging. - Vaughn R. Steele; Nathaniel E. Anderson; Eric D. Claus; Edward M. Bernat; Vikram Rao; Michal Assaf; Godfrey D. Pearlson; Vince D. Calhoun; Kent A. Kiehl (NeuroImage, 2016)

Cross-Frequency rs-fMRI Network Connectivity Patterns Manifest Differently for Schizophrenia Patients and Healthy Controls. - Robyn L. Miller; Maziar Yaesoubi; Vince D. Calhoun (IEEE Signal Process. Lett., 2016)

Time-Varying Brain Connectivity in fMRI Data: Whole-brain data-driven approaches for capturing and characterizing dynamic states. - Vince D. Calhoun; Tülay Adali (IEEE Signal Process. Mag., 2016)

A Method for Intertemporal Functional-Domain Connectivity Analysis: Application to Schizophrenia Reveals Distorted Directional Information Flow. - Robyn L. Miller; Victor M. Vergara; David B. Keator; Vince D. Calhoun (IEEE Trans. Biomed. Eng., 2016)

Brain language: Uncovering functional connectivity codes. - Victor M. Vergara; Vince D. Calhoun (ACSSC, 2017)

A graph theoretical approach for performance comparison of ICA for fMRI analysis. - Qunfang Long; Suchita Bhinge; Yuri Levin-Schwartz; Vince D. Calhoun; Tülay Adali (CISS, 2017)

ACMTF for fusion of multi-modal neuroimaging data and identification of biomarkers. - Evrim Acar; Yuri Levin-Schwartz; Vince D. Calhoun; Tülay Adali (EUSIPCO, 2017)

Non-orthogonal constrained independent vector analysis: Application to data fusion. - Suchita Bhinge; Qunfang Long; Yuri Levin-Schwartz; Zois Boukouvalas; Vince D. Calhoun; Tülay Adali (ICASSP, 2017)

A deep-learning approach to translate between brain structure and functional connectivity. - Vince D. Calhoun; Md Faijul Amin; R. Devon Hjelm; Eswar Damaraju; Sergey M. Plis (ICASSP, 2017)

Flexible large-scale fMRI analysis: A survey. - Seung-Jun Kim 002; Vince D. Calhoun; Tülay Adali (ICASSP, 2017)

Post-ICA phase de-noising for resting-state complex-valued FMRI data. - Li-Dan Kuang; Qiu-Hua Lin; Xiao-Feng Gong; Fengyu Cong; Vince D. Calhoun (ICASSP, 2017)

Two models for fusion of medical imaging data: Comparison and connections. - Yuri Levin-Schwartz; Vince D. Calhoun; Tülay Adali (ICASSP, 2017)

Identifying FMRI dynamic connectivity states using affinity propagation clustering method: Application to schizophrenia. - Mustafa S. Salman; Yuhui Du; Vince D. Calhoun (ICASSP, 2017)

Integration of multiple genomic imaging data for the study of schizophrenia using joint nonnegative matrix factorization. - Min Wang 022; Ting-Zhu Huang; Vince D. Calhoun; Jian Fang 001; Yu-Ping Wang 002 (ICASSP, 2017)

Decentralized independent vector analysis. - Nikolas P. Wojtalewicz; Rogers F. Silva; Vince D. Calhoun; Anand D. Sarwate; Sergey M. Plis (ICASSP, 2017)

Fused estimation of sparse connectivity patterns from rest fMRI. - Pascal Zille; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002 (ICASSP, 2017)

See without looking: joint visualization of sensitive multi-site datasets. - Debbrata K. Saha; Vince D. Calhoun; Sandeep R. Panta; Sergey M. Plis (IJCAI, 2017)

End-to-end learning of brain tissue segmentation from imperfect labeling. - Alex Fedorov; Jeremy Johnson; Eswar Damaraju; Alexei Ozerin; Vince D. Calhoun; Sergey M. Plis (IJCNN, 2017)

Cooperative learning: Decentralized data neural network. - Noah Lewis; Sergey M. Plis; Vince D. Calhoun (IJCNN, 2017)

Model order effects on independent vector analysis applied to complex-valued fMRI data. - Li-Dan Kuang; Qiu-Hua Lin; Xiao-Feng Gong; Yong-Gang Chen; Fengyu Cong; Vince D. Calhoun (ISBI, 2017)

Group information guided ICA shows more sensitivity to group differences than dual-regression. - Mustafa S. Salman; Yuhui Du; Eswar Damaraju; Qiu-Hua Lin; Vince D. Calhoun (ISBI, 2017)

Tensor-based fusion of EEG and FMRI to understand neurological changes in schizophrenia. - Evrim Acar; Yuri Levin-Schwartz; Vince D. Calhoun; Tülay Adali (ISCAS, 2017)

Comparison of Functional Network Connectivity and Granger Causality for Resting State fMRI Data. - Ce Zhang; Qiu-Hua Lin; Chao-Ying Zhang; Ying-Guang Hao; Xiao-Feng Gong; Fengyu Cong; Vince D. Calhoun (ISNN (2), 2017)

Discriminating bipolar disorder from major depression based on kernel SVM using functional independent components. - Shuang Gao; Elizabeth A. Osuch; Michael Wammes; Jean Théberge; Tian-Zi Jiang; Vince D. Calhoun; Jing Sui (MLSP, 2017)

Predicting individualized intelligence quotient scores using brainnetome-atlas based functional connectivity. - Rongtao Jiang; Shile Qi; Yuhui Du; Weizheng Yan; Vince D. Calhoun; Tianzi Jiang; Jing Sui (MLSP, 2017)

Discriminating schizophrenia from normal controls using resting state functional network connectivity: A deep neural network and layer-wise relevance propagation method. - Weizheng Yan; Sergey M. Plis; Vince D. Calhoun; Shengfeng Liu; Rongtao Jiang; Tian-Zi Jiang; Jing Sui (MLSP, 2017)

Enforcing Co-expression in Multimodal Regression Framework. - Pascal Zille; Vince D. Calhoun; Yu-Ping Wang 002 (PSB, 2017)

Time-Resolved Resting-State Functional Magnetic Resonance Imaging Analysis: Current Status, Challenges, and New Directions. - Shella D. Keilholz; César Caballero-Gaudes; Peter A. Bandettini; Gustavo Deco; Vince D. Calhoun (Brain Connect., 2017)

Almost instant brain atlas segmentation for large-scale studies. - Alex Fedorov; Eswar Damaraju; Vince D. Calhoun; Sergey M. Plis (CoRR, 2017)

COINSTAC: Decentralizing the future of brain imaging analysis. - Jing Ming; Eric Verner; Anand D. Sarwate; Ross Kelly; Cory Reed; Torran Kahleck; Rogers F. Silva; Sandeep R. Panta; Jessica A. Turner; Sergey M. Plis; Vince D. Calhoun (F1000Research, 2017)

Investigation of True High Frequency Electrical Substrates of fMRI-Based Resting State Networks Using Parallel Independent Component Analysis of Simultaneous EEG/fMRI Data. - Sreenath P. Kyathanahally; Yun Wang; Vince D. Calhoun; Gopikrishna Deshpande (Frontiers Neuroinformatics, 2017)

Replicability of time-varying connectivity patterns in large resting state fMRI samples. - Anees Abrol; Eswar Damaraju; Robyn L. Miller; Julia M. Stephen; Eric D. Claus; Andrew R. Mayer; Vince D. Calhoun (NeuroImage, 2017)

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls. - Mohammad R. Arbabshirani; Sergey M. Plis; Jing Sui; Vince D. Calhoun (NeuroImage, 2017)

Prediction of Individual Differences from Neuroimaging Data. - Vince D. Calhoun; Stephen M. Lawrie; Janaina Mourão Miranda; Klaas E. Stephan (NeuroImage, 2017)

Magnetoencephalographic and functional MRI connectomics in schizophrenia via intra- and inter-network connectivity. - 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 (NeuroImage, 2017)

Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks. - Hojin Jang; Sergey M. Plis; Vince D. Calhoun; Jong-Hwan Lee (NeuroImage, 2017)

Multimodal neural correlates of cognitive control in the Human Connectome Project. - Dov B. Lerman-Sinkoff; Jing Sui; Srinivas Rachakonda; Sridhar Kandala; Vince D. Calhoun; Deanna M. Barch (NeuroImage, 2017)

The real-time fMRI neurofeedback based stratification of Default Network Regulation Neuroimaging data repository. - 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; et al. (NeuroImage, 2017)

Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data. - Xing Meng; Rongtao Jiang; Dongdong Lin; Juan R. Bustillo; Thomas R. Jones; Jiayu Chen 003; Qingbao Yu; Yuhui Du; Yu Zhang; Tianzi Jiang; Jing Sui; Vince D. Calhoun (NeuroImage, 2017)

Chronnectomic patterns and neural flexibility underlie executive function. - Jason S. Nomi; Shruti Gopal Vij; Dina R. Dajani; Rosa Steimke; Eswar Damaraju; Srinivas Rachakonda; Vince D. Calhoun; Lucina Q. Uddin (NeuroImage, 2017)

Machine learning of structural magnetic resonance imaging predicts psychopathic traits in adolescent offenders. - Vaughn R. Steele; Vikram Rao; Vince D. Calhoun; Kent A. Kiehl (NeuroImage, 2017)

Alterations of resting state functional network connectivity in the brain of nicotine and alcohol users. - Victor M. Vergara; Jingyu Liu 001; Eric D. Claus; Kent Hutchison; Vince D. Calhoun (NeuroImage, 2017)

The effect of preprocessing pipelines in subject classification and detection of abnormal resting state functional network connectivity using group ICA. - Victor M. Vergara; Andrew R. Mayer; Eswar Damaraju; Kent Hutchison; Vince D. Calhoun (NeuroImage, 2017)

Regional and source-based patterns of [11C]-(+)-PHNO binding potential reveal concurrent alterations in dopamine D2 and D3 receptor availability in cocaine-use disorder. - 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 (NeuroImage, 2017)

Multimodal Neuroimaging in Schizophrenia: Description and Dissemination. - 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 001; Andy R. Mayer; et al. (Neuroinformatics, 2017)

A Realistic Framework for Investigating Decision Making in the Brain With High Spatiotemporal Resolution Using Simultaneous EEG/fMRI and Joint ICA. - Sreenath P. Kyathanahally; Ana Franco-Watkins; Xiaoxia Zhang; Vince D. Calhoun; Gopikrishna Deshpande (IEEE J. Biomed. Health Informatics, 2017)

Quantifying the Interaction and Contribution of Multiple Datasets in Fusion: Application to the Detection of Schizophrenia. - Yuri Levin-Schwartz; Vince D. Calhoun; Tülay Adali (IEEE Trans. Medical Imaging, 2017)

Weak Mutual Information Between Functional Domains in Schizophrenia. - Mustafa S. Salman; Victor M. Vergara; Eswar Damaraju; Vince D. Calhoun (ACSSC, 2018)

Exploring different impaired speed of genetic-related brain function and structures in schizophrenic progress using multimodal analysis. - Na Luo; Lin Tian; Vince D. Calhoun; Jiayu Chen 003; Dongdong Lin; Victor M. Vergara; Shuquan Rao; Fuquan Zhang 003; Jing Sui (EMBC, 2018)

Discriminating ADHD From Healthy Controls Using a Novel Feature Selection Method Based on Relative Importance and Ensemble Learning. - Dongren Yao; Xiaojie Guo; Qihua Zhao; Lu Liu; Qingjiu Cao; Yufeng Wang; Vince D. Calhoun; Li Sun; Jing Sui (EMBC, 2018)

Abnormal Dynamic Functional Network Connectivity and Graph Theoretical Analysis in Major Depressive Disorder. - 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; et al. (EMBC, 2018)

Consecutive Independence and Correlation Transform for Multimodal Fusion: Application to Eeg and Fmri Data. - Mohammad A. B. S. Akhonda; Yuri Levin-Schwartz; Suchita Bhinge; Vince D. Calhoun; Tülay Adali (ICASSP, 2018)

IVA-Based Spatio-Temporal Dynamic Connectivity Analysis in Large-Scale FMRI Data. - Suchita Bhinge; Vince D. Calhoun; Tülay Adali (ICASSP, 2018)

Evaluating Models of Dynamic Functional Connectivity Using Predictive Classification Accuracy. - Søren Føns Vind Nielsen; Yuri Levin-Schwartz; Diego Vidaurre; Tülay Adali; Vince D. Calhoun; Kristoffer Hougaard Madsen; Lars Kai Hansen; Morten Mørup (ICASSP, 2018)

Detection of differentially developed functional connectivity patterns in adolescents based on tensor discriminative analysis. - Jian Fang 001; Julia M. Stephen; Tony W. Wilson; Vince D. Calhoun; Yu-Ping Wang 002 (ISBI, 2018)

Integration of network topological features and graph Fourier transform for fMRI data analysis. - Junqi Wang 001; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002 (ISBI, 2018)

High dimensional latent Gaussian copula model for mixed data in imaging genetics. - Aiying Zhang; Jian Fang 001; Vince D. Calhoun; Yu-Ping Wang 002 (ISBI, 2018)

Brain functional mapping and network connectivity of reconstructed susceptibility data. - Zikuan Chen; Vince D. Calhoun (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2018)

Multi-modal Brain Connectivity Study Using Deep Collaborative Learning. - Wenxing Hu; Biao Cai; Vince D. Calhoun; Yu-Ping Wang 002 (GRAIL/Beyond-MIC@MICCAI, 2018)

Dynamic Whole Brain Polarity Regimes Strongly Distinguish Controls from Schizophrenia Patients. - Robyn L. Miller; Vince D. Calhoun (PRNI, 2018)

Graph Modularity and Randomness Measures : A Comparative Study. - Victor M. Vergara; Qingbao Yu; Vince D. Calhoun (SSIAI, 2018)

In-between and cross-frequency dependence-based summarization of resting-state fMRI data. - Maziar Yaesoubi; Rogers F. Silva; Vince D. Calhoun (SSIAI, 2018)

Whole-Brain Connectivity in a Large Study of Huntington's Disease Gene Mutation Carriers and Healthy Controls. - Flor A. Espinoza; Jessica A. Turner; Victor M. Vergara; Robyn L. Miller; Eva Mennigen; Jingyu Liu 001; Maria B. Misiura; Jennifer Ciarochi; Hans J. Johnson; Jeffrey D. Long; Henry Jeremy Bockholt; Vincent A. Magnotta; et al. (Brain Connect., 2018)

Improving Classification Rate of Schizophrenia Using a Multimodal Multi-Layer Perceptron Model with Structural and Functional MR. - Alvaro Ulloa; Sergey M. Plis; Vince D. Calhoun (CoRR, 2018)

Identifying outliers using multiple kernel canonical correlation analysis with application to imaging genetics. - Md. Ashad Alam; Vince D. Calhoun; Yu-Ping Wang 002 (Comput. Stat. Data Anal., 2018)

Decentralized Analysis of Brain Imaging Data: Voxel-Based Morphometry and Dynamic Functional Network Connectivity. - Harshvardhan Gazula; Bradley T. Baker; Eswar Damaraju; Sergey M. Plis; Sandeep R. Panta; Rogers F. Silva; Vince D. Calhoun (Frontiers Neuroinformatics, 2018)

Sparsity and Independence: Balancing Two Objectives in Optimization for Source Separation with Application to fMRI Analysis. - Zois Boukouvalas; Yuri Levin-Schwartz; Vince D. Calhoun; Tülay Adali (J. Frankl. Inst., 2018)

Corrigendum to "Lateralization of resting state networks and relationship to age and gender" [NeuroImage 104 (2015) 310-325]. - Oktay Agcaoglu; Robyn L. Miller; Andrew R. Mayer; Kenneth Hugdahl; Vince D. Calhoun (NeuroImage, 2018)

Dynamic functional connectivity impairments in early schizophrenia and clinical high-risk for psychosis. - Yuhui Du; Susanna Fryer; Zening Fu; Dongdong Lin; Jing Sui; Jiayu Chen 003; Eswar Damaraju; Eva Mennigen; Barbara Stuart; Rachel L. Loewy; Daniel H. Mathalon; Vince D. Calhoun (NeuroImage, 2018)

Characterizing dynamic amplitude of low-frequency fluctuation and its relationship with dynamic functional connectivity: An application to schizophrenia. - Zening Fu; Yiheng Tu; Xin Di; Yuhui Du; Godfrey D. Pearlson; Jessica A. Turner; Bharat B. Biswal; Zhiguo Zhang 001; Vince D. Calhoun (NeuroImage, 2018)

Connectome-based individualized prediction of temperament trait scores. - 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 (NeuroImage, 2018)

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. - 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 (NeuroImage, 2018)

An approach to directly link ICA and seed-based functional connectivity: Application to schizophrenia. - Lei Wu 013; Arvind Caprihan; Juan R. Bustillo; Andy R. Mayer; Vince D. Calhoun (NeuroImage, 2018)

Whole-brain connectivity dynamics reflect both task-specific and individual-specific modulation: A multitask study. - Hua Xie; Vince D. Calhoun; Javier Gonzalez-Castillo; Eswar Damaraju; Robyn L. Miller; Peter A. Bandettini; Sunanda Mitra (NeuroImage, 2018)

The Dangers of Following Trends in Research: Sparsity and Other Examples of Hammers in Search of Nails. - Tülay Adali; H. Joel Trussell; Lars Kai Hansen; Vince D. Calhoun (Proc. IEEE, 2018)

Application of Graph Theory to Assess Static and Dynamic Brain Connectivity: Approaches for Building Brain Graphs. - Qingbao Yu; Yuhui Du; Jiayu Chen 003; Jing Sui; Tülay Adali; Godfrey D. Pearlson; Vince D. Calhoun (Proc. IEEE, 2018)

Adaptive Sparse Multiple Canonical Correlation Analysis With Application to Imaging (Epi)Genomics Study of Schizophrenia. - Wenxing Hu; Dongdong Lin; Shaolong Cao; Jingyu Liu 001; Jiayu Chen 003; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Biomed. Eng., 2018)

Integrating Imaging Genomic Data in the Quest for Biomarkers of Schizophrenia Disease. - Su-Ping Deng; Wenxing Hu; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE ACM Trans. Comput. Biol. Bioinform., 2018)

Fast and Accurate Detection of Complex Imaging Genetics Associations Based on Greedy Projected Distance Correlation. - Jian Fang 001; Chao Xu 014; Pascal Zille; Dongdong Lin; Hong-Wen Deng; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Medical Imaging, 2018)

Estimation of Dynamic Sparse Connectivity Patterns From Resting State fMRI. - Biao Cai; Pascal Zille; Julia M. Stephen; Tony W. Wilson; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Medical Imaging, 2018)

FDR-Corrected Sparse Canonical Correlation Analysis With Applications to Imaging Genomics. - Alexej Gossmann; Pascal Zille; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Medical Imaging, 2018)

Multimodal Fusion With Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia. - Shile Qi; Vince D. Calhoun; Theo G. M. van Erp; Juan R. Bustillo; Eswar Damaraju; Jessica A. Turner; Yuhui Du; Jian Yang 009; Jiayu Chen 003; Qingbao Yu; Daniel H. Mathalon; Judith M. Ford; et al. (IEEE Trans. Medical Imaging, 2018)

Fused Estimation of Sparse Connectivity Patterns From Rest fMRI - Application to Comparison of Children and Adult Brains. - Pascal Zille; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002 (IEEE Trans. Medical Imaging, 2018)

Enforcing Co-Expression Within a Brain-Imaging Genomics Regression Framework. - Pascal Zille; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Medical Imaging, 2018)

Discriminating Bipolar Disorder from Major Depression using Whole-Brain Functional Connectivity: a Feature Selection Analysis with SVM-FoBa Algorithm. - Nan-Feng Jie; Elizabeth A. Osuch; Mao-Hu Zhu; Michael Wammes; Xiao-Ying Ma; Tian-Zi Jiang; Jing Sui; Vince D. Calhoun (J. Signal Process. Syst., 2018)

Prediction of Progression to Alzheimer's disease with Deep InfoMax. - Alex Fedorov; R. Devon Hjelm; Anees Abrol; Zening Fu; Yuhui Du; Sergey M. Plis; Vince D. Calhoun (BHI, 2019)

Disjoint Subspaces for Common and Distinct Component Analysis: Application to Task FMRI Data. - Mohammad A. B. S. Akhonda; Qunfang Long; Suchita Bhinge; Vince D. Calhoun; Tülay Adali (CISS, 2019)

C-ICT for Discovery of Multiple Associations in Multimodal Imaging Data: Application to Fusion of fMRI and DTI Data. - Chunying Jia; Mohammad A. B. S. Akhonda; Qunfang Long; Vince D. Calhoun; Shari Waldstein; Tülay Adali (CISS, 2019)

Multimodal Data Fusion of Deep Learning and Dynamic Functional Connectivity Features to Predict Alzheimer's Disease Progression. - Anees Abrol; Zening Fu; Yuhui Du; Vince D. Calhoun (EMBC, 2019)

Diagnostic and Prognostic Classification of Brain Disorders Using Residual Learning on Structural MRI Data. - Anees Abrol; Hooman Rokham; Vince D. Calhoun (EMBC, 2019)

Selection of Efficient Clustering Index to Estimate the Number of Dynamic Brain States from Functional Network Connectivity. - Victor M. Vergara; Anees Abrol; Flor A. Espinoza; Vince D. Calhoun (EMBC, 2019)

Sparse Infomax Based on Hoyer Projection and its Application to Simulated Structural MRI and SNP Data. - Kuaikuai Duan; Rogers F. Silva; Jiayu Chen 003; Dongdong Lin; Vince D. Calhoun; Jingyu Liu 001 (ISBI, 2019)

Using Gradient as a New Metric for Dynamic Connectivity Estimation from Resting fMRI Data. - Ashkan Faghiri; Julia M. Stephen; Yu-Ping Wang 002; Tony W. Wilson; Vince D. Calhoun (ISBI, 2019)

Multimodal Neuroimaging Patterns Associated with Social Responsiveness Impairment in Autism: A Replication Study. - Tiantian Li; Zening Fu; Xia Liu; Shile Qi; Vince D. Calhoun; Jing Sui (ISBI, 2019)

Classification As a Criterion to Select Model Order For Dynamic Functional Connectivity States in Rest-fMRI Data. - Debbrata K. Saha; Anees Abrol; Eswar Damaraju; Barnaly Rashid; Sergey M. Plis; Vince D. Calhoun (ISBI, 2019)

ADHD Classification Within and Cross Cohort Using an Ensembled Feature Selection Framework. - Dongren Yao; Hailun Sun; Xiaojie Guo; Vince D. Calhoun; Li Sun; Jing Sui (ISBI, 2019)

Classification of Schizophrenia Patients and Healthy Controls Using ICA of Complex-Valued fMRI Data and Convolutional Neural Networks. - Yue Qiu; Qiu-Hua Lin; Li-Dan Kuang; Wen-Da Zhao; Xiao-Feng Gong; Fengyu Cong; Vince D. Calhoun (ISNN (2), 2019)

Extraction of co-expressed discriminative features of Schizophrenia in imaging epigenetics framework. - Yuntong Bai; Pascal Zille; Vince D. Calhoun; Yu-Ping Wang 002 (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2019)

Phase fMRI reveals sparser function connectivity than magnitude fMRI. - Zikuan Chen; Vince D. Calhoun (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2019)

Improved estimation of dynamic connectivity from resting-state fMRI data. - Biao Cai; Julia M. Stephen; Tony W. Wilson; Vince D. Calhoun; Yu-Ping Wang 002 (Image Processing, 2019)

Brain Development Includes Linear and Multiple Nonlinear Trajectories: A Cross-Sectional Resting-State Functional Magnetic Resonance Imaging Study. - Ashkan Faghiri; Julia M. Stephen; Yu-Ping Wang 002; Tony W. Wilson; Vince D. Calhoun (Brain Connect., 2019)

Transient Patterns of Functional Dysconnectivity in Clinical High Risk and Early Illness Schizophrenia Individuals Compared with Healthy Controls. - Eva Mennigen; Susanna Fryer; Barnaly Rashid; Eswar Damaraju; Yuhui Du; Rachel L. Loewy; Barbara Stuart; Vince D. Calhoun; Daniel H. Mathalon (Brain Connect., 2019)

Dynamic Functional Network Connectivity in Schizophrenia with Magnetoencephalography and Functional Magnetic Resonance Imaging: Do Different Timescales Tell a Different Story? - Lori Sanfratello; Jon M. Houck; Vince D. Calhoun (Brain Connect., 2019)

Improved Differentially Private Decentralized Source Separation for fMRI Data. - Hafiz Imtiaz; Jafar Mohammadi; Rogers F. Silva; Bradley T. Baker; Sergey M. Plis; Anand D. Sarwate; Vince D. Calhoun (CoRR, 2019)

Learnt dynamics generalizes across tasks, datasets, and populations. - Usman Mahmood; Md Mahfuzur Rahman; Alex Fedorov; Zening Fu; Vince D. Calhoun; Sergey M. Plis (CoRR, 2019)

Robust kernel canonical correlation analysis to detect gene-gene co-associations: A case study in genetics. - Md. Ashad Alam; Osamu Komori; Hong-Wen Deng; Vince D. Calhoun; Yu-Ping Wang 002 (J. Bioinform. Comput. Biol., 2019)

Decentralized temporal independent component analysis: Leveraging fMRI data in collaborative settings. - Bradley T. Baker; Anees Abrol; Rogers F. Silva; Eswar Damaraju; Anand D. Sarwate; Vince D. Calhoun; Sergey M. Plis (NeuroImage, 2019)

Neural dynamics of verbal working memory processing in children and adolescents. - Christine M. Embury; Alex I. Wiesman; Amy L. Proskovec; Mackenzie S. Mills; Elizabeth Heinrichs-Graham; Yu-Ping Wang 002; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson (NeuroImage, 2019)

Transient increased thalamic-sensory connectivity and decreased whole-brain dynamism in autism. - Zening Fu; Yiheng Tu; Xin Di; Yuhui Du; Jing Sui; Bharat B. Biswal; Zhiguo Zhang 001; Nina de Lacy; Vincent D. Calhoun (NeuroImage, 2019)

Sex-related differences in intrinsic brain dynamism and their neurocognitive correlates. - Nina de Lacy; Elizabeth McCauley; J. Nathan Kutz; Vince D. Calhoun (NeuroImage, 2019)

Association between the oral microbiome and brain resting state connectivity in smokers. - Dongdong Lin; Kent Hutchison; Salvador Portillo; Victor Vegara; Jarrod M. Ellingson; Jingyu Liu 001; Kenneth S. Krauter; Amanda Carroll-Portillo; Vince D. Calhoun (NeuroImage, 2019)

The inner fluctuations of the brain in presymptomatic Frontotemporal Dementia: The chronnectome fingerprint. - 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; et al. (NeuroImage, 2019)

A framework for linking resting-state chronnectome/genome features in schizophrenia: A pilot study. - Barnaly Rashid; Jiayu Chen 003; Ishtiaque Rashid; Eswar Damaraju; Jingyu Liu 001; Robyn L. Miller; Oktay Agcaoglu; Theo G. M. van Erp; Kelvin O. Lim; Jessica A. Turner; Daniel H. Mathalon; Judith M. Ford; et al. (NeuroImage, 2019)

The developmental trajectory of sensorimotor cortical oscillations. - Michael P. Trevarrow; Max J. Kurz; Timothy J. McDermott; Alex I. Wiesman; Mackenzie S. Mills; Yu-Ping Wang 002; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson (NeuroImage, 2019)

Efficacy of different dynamic functional connectivity methods to capture cognitively relevant information. - Hua Xie; Charles Y. Zheng; Daniel A. Handwerker; Peter A. Bandettini; Vince D. Calhoun; Sunanda Mitra; Javier Gonzalez-Castillo (NeuroImage, 2019)

Scanning the Issue. - Ian F. Akyildiz; Massimiliano Pierobon; Sasitharan Balasubramaniam; Jiankang Zhang 001; Taihai Chen; Shida Zhong; Jingjing Wang 001; Wenbo Zhang 011; Xin Zuo; Robert G. Maunder; Lajos Hanzo; Jiayu Chen 003; et al. (Proc. IEEE, 2019)

Translational Potential of Neuroimaging Genomic Analyses to Diagnosis and Treatment in Mental Disorders. - Jiayu Chen 003; Jingyu Liu 001; Vince D. Calhoun (Proc. IEEE, 2019)

Capturing Dynamic Connectivity From Resting State fMRI Using Time-Varying Graphical Lasso. - Biao Cai; Gemeng Zhang; Aiying Zhang; Julia M. Stephen; Tony W. Wilson; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Biomed. Eng., 2019)

Deep Collaborative Learning With Application to the Study of Multimodal Brain Development. - Wenxing Hu; Biao Cai; Aiying Zhang; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Biomed. Eng., 2019)

Alternating Diffusion Map Based Fusion of Multimodal Brain Connectivity Networks for IQ Prediction. - Li Xiao 002; Julia M. Stephen; Tony W. Wilson; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Biomed. Eng., 2019)

Aberrant Brain Connectivity in Schizophrenia Detected via a Fast Gaussian Graphical Model. - Aiying Zhang; Jian Fang 001; Faming Liang; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE J. Biomed. Health Informatics, 2019)

Extraction of Time-Varying Spatiotemporal Networks Using Parameter-Tuned Constrained IVA. - Suchita Bhinge; Rami Mowakeaa; Vince D. Calhoun; Tülay Adali (IEEE Trans. Medical Imaging, 2019)

A deep learning fusion model for brain disorder classification: Application to distinguishing schizophrenia and autism spectrum disorder. - Yuhui Du; Bang Li; Yuliang Hou; Vince D. Calhoun (BCB, 2020)

Varying Information Complexity in Functional Domain Interactions in Schizophrenia. - Ishaan Batta; Anees Abrol; Zening Fu; Vince D. Calhoun (BIBE, 2020)

Time-varying Graphs: A Method to Identify Abnormal Integration and Disconnection in Functional Brain Connectivity with Application to Schizophrenia. - 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; et al. (BIBE, 2020)

Individualized Prediction of Brain Network Interactions using Deep Siamese Networks. - Reihaneh Hassanzadeh; Vince D. Calhoun (BIBE, 2020)

BPARC: A novel spatio-temporal (4D) data-driven brain parcellation scheme based on deep residual networks. - Behnam Kazemivash; Vince D. Calhoun (BIBE, 2020)

Visualizing functional network connectivity difference between middle adult and older subjects using an explainable machine-learning method. - Mohammad S. Eslampanah Sendi; Ji Ye Chun; Vince D. Calhoun (BIBE, 2020)

Fully automated ordering and labeling of ICA components. - Mustafa S. Salman; Tor D. Wager; Eswar Damaraju; Anees Abrol; Vince D. Calhoun (BIBM, 2020)

Visualizing Functional Network Connectivity Difference between Healthy Control and Major Depressive Disorder Using an Explainable Machine-learning Method. - Ji Ye Chun; Mohammad S. Eslampanah Sendi; Jing Sui; Dongmei Zhi; Vince D. Calhoun (EMBC, 2020)

aNy-way Independent Component Analysis. - Kuaikuai Duan; Vince D. Calhoun; Jingyu Liu 001; Rogers F. Silva (EMBC, 2020)

Aberrant Functional Network Connectivity Transition Probability in Major Depressive Disorder. - 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; et al. (EMBC, 2020)

Tracing Network Evolution Using The Parafac2 Model. - Marie Roald; Suchita Bhinge; Chunying Jia; Vince D. Calhoun; Tülay Adali; Evrim Acar (ICASSP, 2020)

Functional Multi-Connectivity: A Novel Approach To Assess Multi-Way Entanglement Between Networks and Voxels. - Armin Iraji; Noah Lewis; Ashkan Faghiri; Zening Fu; Thomas DeRamus; Anees Abrol; Shile Qi; Vince D. Calhoun (ISBI, 2020)

Integration of multi-task fMRI for cognitive study by structure-enforced collaborative regression. - Yuntong Bai; Vince D. Calhoun; Yu-Ping Wang 002 (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2020)

Reduced sine hyperbolic polynomial model for brain neuro-developmental analysis. - Peyman Hosseinzadeh Kassani; Vince D. Calhoun; Yu-Ping Wang 002 (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2020)

Identification of dementia subtypes based on a diffusion MRI multi-model approach. - Rajikha Raja; Arvind Caprihan; Gary A. Rosenberg; Vince D. Calhoun (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2020)

Graph Laplacian learning based Fourier Transform for brain network analysis with resting state fMRI. - Junqi Wang 001; Julia M. Stephen; Tony W. Wilson; Vince D. Calhoun; Yu-Ping Wang 002 (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2020)

A hypergraph learning method for brain functional connectivity network construction from fMRI data. - Li Xiao 002; Julia M. Stephen; Tony W. Wilson; Vince D. Calhoun; Yu-Ping Wang 002 (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2020)

A causal brain network estimation method leveraging Bayesian analysis and the PC algorithm. - Gemeng Zhang; Aiying Zhang; Vince D. Calhoun; Yu-Ping Wang 002 (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2020)

Multi-modal component subspace-similarity-based multi-kernel SVM for schizophrenia classification. - Shuang Gao; Vince D. Calhoun; Jing Sui (Computer-Aided Diagnosis, 2020)

A data-driven approach for stratifying psychotic and mood disorders subjects using structural magnitude resonance imaging data. - Hooman Rokham; Haleh Falakshahi; Vince D. Calhoun (Computer-Aided Diagnosis, 2020)

Whole MILC: Generalizing Learned Dynamics Across Tasks, Datasets, and Populations. - Usman Mahmood; Md Mahfuzur Rahman; Alex Fedorov; Noah Lewis; Zening Fu; Vince D. Calhoun; Sergey M. Plis (MICCAI (7), 2020)

A GICA-TVGL framework to study sex differences in resting state fMRI dynamic connectivity. - Biao Cai; Julia M. Stephen; Tony W. Wilson; Vince D. Calhoun; Yu-Ping Wang 002 (Image Processing, 2020)

Hybrid dictionary learning-ICA approaches built on novel instantaneous dynamic connectivity metric provide new multiscale insights into dynamic brain connectivity. - Robyn L. Miller; Vince D. Calhoun (Image Processing, 2020)

Transient Spectral Peak Analysis Reveals Distinct Temporal Activation Profiles for Different Functional Brain Networks. - Robyn L. Miller; Vince D. Calhoun (SSIAI, 2020)

A Machine Learning Model for Exploring Aberrant Functional Network Connectivity Transition in Schizophrenia. - Mohammad S. Eslampanah Sendi; Elaheh Zendehrouh; Zening Fu; Babak Mahmoudi; Robyn L. Miller; Vince D. Calhoun (SSIAI, 2020)

Nicotine Addiction Decreases Dynamic Connectivity Frequency In Functional Magnetic Resonance Imaging. - Victor M. Vergara; Vince D. Calhoun (SSIAI, 2020)

Deep Principal Correlated Auto-Encoders With Application to Imaging and Genomics Data Integration. - Gang Li 029; Chao Wang 042; Depeng Han; Yipu Zhang; Peng Peng; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Access, 2020)

Dynamic Resting-State Connectivity Differences in Eyes Open Versus Eyes Closed Conditions. - Oktay Agcaoglu; Tony W. Wilson; Yu-Ping Wang 002; Julia M. Stephen; Vince D. Calhoun (Brain Connect., 2020)

Weaker Cerebellocortical Connectivity Within Sensorimotor and Executive Networks in Schizophrenia Compared to Healthy Controls: Relationships with Processing Speed. - Sarah V. Clark; Amber Tannahill; Vince D. Calhoun; Jessica A. Bernard; Juan R. Bustillo; Jessica A. Turner (Brain Connect., 2020)

Application of deep canonically correlated sparse autoencoder for the classification of schizophrenia. - Gang Li 029; Depeng Han; Chao Wang 042; Wenxing Hu; Vince D. Calhoun; Yu-Ping Wang 002 (Comput. Methods Programs Biomed., 2020)

Interpretable multimodal fusion networks reveal mechanisms of brain cognition. - Wenxing Hu; Xianghe Meng; Yuntong Bai; Aiying Zhang; Biao Cai; Gemeng Zhang; Tony W. Wilson; Julia M. Stephen; Vince D. Calhoun; Yu-Ping Wang 002 (CoRR, 2020)

Causal inference of brain connectivity from fMRI with ψ-Learning Incorporated Linear non-Gaussian Acyclic Model (ψ-LiNGAM). - Aiying Zhang; Gemeng Zhang; Biao Cai; Wenxing Hu; Li Xiao 002; Tony W. Wilson; Julia M. Stephen; Vince D. Calhoun; Yu-Ping Wang 002 (CoRR, 2020)

A Bayesian incorporated linear non-Gaussian acyclic model for multiple directed graph estimation to study brain emotion circuit development in adolescence. - Aiying Zhang; Gemeng Zhang; Biao Cai; Tony W. Wilson; Julia M. Stephen; Vince D. Calhoun; Yu-Ping Wang 002 (CoRR, 2020)

On self-supervised multi-modal representation learning: An application to Alzheimer's disease. - Alex Fedorov; Lei Wu 013; Tristan Sylvain; Margaux Luck; Thomas P. DeRamus; Dmitry Bleklov; Sergey M. Plis; Vince D. Calhoun (CoRR, 2020)

Taxonomy of multimodal self-supervised representation learning. - Alex Fedorov; Tristan Sylvain; Margaux Luck; Lei Wu 013; Thomas P. DeRamus; Alex Kirilin; Dmitry Bleklov; Vince D. Calhoun; Sergey M. Plis (CoRR, 2020)

Log-sum enhanced sparse deep neural network. - Chen Qiao; Yan Shi; Yu-Xian Diao; Vince D. Calhoun; Yu-Ping Wang 002 (Neurocomputing, 2020)

COINSTAC: Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation. - 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; et al. (J. Open Source Softw., 2020)

Adaptive Constrained Independent Vector Analysis: An Effective Solution for Analysis of Large-Scale Medical Imaging Data. - Suchita Bhinge; Qunfang Long; Vince D. Calhoun; Tülay Adali (IEEE J. Sel. Top. Signal Process., 2020)

Disambiguating the role of blood flow and global signal with partial information decomposition. - Nigel Colenbier; Frederik Van de Steen; Lucina Q. Uddin; Russell A. Poldrack; Vince D. Calhoun; Daniele Marinazzo (NeuroImage, 2020)

Connectivity dynamics from wakefulness to sleep. - Eswar Damaraju; Enzo Tagliazucchi; Helmut Laufs; Vince D. Calhoun (NeuroImage, 2020)

Task-induced brain connectivity promotes the detection of individual differences in brain-behavior relationships. - 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 (NeuroImage, 2020)

Development and sex modulate visuospatial oscillatory dynamics in typically-developing children and adolescents. - Abraham D. Killanin; Alex I. Wiesman; Elizabeth Heinrichs-Graham; Boman R. Groff; Michaela R. Frenzel; Jacob A. Eastman; Yu-Ping Wang 002; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson (NeuroImage, 2020)

Independent vector analysis for common subspace analysis: Application to multi-subject fMRI data yields meaningful subgroups of schizophrenia. - Qunfang Long; Suchita Bhinge; Vince D. Calhoun; Tülay Adali (NeuroImage, 2020)

Nonlinear ICA of fMRI reveals primitive temporal structures linked to rest, task, and behavioral traits. - Hiroshi Morioka; Vince D. Calhoun; Aapo Hyvärinen (NeuroImage, 2020)

Prediction and classification of sleep quality based on phase synchronization related whole-brain dynamic connectivity using resting state fMRI. - Zhongxing Zhou; Biao Cai; Gemeng Zhang; Aiying Zhang; Vince D. Calhoun; Yu-Ping Wang 002 (NeuroImage, 2020)

Biomarker Identification Through Integrating fMRI and Epigenetics. - Yuntong Bai; Pascal Zille; Wenxing Hu; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Biomed. Eng., 2020)

Meta-Modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia. - Haleh Falakshahi; Victor M. Vergara; Jingyu Liu 001; Daniel H. Mathalon; Judith M. Ford; James Voyvodic; Bryon A. Mueller; Aysenil Belger; Sarah C. McEwen; Steven G. Potkin; Adrian Preda; Hooman Rokham; et al. (IEEE Trans. Biomed. Eng., 2020)

N-BiC: A Method for Multi-Component and Symptom Biclustering of Structural MRI Data: Application to Schizophrenia. - 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; et al. (IEEE Trans. Biomed. Eng., 2020)

A Manifold Regularized Multi-Task Learning Model for IQ Prediction From Two fMRI Paradigms. - Li Xiao 002; Julia M. Stephen; Tony W. Wilson; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Biomed. Eng., 2020)

Integration of Imaging (epi)Genomics Data for the Study of Schizophrenia Using Group Sparse Joint Nonnegative Matrix Factorization. - Min Wang 022; Ting-Zhu Huang; Jian Fang 001; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

Guest Editorial: Information Fusion for Medical Data: Early, Late, and Deep Fusion Methods for Multimodal Data. - Inês Domingues; Henning Müller; Andrés Ortiz 001; Belur V. Dasarathy; Pedro H. Abreu; Vince D. Calhoun (IEEE J. Biomed. Health Informatics, 2020)

Canonical Correlation Analysis of Imaging Genetics Data Based on Statistical Independence and Structural Sparsity. - Yipu Zhang; Peng Peng; Yongfeng Ju; Gang Li 029; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE J. Biomed. Health Informatics, 2020)

Optimized Combination of Multiple Graphs With Application to the Integration of Brain Imaging and (epi)Genomics Data. - Yuntong Bai; Pascal Zille; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Medical Imaging, 2020)

Causality-Based Feature Fusion for Brain Neuro-Developmental Analysis. - Peyman Hosseinzadeh Kassani; Li Xiao 002; Gemeng Zhang; Julia M. Stephen; Tony W. Wilson; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Medical Imaging, 2020)

Shift-Invariant Canonical Polyadic Decomposition of Complex-Valued Multi-Subject fMRI Data With a Phase Sparsity Constraint. - Li-Dan Kuang; Qiu-Hua Lin; Xiao-Feng Gong; Fengyu Cong; Yu-Ping Wang 002; Vince D. Calhoun (IEEE Trans. Medical Imaging, 2020)

Multi-Hypergraph Learning-Based Brain Functional Connectivity Analysis in fMRI Data. - Li Xiao 002; Junqi Wang 001; Peyman Hosseinzajeh Kassani; Yipu Zhang; Yuntong Bai; Julia M. Stephen; Tony W. Wilson; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Medical Imaging, 2020)

Joint Bayesian-Incorporating Estimation of Multiple Gaussian Graphical Models to Study Brain Connectivity Development in Adolescence. - Aiying Zhang; Biao Cai; Wenxing Hu; Bochao Jia; Faming Liang; Tony W. Wilson; Julia M. Stephen; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Medical Imaging, 2020)

Estimating Dynamic Functional Brain Connectivity With a Sparse Hidden Markov Model. - Gemeng Zhang; Biao Cai; Aiying Zhang; Julia M. Stephen; Tony W. Wilson; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Medical Imaging, 2020)

Harmonization of Multi-site Dynamic Functional Connectivity Network Data. - Biozid Bostami; Vince D. Calhoun; Harm J. van der Horn; Victor M. Vergara (BIBE, 2021)

Stability of functional network connectivity (FNC) values across multiple spatial normalization pipelines in spatially constrained independent component analysis. - Thomas DeRamus; Armin Iraji; Zening Fu; Rogers F. Silva; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002; Yuhui Du; Jingyu Liu 001; Vince D. Calhoun (BIBE, 2021)

A Novel Local Explainability Approach for Spectral Insight into Raw EEG-based Deep Learning Classifiers. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (BIBE, 2021)

A Gradient-based Approach for Explaining Multimodal Deep Learning Classifiers. - Charles A. Ellis; Rongen Zhang; Vince D. Calhoun; Darwin A. Carbajal; Robyn L. Miller; May D. Wang (BIBE, 2021)

A Novel Local Ablation Approach for Explaining Multimodal Classifiers. - Charles A. Ellis; Rongen Zhang; Vince D. Calhoun; Darwin A. Carbajal; Mohammad S. Eslampanah Sendi; May D. Wang; Robyn L. Miller (BIBE, 2021)

Machine Learning Predicts Treatment Response in Bipolar & Major Depression Disorders. - Mustafa S. Salman; Eric Verner; Henry Jeremy Bockholt; Zening Fu; Vince D. Calhoun (BIBE, 2021)

A Novel Activation Maximization-based Approach for Insight into Electrophysiology Classifiers. - Charles A. Ellis; Mohammad S. Eslampanah Sendi; Robyn L. Miller; Vince D. Calhoun (BIBM, 2021)

Confirmatory Factor Analysis on Mental Health Status using ABCD Cohort. - Britny Farahdel; Bishal Thapaliya; Pranav Suresh; Bhaskar Ray; Vince D. Calhoun; Jingyu Liu 001 (BIBM, 2021)

Variational voxelwise rs-fMRI representation learning: Evaluation of sex, age, and neuropsychiatric signatures. - Eloy Geenjaar; Tonya White; Vince D. Calhoun (BIBM, 2021)

Environmental and genome-wide association study on children anxiety and depression. - Bishal Thapaliya; Vince D. Calhoun; Jingyu Liu 001 (BIBM, 2021)

Deep learning in resting-state fMRI*. - Anees Abrol; Reihaneh Hassanzadeh; Sergey M. Plis; Vince D. Calhoun (EMBC, 2021)

Federation of Brain Age Estimation in Structural Neuroimaging Data. - Sunitha Basodi; Rajikha Raja; Bhaskar Ray; Harshvardhan Gazula; Jingyu Liu 001; Eric Verner; Vince D. Calhoun (EMBC, 2021)

Uncovering Active Structural Subspaces Associated with Changes in Indicators for Alzheimer's Disease. - Ishaan Batta; Anees Abrol; Vince D. Calhoun (EMBC, 2021)

A multimodal IVA fusion approach to identify linked neuroimaging markers. - Eswar Damaraju; Rogers F. Silva; Tülay Adali; Vince D. Calhoun (EMBC, 2021)

SMART (splitting-merging assisted reliable) Independent Component Analysis for Brain Functional Networks. - Yuhui Du; Xingyu He; Vince D. Calhoun (EMBC, 2021)

A Transdiagnostic Biotype Detection Method for Schizophrenia and Autism Spectrum Disorder Based on Graph Kernel. - Yuhui Du; Hui Hao; Ying Xing; Ju Niu; Vince D. Calhoun (EMBC, 2021)

Explainable Sleep Stage Classification with Multimodal Electrophysiology Time-series*. - Charles A. Ellis; Rongen Zhang; Darwin A. Carbajal; Robyn L. Miller; Vince D. Calhoun; May D. Wang (EMBC, 2021)

Fusing multimodal neuroimaging data with a variational autoencoder. - Eloy Geenjaar; Noah Lewis; Zening Fu; Rohan Venkatdas; Sergey M. Plis; Vince D. Calhoun (EMBC, 2021)

Investigating ADHD subtypes in children using temporal dynamics of the electroencephalogram (EEG) microstates *. - Na Luo; Xiangsheng Luo; Dongren Yao; Vince D. Calhoun; Li Sun; Jing Sui (EMBC, 2021)

Multiframe Evolving Dynamic Functional Network Connectivity Motifs (Evodfncs) from Continuity-Preserving Planar Embedding. - Robyn L. Miller; Victor M. Vergara; Vince D. Calhoun (EMBC, 2021)

A Method for Integrative Analysis of Local and Global Brain Dynamics. - Robyn L. Miller; Victor M. Vergara; Vince D. Calhoun (EMBC, 2021)

Multi-modal deep learning of functional and structural neuroimaging and genomic data to predict mental illness. - Md Abdur Rahaman; Jiayu Chen 003; Zening Fu; Noah Lewis; Armin Iraji; Vince D. Calhoun (EMBC, 2021)

Shared sets of correlated polygenic risk scores and voxel-wise grey matter across multiple traits identified via bi-clustering. - Md Abdur Rahaman; Amanda Rodrigue; David C. Glahn; Jessica A. Turner; Vince D. Calhoun (EMBC, 2021)

Multimodal Brain Age Prediction with Feature Selection and Comparison. - Bhaskar Ray; Kuaikuai Duan; Jiayu Chen 003; Zening Fu; Pranav Suresh; Sarah Johnson; Vince D. Calhoun; Jingyu Liu 001 (EMBC, 2021)

Brain age gap difference between healthy and mild dementia subjects: Functional network connectivity analysis. - Mohammad S. Eslampanah Sendi; David H. Salat; Vince D. Calhoun (EMBC, 2021)

Dynamic patterns within the default mode network in schizophrenia subgroups. - Mohammad S. Eslampanah Sendi; Elaheh Zendehrouh; Jessica A. Turner; Vince D. Calhoun (EMBC, 2021)

Evidence for Transcranial Magnetic Stimulation Induced Functional Connectivity Oscillations in the Brain. - Victor M. Vergara; Farshad Rafiei; Martijn E. Wokke; Hakwan Lau; Dobromir Rahnev; Vince D. Calhoun (EMBC, 2021)

BNCPL: Brain-Network-based Convolutional Prototype Learning for Discriminating Depressive Disorders. - 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; et al. (EMBC, 2021)

Tucker Decomposition for Extracting Shared and Individual Spatial Maps from Multi-Subject Resting-State fMRI Data. - Yue Han; Qiu-Hua Lin; Li-Dan Kuang; Xiao-Feng Gong; Fengyu Cong; Vince D. Calhoun (ICASSP, 2021)

Sparse Representation of Complex-Valued fMRI Data Based on Hard Thresholding of Spatial Source Phase. - Jia-Yang Song; Miao-Ying Qi; Dun-Pei Lv; Chao-Ying Zhang; Qiu-Hua Lin; Vince D. Calhoun (ICASSP, 2021)

Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease. - Alex Fedorov; Tristan Sylvain; Eloy Geenjaar; Margaux Luck; Lei Wu 013; Thomas P. DeRamus; Alex Kirilin; Dmitry Bleklov; Vince D. Calhoun; Sergey M. Plis (ICHI, 2021)

Can recurrent models know more than we do? - Noah Lewis; Robyn L. Miller; Harshvardhan Gazula; Md Mahfuzur Rahman; Armin Iraji; Vince D. Calhoun; Sergey M. Plis (ICHI, 2021)

Marginal Spectrum Modulated Hilbert-Huang Transform: Application to Time Courses Extracted by Independent Vector Analysis of Resting-State fMRI Data. - Wei-Xing Li; Chao-Ying Zhang; Li-Dan Kuang; Yue Han; Huan-Jie Li; Qiu-Hua Lin; Vince D. Calhoun (ICONIP (6), 2021)

Fusion of Multiple Spatial Networks Derived from Complex-Valued fMRI Data via CNN Classification. - Yan-Wei Niu; Chao-Ying Zhang; Yue Qiu; Qiu-Hua Lin; Jing Sui; Vince D. Calhoun (IJCNN, 2021)

A Multimodal Learning Framework to Study Varying Information Complexity in Structural and Functional Sub-Domains in Schizophrenia. - Ishaan Batta; Anees Abrol; Zening Fu; Vince D. Calhoun (ISBI, 2021)

A New Semi-Supervised Non-Negative Matrix Factorization Method For Brain Dynamic Functional Connectivity Analysis. - Yuhui Du; Xingyu He; Vince D. Calhoun (ISBI, 2021)

A New Hypergraph Clustering Method For Exploring Transdiagnostic Biotypes In Mental Illnesses: Application To Schizophrenia And Psychotic Bipolar Disorder. - Yuhui Du; Ju Niu; Vince D. Calhoun (ISBI, 2021)

On Self-Supervised Multimodal Representation Learning: An Application To Alzheimer's Disease. - Alex Fedorov; Lei Wu 013; Tristan Sylvain; Margaux Luck; Thomas P. DeRamus; Dmitry Bleklov; Sergey M. Plis; Vince D. Calhoun (ISBI, 2021)

3-way Parallel Fusion of Spatial (sMRI/dMRI) and Spatio-temporal (fMRI) Data with Application to Schizophrenia. - Shile Qi; Sergey M. Plis; Robyn L. Miller; Rogers F. Silva; Victor M. Vergara; Rongtao Jiang; Dongmei Zhi; Jing Sui; Vince D. Calhoun (ISBI, 2021)

Statelets: A Novel Multi-Dimensional State-Shape Representation Of Brain Functional Connectivity Dynamics. - Md Abdur Rahaman; Eswar Damaraju; Debbrata Kumar Saha; Vince D. Calhoun; Sergey M. Plis (ISBI, 2021)

An Attention-Based Hybrid Deep Learning Framework Integrating Temporal Coherence And Dynamics For Discriminating Schizophrenia. - Min Zhao; Weizheng Yan; Rongtao Xu; Dongmei Zhi; Rongtao Jiang; Tianzi Jiang; Vince D. Calhoun; Jing Sui (ISBI, 2021)

A Deep Learning Model for Data-Driven Discovery of Functional Connectivity. - Usman Mahmood; Zening Fu; Vince D. Calhoun; Sergey M. Plis (Algorithms, 2021)

The Influence of Cerebral Small Vessel Disease on Static and Dynamic Functional Network Connectivity in Subjects Along Alzheimer's Disease Continuum. - Kaicheng Li; Zening Fu; Xiao Luo; Qingze Zeng; Peiyu Huang; Minming Zhang; Vince D. Calhoun (Brain Connect., 2021)

Relationship between Dynamic Blood-Oxygen-Level-Dependent Activity and Functional Network Connectivity: Characterization of Schizophrenia Subgroups. - Qunfang Long; Suchita Bhinge; Vince D. Calhoun; Tülay Adali (Brain Connect., 2021)

A Classification-Based Approach to Estimate the Number of Resting Functional Magnetic Resonance Imaging Dynamic Functional Connectivity States. - Debbrata K. Saha; Eswar Damaraju; Barnaly Rashid; Anees Abrol; Sergey M. Plis; Vince D. Calhoun (Brain Connect., 2021)

Abnormal Dynamic Functional Network Connectivity Estimated from Default Mode Network Predicts Symptom Severity in Major Depressive Disorder. - 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; et al. (Brain Connect., 2021)

Ensemble manifold based regularized multi-modal graph convolutional network for cognitive ability prediction. - Gang Qu 002; Li Xiao 002; Wenxing Hu; Kun Zhang 012; Vince D. Calhoun; Yu-Ping Wang 002 (CoRR, 2021)

Efficient Distributed Auto-Differentiation. - Bradley T. Baker; Vince D. Calhoun; Barak A. Pearlmutter; Sergey M. Plis (CoRR, 2021)

Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data. - Alex Fedorov; Eloy Geenjaar; Lei Wu 013; Thomas P. DeRamus; Vince D. Calhoun; Sergey M. Plis (CoRR, 2021)

Algorithm-Agnostic Explainability for Unsupervised Clustering. - Charles A. Ellis; Mohammad S. Eslampanah Sendi; Sergey M. Plis; Robyn L. Miller; Vince D. Calhoun (CoRR, 2021)

Brain dynamics via Cumulative Auto-Regressive Self-Attention. - Usman Mahmood; Zening Fu; Vince D. Calhoun; Sergey M. Plis (CoRR, 2021)

Multi network InfoMax: A pre-training method involving graph convolutional networks. - Usman Mahmood; Zening Fu; Vince D. Calhoun; Sergey M. Plis (CoRR, 2021)

A deep autoencoder with sparse and graph Laplacian regularization for characterizing dynamic functional connectivity during brain development. - Chen Qiao; Xin-Yu Hu; Li Xiao 002; Vince D. Calhoun; Yu-Ping Wang 002 (Neurocomputing, 2021)

Accessing dynamic functional connectivity using l0-regularized sparse-smooth inverse covariance estimation from fMRI. - Li Zhang 041; Zening Fu; Wenwen Zhang; Gan Huang; Zhen Liang; Linling Li; Bharat B. Biswal; Vince D. Calhoun; Zhiguo Zhang 001 (Neurocomputing, 2021)

Dynamic state with covarying brain activity-connectivity: On the pathophysiology of schizophrenia. - Zening Fu; Armin Iraji; Jessica A. Turner; Jing Sui; Robyn L. Miller; Godfrey D. Pearlson; Vince D. Calhoun (NeuroImage, 2021)

Frequency drift in MR spectroscopy at 3T. - 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; et al. (NeuroImage, 2021)

Spontaneous cortical MEG activity undergoes unique age- and sex-related changes during the transition to adolescence. - Lauren R. Ott; Samantha H. Penhale; Brittany K. Taylor; Brandon J. Lew; Yu-Ping Wang 002; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson (NeuroImage, 2021)

Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset? - 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; et al. (NeuroImage, 2021)

Respiratory, cardiac, EEG, BOLD signals and functional connectivity over multiple microsleep episodes. - Chun Siong Soon; Ksenia Vinogradova; Ju Lynn Ong; Vince D. Calhoun; Thomas Liu; Juan Helen Zhou; Kwun Kei Ng; Michael W. L. Chee (NeuroImage, 2021)

The Developmental Chronnecto-Genomics (Dev-CoG) study: A multimodal study on the developing brain. - 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 001; et al. (NeuroImage, 2021)

Tracking spatial dynamics of functional connectivity during a task. - Lei Wu 013; Arvind Caprihan; Vince D. Calhoun (NeuroImage, 2021)

Decentralized Multisite VBM Analysis During Adolescence Shows Structural Changes Linked to Age, Body Mass Index, and Smoking: a COINSTAC Analysis. - 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; et al. (Neuroinformatics, 2021)

Sparse deep dictionary learning identifies differences of time-varying functional connectivity in brain neuro-developmental study. - Chen Qiao; Lan Yang 010; Vince D. Calhoun; Zong-Ben Xu; Yu-Ping Wang 002 (Neural Networks, 2021)

Multiview Diffusion Map Improves Prediction of Fluid Intelligence With Two Paradigms of fMRI Analysis. - Guixia Pan; Li Xiao 002; Yuntong Bai; Tony W. Wilson; Julia M. Stephen; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Biomed. Eng., 2021)

Ensemble Manifold Regularized Multi-Modal Graph Convolutional Network for Cognitive Ability Prediction. - Gang Qu 002; Li Xiao 002; Wenxing Hu; Junqi Wang 001; Kun Zhang 012; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Biomed. Eng., 2021)

Correlation Guided Graph Learning to Estimate Functional Connectivity Patterns From fMRI Data. - Li Xiao 002; Aiying Zhang; Biao Cai; Julia M. Stephen; Tony W. Wilson; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Biomed. Eng., 2021)

A Latent Gaussian Copula Model for Mixed Data Analysis in Brain Imaging Genetics. - Aiying Zhang; Jian Fang 001; Wenxing Hu; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

Multidataset Independent Subspace Analysis With Application to Multimodal Fusion. - Rogers F. Silva; Sergey M. Plis; Tülay Adali; Marios S. Pattichis; Vince D. Calhoun (IEEE Trans. Image Process., 2021)

Multi-Paradigm fMRI Fusion via Sparse Tensor Decomposition in Brain Functional Connectivity Study. - Yipu Zhang; Li Xiao 002; Gemeng Zhang; Biao Cai; Julia M. Stephen; Tony W. Wilson; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE J. Biomed. Health Informatics, 2021)

A Joint Analysis of Multi-Paradigm fMRI Data With Its Application to Cognitive Study. - Yuntong Bai; Yun Gong; Jianchao Bai; Jingyu Liu 001; Hong-Wen Deng; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Medical Imaging, 2021)

Interpretable Multimodal Fusion Networks Reveal Mechanisms of Brain Cognition. - Wenxing Hu; Xianghe Meng; Yuntong Bai; Aiying Zhang; Gang Qu 002; Biao Cai; Gemeng Zhang; Tony W. Wilson; Julia M. Stephen; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Medical Imaging, 2021)

A Correlated Noise-Assisted Decentralized Differentially Private Estimation Protocol, and its Application to fMRI Source Separation. - Hafiz Imtiaz; Jafar Mohammadi; Rogers F. Silva; Bradley T. Baker; Sergey M. Plis; Anand D. Sarwate; Vince D. Calhoun (IEEE Trans. Signal Process., 2021)

Classification of Schizophrenia and Alzheimer's Disease using Resting-State Functional Network Connectivity. - Reihaneh Hassanzadeh; Anees Abrol; Vince D. Calhoun (BHI, 2022)

Relationship of Hemodynamic Delay and Sex Differences Among Adolescents Using Resting-state fMRI Data. - Hooman Rokham; Haleh Falakshahi; Vince D. Calhoun (BHI, 2022)

A deep generative multimodal imaging genomics framework for Alzheimer's disease prediction. - Giorgio Dolci; Md Abdur Rahaman; Jiayu Chen 003; Kuaikuai Duan; Zening Fu; Anees Abrol; Gloria Menegaz; Vince D. Calhoun (BIBE, 2022)

An Approach for Estimating Explanation Uncertainty in fMRI dFNC Classification. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (BIBE, 2022)

Examining Effects of Schizophrenia on EEG with Explainable Deep Learning Models. - Charles A. Ellis; Abhinav Sattiraju; Robyn L. Miller; Vince D. Calhoun (BIBE, 2022)

Examining Reproducibility of EEG Schizophrenia Biomarkers Across Explainable Machine Learning Models. - Charles A. Ellis; Abhinav Sattiraju; Robyn L. Miller; Vince D. Calhoun (BIBE, 2022)

Exploring Relationships between Functional Network Connectivity and Cognition with an Explainable Clustering Approach. - Charles A. Ellis; Martina Lapera Sancho; Mohammad S. Eslampanah Sendi; Robyn L. Miller; Vince D. Calhoun (BIBE, 2022)

Multimodal Analysis Uncovers Links between Grey Matter Volume and both Low-and High-frequency Dynamic Connectivity States in Schizophrenia. - Marlena Duda; Ashkan Faghiri; Vince D. Calhoun (BIBM, 2022)

Data-driven spatio-temporal dynamic brain connectivity analysis using fALFF: Application to sensorimotor task data. - Khondoker Murad Hossain; Suchita Bhinge; Qunfang Long; Vince D. Calhoun; Tülay Adali (CISS, 2022)

Discovery and Replication of Time-Resolved Functional Network Connectivity Differences in Adolescence and Adulthood in over 50K fMRI Datasets. - Anees Abrol; Vince D. Calhoun (EMBC, 2022)

Probing the link between the APOE-ε4 allele and whole-brain gray matter using deep learning. - Anees Abrol; Ihab Hajjar; Vince D. Calhoun (EMBC, 2022)

Longitudinal Changes in Resting State FMRI Spectra in Children. - Oktay Agcaoglu; Tony W. Wilson; Yu-Ping Wang 002; Julia M. Stephen; Vince D. Calhoun (EMBC, 2022)

Learning Active Multimodal Subspaces in the Brain. - Ishaan Batta; Anees Abrol; Zening Fu; Vince D. Calhoun (EMBC, 2022)

Deep Learning Prediction and Visualization of Gender Related Brain Changes from Longitudinal Structural MRI Data in the ABCD Study. - Yuda Bi; Anees Abrol; Zening Fu; Vince D. Calhoun (EMBC, 2022)

An ICA-based framework for joint analysis of cognitive scores and MEG event-related fields. - Poomipat Boonyakitanont; Ben Gabrielson; Irina Belyaeva; Parthan Olikkal; Jitkomut Songsiri; Yu-Ping Wang 002; Tony W. Wilson; Vince D. Calhoun; Julia M. Stephen; Tülay Adali (EMBC, 2022)

Multi-Site Mild Traumatic Brain Injury Classification with Machine Learning and Harmonization. - Biozid Bostami; Flor A. Espinoza; Harm J. van der Horn; Joukje van der Naalt; Vince D. Calhoun; Victor M. Vergara (EMBC, 2022)

Spatially Constrained ICA Enables Robust Detection of Schizophrenia from Very Short Resting-state fMRI. - Marlena Duda; Armin Iraji; Vince D. Calhoun (EMBC, 2022)

A Model Visualization-based Approach for Insight into Waveforms and Spectra Learned by CNNs. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (EMBC, 2022)

An Unsupervised Feature Learning Approach for Elucidating Hidden Dynamics in rs-fMRI Functional Network Connectivity. - Charles A. Ellis; Mohammad S. Eslampanah Sendi; Robyn L. Miller; Vince D. Calhoun (EMBC, 2022)

A Unified Framework for Modularizing and Comparing Time-Resolved Functional Connectivity Methods. - Ashkan Faghiri; Armin Iraji; Marlena Duda; Tülay Adali; Vince D. Calhoun (EMBC, 2022)

Functional Connectivity Stability: A Signature of Neurocognitive Development and Psychiatric Problems in Children. - Zening Fu; Mustafa S. Salman; Jingyu Liu 001; Vince D. Calhoun (EMBC, 2022)

Transient Intervals of Significantly Different Whole Brain Connectivity Predict Recovery vs. Progression from Mild Cognitive Impairment: New Insights from Interpretable LSTM Classifiers. - Yutong Gao 002; Vince D. Calhoun; Robyn L. Miller (EMBC, 2022)

A Supervised Contrastive Learning-based Analysis of rs-tMRI Data Captures Gender Differences in Nonlinear Functional Network Coupling. - Reihaneh Hassanzadeh; Vince D. Calhoun (EMBC, 2022)

A 5D approach to study spatio-temporal dynamism of resting-state brain networks in schizophrenia. - Behnam Kazemivash; Vince D. Calhoun (EMBC, 2022)

Mind the gap: functional network connectivity interpolation between schizophrenia patients and controls using a variational autoencoder. - Xinhui Li; Eloy Geenjaar; Zening Fu; Sergey M. Plis; Vince D. Calhoun (EMBC, 2022)

Default mode network dynamic functional network connectivity predicts psychotic symptom severity. - Mohammad S. Eslampanah Sendi; Hossein Dini; Luis Emilio Bruni; Vince D. Calhoun (EMBC, 2022)

A two-step clustering-based pipeline for big dynamic functional network connectivity data. - Mohammad S. Eslampanah Sendi; Robyn L. Miller; David H. Salat; Vince D. Calhoun (EMBC, 2022)

Comparison of Energy Signals from the 4D DWT of Resting State FMRI Data Obtained from a Study on Schizophrenia. - Michael Weeks; Vince D. Calhoun; Robyn L. Miller (EMBC, 2022)

'Harmless' adversarial network harmonization approach for removing site effects and improving reproducibility in neuroimaging studies. - Weizheng Yan; Zening Fu; Jing Sui; Vince D. Calhoun (EMBC, 2022)

An Accelerated Rank-(L, L, 1, 1) Block Term Decomposition Of Multi-Subject Fmri Data Under Spatial Orthonormality Constraint. - Li-Dan Kuang; Biao Wang; Qiu-Hua Lin; Haopeng Zhang 010; Jianming Zhang 003; Wenjun Li; Feng Li 065; Vince D. Calhoun (ICASSP, 2022)

Multi-Task fMRI Data Fusion Using IVA and PARAFAC2. - Isabell Lehmann; Evrim Acar; Tanuj Hasija; Mohammad A. B. S. Akhonda; Vince D. Calhoun; Peter J. Schreier; Tülay Adali (ICASSP, 2022)

Independent Vector Analysis Based Subgroup Identification from Multisubject fMRI Data. - Hanlu Yang 001; Mohammad A. B. S. Akhonda; Fateme Ghayem; Qunfang Long; Vince D. Calhoun; Tülay Adali (ICASSP, 2022)

Explainable AI (XAI) In Biomedical Signal and Image Processing: Promises and Challenges. - Guang Yang 006; Arvind Rao; Christine Fernandez-Maloigne; Vince D. Calhoun; Gloria Menegaz (ICIP, 2022)

Deep Learning From Imaging Genetics for Schizophrenia Classification. - Hongkun Yu 003; Thomas Florian; Vince D. Calhoun; Dong Hye Ye (ICIP, 2022)

Deep Dynamic Effective Connectivity Estimation from Multivariate Time Series. - Usman Mahmood; Zening Fu; Vince D. Calhoun; Sergey M. Plis (IJCNN, 2022)

Refacing Defaced MRI with PixelCNN. - Yaorong Xiao; William Ashbee; Vince D. Calhoun; Sergey M. Plis (IJCNN, 2022)

Single Sideband Modulation as a Tool To Improve Functional Connectivity Estimation. - Ashkan Faghiri; Tülay Adali; Vince D. Calhoun (ISBI, 2022)

A Contrastive Learning-Based Approach To Measure Spatial Coupling Among Brain Networks: A Schizophrenia Study. - Reihaneh Hassanzadeh; Vince D. Calhoun (ISBI, 2022)

Decentralized Spatially Constrained Source-Based Morphometry. - Debbrata K. Saha; Rogers F. Silva; Bradley T. Baker; Vince D. Calhoun (ISBI, 2022)

Longitudinal Whole-Brain Functional Network Change Patterns Over A Two-Year Period In The ABCD Data. - Rekha Saha; Debbrata K. Saha; Md Abdur Rahaman; Zening Fu; Vince D. Calhoun (ISBI, 2022)

Multimodal fusion of brain imaging data with joint non-linear independent component analysis. - Oktay Agcaoglu; Rogers F. Silva; Vince D. Calhoun (IVMSP, 2022)

Going from lines to triangles: A formulation for time-frequency moments of time-series with application to study fMRI. - Ashkan Faghiri; Armin Iraji; Noah Lewis; Kun Yang; Koko Ishizuka; Akira Sawa; Tülay Adali; Vince D. Calhoun (IVMSP, 2022)

Two-Dimensional Attentive Fusion for Multi-Modal Learning of Neuroimaging and Genomics Data. - Md Abdur Rahaman; Yash Garg; Armin Iraji; Zening Fu; Jiayu Chen 003; Vince D. Calhoun (MLSP, 2022)

Rapid automated validation, annotation and publication of SARS-CoV-2 sequences to GenBank. - 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 (Database J. Biol. Databases Curation, 2022)

Lateralization of Resting-State Networks in Children: Association with Age, Sex, Handedness, Intelligence Quotient, and Behavior. - Oktay Agcaoglu; Ryan L. Muetzel; Barnaly Rashid; Tonya White; Henning Tiemeier; Vince D. Calhoun (Brain Connect., 2022)

Multimodel Order Independent Component Analysis: A Data-Driven Method for Evaluating Brain Functional Network Connectivity Within and Between Multiple Spatial Scales. - 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; et al. (Brain Connect., 2022)

Tri-Clustering Dynamic Functional Network Connectivity Identifies Significant Schizophrenia Effects Across Multiple States in Distinct Subgroups of Individuals. - 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 (Brain Connect., 2022)

An Approach to Automatically Label and Order Brain Activity/Component Maps. - Mustafa S. Salman; Tor D. Wager; Eswar Damaraju; Anees Abrol; Victor M. Vergara; Zening Fu; Vince D. Calhoun (Brain Connect., 2022)

Dynamic Persistent Homology for Brain Networks via Wasserstein Graph Clustering. - Moo K. Chung; Shih-Gu Huang; Ian C. Carroll; Vince D. Calhoun; H. Hill Goldsmith (CoRR, 2022)

Spatio-temporally separable non-linear latent factor learning: an application to somatomotor cortex fMRI data. - Eloy Geenjaar; Amrit Kashyap; Noah Lewis; Robyn L. Miller; Vince D. Calhoun (CoRR, 2022)

Pipeline-Invariant Representation Learning for Neuroimaging. - Xinhui Li; Alex Fedorov; Mrinal Mathur; Anees Abrol; Gregory Kiar; Sergey M. Plis; Vince D. Calhoun (CoRR, 2022)

Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes. - Alex Fedorov; Eloy Geenjaar; Lei Wu 013; Tristan Sylvain; Thomas P. DeRamus; Margaux Luck; Maria B. Misiura; R. Devon Hjelm; Sergey M. Plis; Vince D. Calhoun (CoRR, 2022)

CommsVAE: Learning the brain's macroscale communication dynamics using coupled sequential VAEs. - Eloy Geenjaar; Noah Lewis; Amrit Kashyap; Robyn L. Miller; Vince D. Calhoun (CoRR, 2022)

SSPNet: An interpretable 3D-CNN for classification of schizophrenia using phase maps of resting-state complex-valued fMRI data. - Qiu-Hua Lin; Yan-Wei Niu; Jing Sui; Wen-Da Zhao; Chuanjun Zhuo; Vince D. Calhoun (Medical Image Anal., 2022)

An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data. - Min Zhao; Weizheng Yan; Na Luo; Dongmei Zhi; Zening Fu; Yuhui Du; Shan Yu; Tianzi Jiang; Vince D. Calhoun; Jing Sui (Medical Image Anal., 2022)

Cerebral blood flow and cardiovascular risk effects on resting brain regional homogeneity. - 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; et al. (NeuroImage, 2022)

The development of sensorimotor cortical oscillations is mediated by pubertal testosterone. - Madison H. Fung; Elizabeth Heinrichs-Graham; Brittany K. Taylor; Michaela R. Frenzel; Jacob A. Eastman; Yu-Ping Wang 002; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson (NeuroImage, 2022)

Moving beyond the 'CAP' of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping. - 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; et al. (NeuroImage, 2022)

Through the looking glass: Deep interpretable dynamic directed connectivity in resting fMRI. - Usman Mahmood; Zening Fu; Satrajit S. Ghosh; Vince D. Calhoun; Sergey M. Plis (NeuroImage, 2022)

Eyes-closed versus eyes-open differences in spontaneous neural dynamics during development. - Nathan M. Petro; Lauren R. Ott; Samantha H. Penhale; Maggie P. Rempe; Christine M. Embury; Giorgia Picci; Yu-Ping Wang 002; Julia M. Stephen; Vince D. Calhoun; Tony W. Wilson (NeuroImage, 2022)

A longitudinal study of functional connectome uniqueness and its association with psychological distress in adolescence. - 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 (NeuroImage, 2022)

Individual differences in amygdala volumes predict changes in functional connectivity between subcortical and cognitive control networks throughout adolescence. - Brittany K. Taylor; Michaela R. Frenzel; Jacob A. Eastman; Christine M. Embury; Oktay Agcaoglu; Yu-Ping Wang 002; Julia M. Stephen; Vince D. Calhoun; Tony W. Wilson (NeuroImage, 2022)

Longitudinal changes in the neural oscillatory dynamics underlying abstract reasoning in children and adolescents. - Brittany K. Taylor; Elizabeth Heinrichs-Graham; Jacob A. Eastman; Michaela R. Frenzel; Yu-Ping Wang 002; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson (NeuroImage, 2022)

Detecting abnormal connectivity in schizophrenia via a joint directed acyclic graph estimation model. - Gemeng Zhang; Biao Cai; Aiying Zhang; Zhuozhuo Tu; Li Xiao 002; Julia M. Stephen; Tony W. Wilson; Vince D. Calhoun; Yu-Ping Wang 002 (NeuroImage, 2022)

A dynamic graph convolutional neural network framework reveals new insights into connectome dysfunctions in ADHD. - Kanhao Zhao; Boris Duka; Hua Xie; Desmond J. Oathes; Vince D. Calhoun; Yu Zhang 009 (NeuroImage, 2022)

Decentralized Brain Age Estimation Using MRI Data. - Sunitha Basodi; Rajikha Raja; Bhaskar Ray; Harshvardhan Gazula; Anand D. Sarwate; Sergey M. Plis; Jingyu Liu 001; Eric Verner; Vince D. Calhoun (Neuroinformatics, 2022)

Building Models of Functional Interactions Among Brain Domains that Encode Varying Information Complexity: A Schizophrenia Case Study. - Ishaan Batta; Anees Abrol; Zening Fu; Adrian Preda; Theo G. M. van Erp; Vince D. Calhoun (Neuroinformatics, 2022)

Federated Analysis of Neuroimaging Data: A Review of the Field. - Kelly Rootes-Murdy; Harshvardhan Gazula; Eric Verner; Ross Kelly; Thomas DeRamus; Sergey M. Plis; Anand D. Sarwate; Jessica A. Turner; Vince D. Calhoun (Neuroinformatics, 2022)

NeuroCrypt: Machine Learning Over Encrypted Distributed Neuroimaging Data. - Nipuna Senanayake; Robert Podschwadt; Daniel Takabi; Vince D. Calhoun; Sergey M. Plis (Neuroinformatics, 2022)

ENIGMA + COINSTAC: Improving Findability, Accessibility, Interoperability, and Re-usability. - 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; et al. (Neuroinformatics, 2022)

Association of Neuroimaging Data with Behavioral Variables: A Class of Multivariate Methods and Their Comparison Using Multi-Task FMRI Data. - Mohammad A. B. S. Akhonda; Yuri Levin-Schwartz; Vince D. Calhoun; Tülay Adali (Sensors, 2022)

Reproducibility in Matrix and Tensor Decompositions: Focus on model match, interpretability, and uniqueness. - Tülay Adali; Furkan Kantar; Mohammad Abu Baker Siddique Akhonda; Stephen C. Strother; Vince D. Calhoun; Evrim Acar (IEEE Signal Process. Mag., 2022)

Deep Learning in Biological Image and Signal Processing [From the Guest Editors]. - Erik Meijering; Vince D. Calhoun; Gloria Menegaz; David J. Miller 001; Jong Chul Ye (IEEE Signal Process. Mag., 2022)

Deep Learning in Neuroimaging: Promises and challenges. - Weizheng Yan; Gang Qu 002; Wenxing Hu; Anees Abrol; Biao Cai; Chen Qiao; Sergey M. Plis; Yu-Ping Wang 002; Jing Sui; Vince D. Calhoun (IEEE Signal Process. Mag., 2022)

Distance Correlation-Based Brain Functional Connectivity Estimation and Non-Convex Multi-Task Learning for Developmental fMRI Studies. - Li Xiao 002; Biao Cai; Gang Qu 002; Gemeng Zhang; Julia M. Stephen; Tony W. Wilson; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Biomed. Eng., 2022)

Group Sparse Joint Non-Negative Matrix Factorization on Orthogonal Subspace for Multi-Modal Imaging Genetics Data Analysis. - Peng Peng; Yipu Zhang; Yongfeng Ju; Kaiming Wang; Gang Li 029; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

Low-Rank Tucker-2 Model for Multi-Subject fMRI Data Decomposition With Spatial Sparsity Constraint. - Yue Han; Qiu-Hua Lin; Li-Dan Kuang; Xiao-Feng Gong; Fengyu Cong; Yu-Ping Wang 002; Vince D. Calhoun (IEEE Trans. Medical Imaging, 2022)

Multi-Modal Imaging Genetics Data Fusion via a Hypergraph-Based Manifold Regularization: Application to Schizophrenia Study. - Yipu Zhang; Haowei Zhang; Li Xiao 002; Yuntong Bai; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Medical Imaging, 2022)

A Systematic Approach for Explaining Time and Frequency Features Extracted by Convolutional Neural Networks From Raw Electroencephalography Data. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (Frontiers Neuroinformatics, 2022)

An AO-ADMM Approach to Constraining PARAFAC2 on All Modes. - Marie Roald; Carla Schenker; Vince D. Calhoun; Tülay Adali; Rasmus Bro; Jeremy E. Cohen; Evrim Acar (SIAM J. Math. Data Sci., 2022)

REGRESSION-ASSISTED INDEPENDENT VECTOR ANALYSIS: A SOLUTION TO LARGE-SCALE FMRI DATA ANALYSIS. - Hanlu Yang 001; Ben Gabrielson; Vince D. Calhoun; Tülay Adali (ACSSC, 2023)

Flexible Multisubject Multiset FMRI Data Analysis Using Robust Discriminative Dictionary Learning. - Rui Jin; Shuai Xu; Seung-Jun Kim 002; Vince D. Calhoun (ACSSC, 2023)

Reproducibility in Joint Blind Source Separation: Application to fMRI Analysis. - Francisco Laport; Trung Vu 001; Hanlu Yang 001; Vince D. Calhoun; Tülay Adali (ACSSC, 2023)

Multimodal Fusion of Functional and Structural Data to Recognize Longitudinal Change Patterns in the Adolescent Brain. - Rekha Saha; Debbrata K. Saha; Zening Fu; Rogers F. Silva; Vince D. Calhoun (BHI, 2023)

An Explainable and Robust Deep Learning Approach for Automated Electroencephalography-Based Schizophrenia Diagnosis. - Abhinav Sattiraju; Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (BIBE, 2023)

Improving Explainability for Single-Channel EEG Deep Learning Classifiers via Interpretable Filters and Activation Analysis. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (BIBM, 2023)

Improving Multichannel Raw Electroencephalography-based Diagnosis of Major Depressive Disorder via Transfer Learning with Single Channel Sleep Stage Data. - Charles A. Ellis; Abhinav Sattiraju; Robyn L. Miller; Vince D. Calhoun (BIBM, 2023)

How Does Aging Affect Whole-brain Functional Network Connectivity? Evidence from An ICA Method. - Yuhui Du; Yating Guo; Vince D. Calhoun (EMBC, 2023)

A Novel Explainable Fuzzy Clustering Approach for fMRI Dynamic Functional Network Connectivity Analysis. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (EMBC, 2023)

A Convolutional Autoencoder-based Explainable Clustering Approach for Resting-State EEG Analysis. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (EMBC, 2023)

Neuropsychiatric Disorder Subtyping Via Clustered Deep Learning Classifier Explanations. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (EMBC, 2023)

Network Differential in Gaussian Graphical Models from Multimodal Neuroimaging Data. - Haleh Falakshahi; Hooman Rokham; Robyn L. Miller; Jean Liu; Vince D. Calhoun (EMBC, 2023)

ICA-based Individualized Differential Structure Similarity Networks for Predicting Symptom Scores in Adolescents with Major Depressive Disorder. - Xiang Li; Ming Xu; Rongtao Jiang; Xuemei Li; Vince D. Calhoun; Xinyu Zhou; Jing Sui (EMBC, 2023)

Hyperlocal Spatial Flows in BOLD fMRI Expose Novel Brain-Based Correlates of Schizophrenia. - Robyn L. Miller; Victor M. Vergara; Vince D. Calhoun (EMBC, 2023)

Decentralized Parallel Independent Component Analysis for Multimodal, Multisite Data. - Chan Aek Panichvatana; Jiayu Chen 003; Bradley T. Baker; Bishal Thapaliya; Vince D. Calhoun; Jingyu Liu 001 (EMBC, 2023)

A Deep Learning Approach for Psychosis Spectrum Label Noise Detection from Multimodal Neuroimaging Data. - Hooman Rokham; Haleh Falakshahi; Vince D. Calhoun (EMBC, 2023)

A Multivariate Method for Estimating and comparing whole brain functional connectomes from fMRI and PET data. - Debbrata Kumar Saha; Anastasia Bohsali; Rekha Saha; Ihab Hajjar; Vince D. Calhoun (EMBC, 2023)

Functional and Structural Longitudinal Change Patterns in Adolescent Brain. - Rekha Saha; Debbrata K. Saha; Zening Fu; Rogers F. Silva; Vince D. Calhoun (EMBC, 2023)

Phase and amplitude, two sides of functional connectivity. - Sir-Lord Wiafe; Zening Fu; Vince D. Calhoun; Ashkan Faghiri (EMBC, 2023)

Towards a multimodal neuroimaging-based risk score for Alzheimer's disease by combining clinical and large N>37000 population data. - Elaheh Zendehrouh; Mohammad S. Eslampanah Sendi; Vince D. Calhoun (EMBC, 2023)

Coupled CP Tensor Decomposition with Shared and Distinct Components for Multi-Task Fmri Data Fusion. - R. A. Borsoi; Isabell Lehmann; Mohammad A. B. S. Akhonda; Vince D. Calhoun; Konstantin Usevich; David Brie; Tülay Adali (ICASSP, 2023)

Deep Generative Transfer Learning Predicts Conversion To Alzheimer'S Disease From Neuroimaging Genomics Data. - Giorgio Dolci; Md Abdur Rahaman; Ilaria Boscolo Galazzo; Federica Cruciani; Anees Abrol; Jiayu Chen 003; Zening Fu; Kuaikuai Duan; Gloria Menegaz; Vince D. Calhoun (ICASSP Workshops, 2023)

Novel Approach Explains Spatio-Spectral Interactions In Raw Electroencephalogram Deep Learning Classifiers. - Charles A. Ellis; Abhinav Sattiraju; Robyn L. Miller; Vince D. Calhoun (ICASSP Workshops, 2023)

Independent Vector Analysis with Multivariate Gaussian Model: a Scalable Method by Multilinear Regression. - Ben Gabrielson; Mingyu Sun; Mohammad A. B. S. Akhonda; Vince D. Calhoun; Tülay Adali (ICASSP, 2023)

New Interpretable Patterns and Discriminative Features from Brain Functional Network Connectivity using Dictionary Learning. - Fateme Ghayem; Hanlu Yang 001; Furkan Kantar; Seung-Jun Kim 002; Vince D. Calhoun; Tülay Adali (ICASSP, 2023)

Multi-Modal Deep Learning on Imaging Genetics for Schizophrenia Classification. - Ayush Kanyal; Srinivas Kandula; Vince D. Calhoun; Dong Hye Ye (ICASSP Workshops, 2023)

Higher-Order Organization in the Human Brain From Matrix-Based Rényi's Entropy. - Qiang Li 046; Shujian Yu; Kristoffer H. Madsen; Vince D. Calhoun; Armin Iraji (ICASSP Workshops, 2023)

Fusion of Multi-Modal Neuroimaging Data and Association With Cognitive Data. - Mark D. LoPresto; Mohammad A. B. S. Akhonda; Vince D. Calhoun; Tülay Adali (ICASSP Workshops, 2023)

Glacier: Glass-Box Transformer for Interpretable Dynamic Neuroimaging. - Usman Mahmood; Zening Fu; Vince D. Calhoun; Sergey M. Plis (ICASSP, 2023)

Local Spatial Flow Strengths in Bold FMRI are Strongly Impacted by Schizophrenia. - Robyn L. Miller; Victor M. Vergara; Helen Petropoulos; Vince D. Calhoun (ICASSP Workshops, 2023)

Constrained Independent Component Analysis Based on Entropy Bound Minimization for Subgroup Identification from Multi-subject fMRI Data. - Hanlu Yang 001; Fateme Ghayem; Ben Gabrielson; Mohammad A. B. S. Akhonda; Vince D. Calhoun; Tülay Adali (ICASSP, 2023)

A Multi-dimensional Joint ICA Model with Gaussian Copula. - Oktay Agcaoglu; Rogers F. Silva; Deniz Alaçam; Vince D. Calhoun (ICIAP Workshops (2), 2023)

Extraction of One Time Point Dynamic Group Features via Tucker Decomposition of Multi-subject FMRI Data: Application to Schizophrenia. - Yue Han; Qiu-Hua Lin; Li-Dan Kuang; Ying-Guang Hao; Wei-Xing Li; Xiao-Feng Gong; Vince D. Calhoun (ICONIP (9), 2023)

Functional Network Connectivity Based Mental Health Category Prediction from Rest-fMRI Data. - Meenu Ajith; Vince D. Calhoun (ISBI, 2023)

Federated Linear Mixed Effects Modeling for Voxel-Based Morphometry. - Sunitha Basodi; Rajikha Raja; Harshvardhan Gazula; Javier Tomas Romero; Sandeep R. Panta; Vince D. Calhoun (ISBI, 2023)

A Multimodal Deep Learning Approach for Automated Detection and Characterization of Distinctly Salient Features of Alzheimers Disease. - Ishaan Batta; Anees Abrol; Vince D. Calhoun (ISBI, 2023)

MultiViT: Multimodal Vision Transformer for Schizophrenia Prediction using Structural MRI and Functional Network Connectivity Data. - Yuda Bi; Anees Abrol; Zening Fu; Vince D. Calhoun (ISBI, 2023)

Spatial Dynamic Propagation of Network Activity in Resting fMRI Data. - Biozid Bostami; Mukesh Dhamala; Tülay Adali; Vince D. Calhoun; Armin Iraji (ISBI, 2023)

An Adaptive Semi-Supervised Deep Clustering and Its Application to Identifying Biotypes of Psychiatric Disorders. - Yuhui Du; Fulin Wu; Ju Niu; Vince D. Calhoun (ISBI, 2023)

Any-Way Independent Component Analysis with Reference. - Kuaikuai Duan; Rogers F. Silva; Jingyu Liu 001; Oktay Agcaoglu; Vince D. Calhoun (ISBI, 2023)

Identifying Neuropsychiatric Disorder Subtypes and Subtype-Dependent Variation in Diagnostic Deep Learning Classifier Performance. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (ISBI, 2023)

Capturing Spatial Dynamics Using Time-Resolved Referenced-Informed Network Estimation Techniques. - Armin Iraji; Jiayu Chen 003; Ashkan Faghiri; Zening Fu; Jingyu Liu 001; Juan R. Bustillo; Tülay Adali; Mukesh Dhamala; Vince D. Calhoun (ISBI, 2023)

The Nonlinear Brain: Towards Uncovering Hidden Brain Networks Using Explicitly Nonlinear Functional Interaction. - Armin Iraji; Katarzyna Kazimierczak; Jiayu Chen 003; Sara Motlaghian; Karsten Specht; Tülay Adali; Vince D. Calhoun (ISBI, 2023)

Topological Correction of Subject-Level Intrinsic Connectivity Networks. - Noah Lewis; Armin Iraji; Robyn L. Miller; Vince D. Calhoun (ISBI, 2023)

Multimodal Subspace Independent Vector Analysis Better Captures Hidden Relationships in Multimodal Neuroimaging Data. - Xinhui Li; Tülay Adali; Rogers F. Silva; Vince D. Calhoun (ISBI, 2023)

Evaluating Trade-Offs in IVA of Multimodal Neuroimaging using Cross-Platform Multidataset Independent Subspace Analysis. - Xinhui Li; Daniel Khosravinezhad; Vince D. Calhoun; Rogers F. Silva (ISBI, 2023)

Topological Characteristics of 5d Spatially Dynamic Brain Networks in Schizophrenia. - Mustafa S. Salman; Armin Iraji; Noah Lewis; Vince D. Calhoun (ISBI, 2023)

Effective Training Strategy for NN Models of Working Memory Classification with Limited Samples. - Pranav Suresh; Bhaskar Ray; Bishal Thapaliya; Britny Farahdel; Behnam Kazemivash; Jiayu Chen 003; Kuaikuai Duan; Vince D. Calhoun; Jingyu Liu 001 (ISBI, 2023)

Objective Assessment of the Bias Introduced by Baseline Signals in XAI Attribution Methods. - Giorgio Dolci; Federica Cruciani; Ilaria Boscolo Galazzo; Vince D. Calhoun; Gloria Menegaz (MetroXRAINE, 2023)

Joint Structural and Functional Connectivity Learning Based Independent Component Analysis. - Mahshid Fouladivanda; Armin Iraji; Lei Wu 013; Vince D. Calhoun (MLSP, 2023)

BrainForge: An online data analysis platform for integrative neuroimaging acquisition, analysis, and sharing. - Eric Verner; Helen Petropoulos; Bradley T. Baker; Henry Jeremy Bockholt; Jill Fries; Anastasia Bohsali; Rajikha Raja; Duc Hoai Trinh; Vince D. Calhoun (Concurr. Comput. Pract. Exp., 2023)

SalientGrads: Sparse Models for Communication Efficient and Data Aware Distributed Federated Training. - Riyasat Ohib; Bishal Thapaliya; Pratyush Gaggenapalli; Jingyu Liu 001; Vince D. Calhoun; Sergey M. Plis (CoRR, 2023)

Learning low-dimensional dynamics from whole-brain data improves task capture. - Eloy Geenjaar; Donghyun Kim; Riyasat Ohib; Marlena Duda; Amrit Kashyap; Sergey M. Plis; Vince D. Calhoun (CoRR, 2023)

Looking deeper into interpretable deep learning in neuroimaging: a comprehensive survey. - Md. Mahfuzur Rahman; Vince D. Calhoun; Sergey M. Plis (CoRR, 2023)

Predictive Sparse Manifold Transform. - Yujia Xie; Xinhui Li; Vince D. Calhoun (CoRR, 2023)

A Scalable Approach to Independent Vector Analysis by Shared Subspace Separation for Multi-Subject fMRI Analysis. - Mingyu Sun; Ben Gabrielson; Mohammad Abu Baker Siddique Akhonda; Hanlu Yang 001; Francisco Laport; Vince D. Calhoun; Tülay Adali (Sensors, 2023)

A Novel Neighborhood Rough Set-Based Feature Selection Method and Its Application to Biomarker Identification of Schizophrenia. - Ying Xing; Peter V. Kochunov; Theo G. M. van Erp; Tianzhou Ma; Vince D. Calhoun; Yuhui Du (IEEE J. Biomed. Health Informatics, 2023)

Multi-Subject Analysis for Brain Developmental Patterns Discovery via Tensor Decomposition of MEG Data. - Irina Belyaeva; Ben Gabrielson; Yu-Ping Wang 002; Tony W. Wilson; Vince D. Calhoun; Julia M. Stephen; Tülay Adali (Neuroinformatics, 2023)

Correction to: Multi-Subject Analysis for Brain Developmental Patterns Discovery via Tensor Decomposition of MEG Data. - Irina Belyaeva; Ben Gabrielson; Yu-Ping Wang 002; Tony W. Wilson; Vince D. Calhoun; Julia M. Stephen; Tülay Adali (Neuroinformatics, 2023)

An explainable autoencoder with multi-paradigm fMRI fusion for identifying differences in dynamic functional connectivity during brain development. - Faming Xu; Chen Qiao; Huiyu Zhou 001; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002 (Neural Networks, 2023)

Novel methods for elucidating modality importance in multimodal electrophysiology classifiers. - Charles A. Ellis; Mohammad S. Eslampanah Sendi; Rongen Zhang; Darwin A. Carbajal; May D. Wang; Robyn L. Miller; Vince D. Calhoun (Frontiers Neuroinformatics, 2023)

Enhancing collaborative neuroimaging research: introducing COINSTAC Vaults for federated analysis and reproducibility. - 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; et al. (Frontiers Neuroinformatics, 2023)

Identification of Homogeneous Subgroups from Resting-State fMRI Data. - Hanlu Yang 001; Trung Vu 001; Qunfang Long; Vince D. Calhoun; Tülay Adali (Sensors, 2023)

Federated Analysis in COINSTAC Reveals Functional Network Connectivity and Spectral Links to Smoking and Alcohol Consumption in Nearly 2,000 Adolescent Brains. - 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; et al. (Neuroinformatics, 2023)

The Individualized Prediction of Neurocognitive Function in People Living With HIV Based on Clinical and Multimodal Connectome Data. - Xiang Li; Sheri L. Towe; Ryan P. Bell; Rongtao Jiang; Shana A. Hall; Vince D. Calhoun; Christina S. Meade; Jing Sui (IEEE J. Biomed. Health Informatics, 2023)

Latent Similarity Identifies Important Functional Connections for Phenotype Prediction. - Anton Orlichenko; Gang Qu 002; Gemeng Zhang; Binish Patel; Tony W. Wilson; Julia M. Stephen; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Biomed. Eng., 2023)

Interpretable LSTM model reveals transiently-realized patterns of dynamic brain connectivity that predict patient deterioration or recovery from very mild cognitive impairment. - Yutong Gao 002; Noah Lewis; Vince D. Calhoun; Robyn L. Miller (Comput. Biol. Medicine, 2023)

Highlight results, don't hide them: Enhance interpretation, reduce biases and improve reproducibility. - Paul A. Taylor; Richard C. Reynolds; Vince D. Calhoun; Javier Gonzalez-Castillo; Daniel A. Handwerker; Peter A. Bandettini; Amanda F. Mejia; Gang Chen 008 (NeuroImage, 2023)

Disrupted Dynamic Functional Network Connectivity Among Cognitive Control Networks in the Progression of Alzheimer's Disease. - Mohammad S. Eslampanah Sendi; Elaheh Zendehrouh; Zening Fu; Jingyu Liu 001; Yuhui Du; Elizabeth Mormino; David H. Salat; Vince D. Calhoun; Robyn L. Miller (Brain Connect., 2023)

Explainable Multimodal Deep Dictionary Learning to Capture Developmental Differences From Three fMRI Paradigms. - Lan Yang 010; Chen Qiao; Huiyu Zhou 001; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002 (IEEE Trans. Biomed. Eng., 2023)

bids-specification. - 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; et al. (Zenodo, 2023)

Deep learning with explainability for characterizing age-related intrinsic differences in dynamic brain functional connectivity. - Chen Qiao; Bin Gao; Yuechen Liu; Xin-Yu Hu; Wenxing Hu; Vince D. Calhoun; Yu-Ping Wang 002 (Medical Image Anal., 2023)

Improved Dictionary Learning for FMRI Data Analysis Capturing Common and Individual Activation Maps. - Shuai Xu; Rui Jin; Seung-Jun Kim 002; Tülay Adali; Vince D. Calhoun (IEEECONF, 2024)

Denoising Diffusion Probabilistic Models for High-Fidelity fMRI Intrinsic Connectivity Network Data Generation. - Meenu Ajith; Vince D. Calhoun (BHI, 2024)

Constrained Source-based Salience: Network-based Visualization of Deep Learning Neuroimaging Models. - Ishaan Batta; Anees Abrol; Vince D. Calhoun (BHI, 2024)

Integrating Neuroimaging and Genetics via Contrastive Learning for Working Memory. - Pranav Nadigapu Suresh; Behnam Kazemivash; Dawn M. Jensen; Vince D. Calhoun; Jingyu Liu 001 (BHI, 2024)

GPR-SCSANet: Unequal-Length Time Series Normalization with Split-Channel Residual Convolution and Self-Attention for Brain Age Prediction. - Fangling Sun; Chuang Liang; Tülay Adali; Daoqiang Zhang; Rongtao Jiang; Vince D. Calhoun; Shile Qi (BIBM, 2024)

Advanced machine learning in neuroimaging studies via federated learning. - Sunitha Basodi; Javier Tomas Romero; Sandeep R. Panta; Dylan Martin; Sergey M. Plis; Anand D. Sarwate; Vince D. Calhoun (IEEE Big Data, 2024)

Federated Privacy-Preserving Visualization: A Vision Paper. - Ye Tao; Anand D. Sarwate; Sandeep R. Panta; Sergey M. Plis; Vince D. Calhoun (IEEE Big Data, 2024)

Spatiotemporal Vision Transformer for Weakly Supervised Dense Prediction of Dynamic Brain Maps. - Behnam Kazemivash; Armin Iraji; Sergey M. Plis; Vince D. Calhoun (BMVC, 2024)

A Novel Deep Subspace Learning Framework to Automatically Uncover Assessment-Specific Independent Brain Networks. - Ishaan Batta; Anees Abrol; Vince D. Calhoun (CISS, 2024)

A Deep Biclustering Framework for Brain Network Analysis. - Md Abdur Rahaman; Zening Fu; Armin Iraji; Vince D. Calhoun (CVPR Workshops, 2024)

A deep spatio-temporal attention model of dynamic functional network connectivity shows sensitivity to Alzheimer's in asymptomatic individuals. - Yuxiang Wei 008; Anees Abrol; James J. Lah; Deqiang Qiu; Vince D. Calhoun (EMBC, 2024)

Copula linked parallel ICA jointly estimates linked structural and functional MRI brain networks. - Oktay Agcaoglu; Deniz Alaçam; Tülay Adali; Vince D. Calhoun; Rogers F. Silva; Sergey M. Plis; Biozid Bostami (EMBC, 2024)

Identifying Canonical multi-scale Intrinsic Connectivity Networks in Infant resting-state fMRI and their Association with Age. - Prerana Bajracharya; Ashkan Faghiri; Zening Fu; Vince D. Calhoun; Sarah Shultz; Armin Iraji (EMBC, 2024)

Multiband Group Independent Component Analysis: Unveiling Frequency-Dependent Dynamics of Functional Connectivity in Group-Level fMRI Analyses. - Neda Behzadfar; Armin Iraji; Vince D. Calhoun (EMBC, 2024)

Dynamic Functional Network Connectivity Clustering and Harmonization Evaluation Metric. - Biozid Bostami; Noah Lewis; Victor M. Vergara; Vince D. Calhoun (EMBC, 2024)

CGDM-GAN: An Adversarial Network Approach with Self-supervised Learning for Site Effect Removal. - Xiangxiang Cui; Dongmei Zhi; Weizheng Yan; Vince D. Calhoun; Chuanjun Zhuo; Jing Sui (EMBC, 2024)

Functionally-Adaptive Gray and White Matter Structural Basis Sets via Dynamic Fusion of Multimodal MRI Data. - Marlena Duda; Vince D. Calhoun (EMBC, 2024)

NeuroMark PET: Replicable positron emission tomography ICA templates for florbetapir and florbetaben radioligands. - Cyrus Eierud; Zening Fu; Helen Petropoulos; Anastasia Bohsali; Armin Iraji; Melanie Ganz; Cyril R. Pernet; Vince D. Calhoun (EMBC, 2024)

Evaluating Augmentation Approaches for Deep Learning-based Major Depressive Disorder Diagnosis with Raw Electroencephalogram Data. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (EMBC, 2024)

Exploring Schizophrenia Classification in fMRI Data: A Common Spatial Patterns(CSP) Approach for Enhanced Feature Extraction and Classification. - M. Moein Esfahani; Robyn L. Miller; Vince D. Calhoun (EMBC, 2024)

Path-based Differential Analysis in Near-centenarians and Centenarians Brain Network. - Haleh Falakshahi; Hooman Rokham; Vince D. Calhoun (EMBC, 2024)

Brain community detection in the general children population. - Britny Farahdel; Bishal Thapaliya; Pranav Suresh; Bhaskar Ray; Vince D. Calhoun; Jingyu Liu 001 (EMBC, 2024)

Cross-Modality Translation with Generative Adversarial Networks to Unveil Alzheimer's Disease Biomarkers. - Reihaneh Hassanzadeh; Anees Abrol; Hamid Reza Hassanzadeh; Vince D. Calhoun (EMBC, 2024)

Scepter: Weakly Supervised Framework for Spatiotemporal Dense Prediction of 4D Dynamic Brain Networks. - Behnam Kazemivash; Pranav Suresh; Jingyu Liu 001; Dong Hye Ye; Vince D. Calhoun (EMBC, 2024)

Parallel Multilink Joint ICA for Multimodal Fusion of Gray Matter and Multiple Resting fMRI Networks. - K. M. Ibrahim Khalilullah; Oktay Agcaoglu; Marlena Duda; Vince D. Calhoun (EMBC, 2024)

Revealing Alzheimer's Disease Dementia Patterns in [18F]Florbetapir PET with Independent Component Analysis. - Nigar Khasayeva; Cyrus Eierud; Kyle M. Jensen; Enrico Premi; Barbara Borroni; Vince D. Calhoun; Armin Iraji (EMBC, 2024)

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. - Aline Kotoski; Robin Morris; Vince D. Calhoun (EMBC, 2024)

Beyond Artifacts: Rethinking Motion-Related Signals in Resting-State fMRI Analysis. - Samujjwal Kumar; Spencer Kinsey; Kyle M. Jensen; Prerana Bajracharya; Vince D. Calhoun; Armin Iraji (EMBC, 2024)

Joint density distributions of dynamic spatial brain networks show systematic variations at rest. - Krishna Pusuluri; Armin Iraji; Vince D. Calhoun (EMBC, 2024)

SpaDE: Semantic Locality Preserving Biclustering for Neuroimaging Data. - Md Abdur Rahaman; Zening Fu; Armin Iraji; Vince D. Calhoun (EMBC, 2024)

Label Noise-Robust Ensemble Deep Multimodal Framework For Neuroimaging Data. - Hooman Rokham; Haleh Falakshahi; Vince D. Calhoun (EMBC, 2024)

Identifying Reproducibly Important EEG Markers of Schizophrenia with an Explainable Multi-Model Deep Learning Approach. - Martina Lapera Sancho; Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (EMBC, 2024)

Uncovering Effects of Schizophrenia upon a Maximally Significant, Minimally Complex Subset of Default Mode Network Connectivity Features. - Masoud Seraji; Charles A. Ellis; Mohammad S. Eslampanah Sendi; Robyn L. Miller; Vince D. Calhoun (EMBC, 2024)

Neural Complexity Unveiled: Doubly Functionally Independent Primitives (dFIPs) in Psychiatric Risk Score Assessment. - Najme Soleimani; Vince D. Calhoun (EMBC, 2024)

Graph-based deep learning models in the prediction of early-stage Alzheimers. - Bishal Thapaliya; Zundong Wu; Ram Sapkota; Bhaskar Ray; Pranav Suresh; Santosh Ghimire; Vince D. Calhoun; Jingyu Liu 001 (EMBC, 2024)

Classification of Schizophrenia using Intrinsic Connectivity Networks and Incremental Boosting Convolution Neural Networks. - Duc My Vo; Sergey M. Plis; Vince D. Calhoun (EMBC, 2024)

A Cross-Feature Mutual Learning Framework to Integrate Functional Connectivity and Activity for Brain Disorder Classification. - Min Zhao; Rongtao Xu; Dongmei Zhi; Shan Yu; Vince D. Calhoun; Jing Sui (EMBC, 2024)

Assessing Pediatric Cognitive Development via Multisensory Brain Imaging Analysis. - Irina Belyaeva; Yu-Ping Wang 002; Tony W. Wilson; Vince D. Calhoun; Julia M. Stephen; Tülay Adali (EUSIPCO, 2024)

Fusion of Novel FMRI Features Using Independent Vector Analysis for a Multifaceted Characterization of Schizophrenia. - Chunying Jia; Mohammad Abu Baker Siddique Akhonda; Hanlu Yang 001; Vince D. Calhoun; Tülay Adali (EUSIPCO, 2024)

Reproducibility and Replicability in Neuroimaging: Constrained IVA as an Effective Assessment Tool. - Francisco Laport; Adriana Dapena; Trung Vu 001; Hanlu Yang 001; Vince D. Calhoun; Tülay Adali (EUSIPCO, 2024)

Cross-Modal Synthesis of Structural MRI and Functional Connectivity Networks via Conditional ViT-GANs. - Yuda Bi; Anees Abrol; Jing Sui; Vince D. Calhoun (ICASSP, 2024)

Analysis of High-Order Brain Networks Resolved in Time and Frequency Using CP Decomposition. - Ashkan Faghiri; Armin Iraji; Tülay Adali; Vince D. Calhoun (ICASSP, 2024)

Multimodal Imaging Feature Extraction with Reference Canonical Correlation Analysis Underlying Intelligence. - Ram Sapkota; Bishal Thapaliya; Pranav Suresh; Bhaskar Ray; Vince D. Calhoun; Jingyu Liu 001 (ICASSP, 2024)

A Robust and Scalable Method with an Analytic Solution for Multi-Subject FMRI Data Analysis. - Trung Vu 001; Hanlu Yang 001; Francisco Laport; Ben Gabrielson; Vince D. Calhoun; Tülay Adali (ICASSP, 2024)

Subgroup Identification Through Multiplex Community Structure Within Functional Connectivity Networks. - Hanlu Yang 001; Meiby Ortiz-Bouza; Trung Vu 001; Francisco Laport; Vince D. Calhoun; Selin Aviyente; Tülay Adali (ICASSP, 2024)

Multiscale Neuroimaging Features for the Identification of Medication Class and Non-Responders in Mood Disorder Treatment. - Bradley T. Baker; Mustafa S. Salman; Zening Fu; Armin Iraji; Elizabeth A. Osuch; Henry Jeremy Bockholt; Vince D. Calhoun (ISBI, 2024)

Diffusion MRI Allows Capturing the Amyloid-β and τ Proteins Status in Alzheimer's Disease Continuum. - Giorgio Dolci; Federica Cruciani; Lorenza Brusini; Lorenzo Pini; Ilaria Boscolo Galazzo; Vince D. Calhoun; Gloria Menegaz (ISBI, 2024)

Dynamic Fusion of Multimodal MRI Data Captures Flexible, Time-Sensitive Structure-Function Linkages in the Brain. - Marlena Duda; Oktay Agcaoglu; Vince D. Calhoun (ISBI, 2024)

Cross-Sampling Rate Transfer Learning for Enhanced Raw EEG Deep Learning Classifier Performance in Major Depressive Disorder Diagnosis. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (ISBI, 2024)

Voxelwise Intensity Projection for the Spatial Representation of Resting State Functional MRI Networks and Multimodal Deep Learning. - Vaibhavi S. Itkyal; Anees Abrol; Theodore J. LaGrow; Vince D. Calhoun (ISBI, 2024)

Coupling between Time-Varying EEG Spectral Bands and Spatial Dynamic FMRI Networks. - Souvik Phadikar; Krishna Pusuluri; Kyle M. Jensen; Lei Wu 013; Armin Iraji; Vince D. Calhoun (ISBI, 2024)

Replication and Refinement of Brain Age Model for Adolescent Development. - Bhaskar Ray; Jiayu Chen 003; Zening Fu; Pranav Suresh; Bishal Thapaliya; Britny Farahdel; Vince D. Calhoun; Jingyu Liu 001 (ISBI, 2024)

Spatial Sequence Attention Network for Schizophrenia Classification from Structural Brain MR Images. - Nagur Shareef Shaik; Teja Krishna Cherukuri; Vince D. Calhoun; Dong Hye Ye (ISBI, 2024)

Double Functionally Independent Primitives Provide Disorder Specific Fingerprints of Mental Illnesses. - Najme Soleimani; Godfrey D. Pearlson; Armin Iraji; Vince D. Calhoun (ISBI, 2024)

Privacy-Preserving Visualization of Brain Functional Network Connectivity. - Ye Tao; Anand D. Sarwate; Sandeep R. Panta; Sergey M. Plis; Vince D. Calhoun (ISBI, 2024)

Capturing Stretching and Shrinking of Inter-Network Temporal Coupling in FMRI Via WARP Elasticity. - Sir-Lord Wiafe; Ashkan Faghiri; Zening Fu; Robyn L. Miller; Vince D. Calhoun (ISBI, 2024)

Integrated Gradients Demystified: An MRI Case Study on Aβ-T Protein Localization. - Giorgio Dolci; Cristian Morasso; Federica Cruciani; Lorenza Brusini; Lorenzo Pini; Vince D. Calhoun; Ilaria Boscolo Galazzo; Gloria Menegaz (MetroXRAINE, 2024)

Physics-Guided Multi-view Graph Neural Network for Schizophrenia Classification via Structural-Functional Coupling. - Badhan Mazumder; Ayush Kanyal; Lei Wu 013; Vince D. Calhoun; Dong Hye Ye (PRIME@MICCAI, 2024)

Improving Age Prediction: Utilizing LSTM-Based Dynamic Forecasting For Data Augmentation in Multivariate Time Series Analysis. - Yutong Gao 002; Charles A. Ellis; Vince D. Calhoun; Robyn L. Miller (SSIAI, 2024)

Complexity Measures of Psychotic Brain Activity In The FMRI Signal. - Qiang Li 046; Masoud Seraji; Vince D. Calhoun; Armin Iraji (SSIAI, 2024)

Distribution of Connectivity Strengths Across Functional Regions has Higher Entropy in Schizophrenia Patients than in Controls. - Natalia Maksymchuk; Robyn L. Miller; Vince D. Calhoun (SSIAI, 2024)

Markov Spatial Flows in Bold FMRI: A Novel Lens on the Bold Signal Applied To an Imaging Study of Schizophrenia. - Robyn L. Miller; Victor M. Vergara; Vince D. Calhoun (SSIAI, 2024)

Identifying EEG Biomarkers of Depression with Novel Explainable Deep Learning Architectures. - Charles A. Ellis; Martina Lapera Sancho; Robyn L. Miller; Vince D. Calhoun (xAI (4), 2024)

Mode Coresets for Efficient, Interpretable Tensor Decompositions: An Application to Feature Selection in fMRI Analysis. - Ben Gabrielson; Hanlu Yang 001; Trung Vu 001; Vince D. Calhoun; Tülay Adali (IEEE Access, 2024)

Identifying the Relationship Structure Among Multiple Datasets Using Independent Vector Analysis: Application to Multi-Task fMRI Data. - Isabell Lehmann; Tanuj Hasija; Ben Gabrielson; Mohammad A. B. S. Akhonda; Vince D. Calhoun; Tülay Adali (IEEE Access, 2024)

A Roundtable Discussion on Brain Connectivity. - Steven Laureys; Marc Raichle; Karl J. Friston; Susan L. Whitfield-Gabrieli; Jennifer L. Whitwell; Vince D. Calhoun; Linda Douw; Mélanie Boly (Brain Connect., 2024)

A Method to Estimate Longitudinal Change Patterns in Functional Network Connectivity of the Developing Brain Relevant to Psychiatric Problems, Cognition, and Age. - Rekha Saha; Debbrata K. Saha; Md Abdur Rahaman; Zening Fu; Jingyu Liu 001; Vince D. Calhoun (Brain Connect., 2024)

A core tensor sparsity enhancement method for solving Tucker-2 model of multi-subject fMRI data. - Yue Han; Qiu-Hua Lin; Li-Dan Kuang; Bin-Hua Zhao; Xiao-Feng Gong; Fengyu Cong; Yu-Ping Wang 002; Vince D. Calhoun (Biomed. Signal Process. Control., 2024)

Low-Rank Learning by Design: the Role of Network Architecture and Activation Linearity in Gradient Rank Collapse. - Bradley T. Baker; Barak A. Pearlmutter; Robyn L. Miller; Vince D. Calhoun; Sergey M. Plis (CoRR, 2024)

An Interpretable Cross-Attentive Multi-modal MRI Fusion Framework for Schizophrenia Diagnosis. - Ziyu Zhou; Anton Orlichenko; Gang Qu 002; Zening Fu; Vince D. Calhoun; Zhengming Ding; Yu-Ping Wang 002 (CoRR, 2024)

Optimizing Brain-Computer Interface Performance: Advancing EEG Signals Channel Selection through Regularized CSP and SPEA II Multi-Objective Optimization. - M. Moein Esfahani; Hossein Sadati; Vince D. Calhoun (CoRR, 2024)

A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds. - Anton Orlichenko; Gang Qu 002; Ziyu Zhou; Anqi Liu; Hong-Wen Deng; Zhengming Ding; Julia M. Stephen; Tony W. Wilson; Vince D. Calhoun; Yu-Ping Wang 002 (CoRR, 2024)

Unmasking Efficiency: Learning Salient Sparse Models in Non-IID Federated Learning. - Riyasat Ohib; Bishal Thapaliya; Gintare Karolina Dziugaite; Jingyu Liu 001; Vince D. Calhoun; Sergey M. Plis (CoRR, 2024)

Spectral Introspection Identifies Group Training Dynamics in Deep Neural Networks for Neuroimaging. - Bradley T. Baker; Vince D. Calhoun; Sergey M. Plis (CoRR, 2024)

An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease. - Giorgio Dolci; Federica Cruciani; Md Abdur Rahaman; Anees Abrol; Jiayu Chen 003; Zening Fu; Ilaria Boscolo Galazzo; Gloria Menegaz; Vince D. Calhoun (CoRR, 2024)

Multimodal MRI-based Detection of Amyloid Status in Alzheimer's Disease Continuum. - Giorgio Dolci; Charles A. Ellis; Federica Cruciani; Lorenza Brusini; Anees Abrol; Ilaria Boscolo Galazzo; Gloria Menegaz; Vince D. Calhoun (CoRR, 2024)

Hierarchical Spatio-Temporal State-Space Modeling for fMRI Analysis. - Yuxiang Wei 008; Anees Abrol; Reihaneh Hassanzadeh; Vince D. Calhoun (CoRR, 2024)

Copula-Linked Parallel ICA: A Method for Coupling Structural and Functional MRI brain Networks. - Oktay Agcaoglu; Rogers F. Silva; Deniz Alaçam; Sergey M. Plis; Tülay Adali; Vince D. Calhoun (CoRR, 2024)

Generative forecasting of brain activity enhances Alzheimer's classification and interpretation. - Yutong Gao 002; Vince D. Calhoun; Robyn L. Miller (CoRR, 2024)

Efficient federated learning for distributed neuroimaging data. - Bishal Thapaliya; Riyasat Ohib; Eloy Geenjaar; Jingyu Liu 001; Vince D. Calhoun; Sergey M. Plis (Frontiers Neuroinformatics, 2024)

Multiview hyperedge-aware hypergraph embedding learning for multisite, multiatlas fMRI based functional connectivity network analysis. - Wei Wang 018; Li Xiao 002; Gang Qu 002; Vince D. Calhoun; Yu-Ping Wang 002; Xiaoyan Sun 001 (Medical Image Anal., 2024)

Gray matters: ViT-GAN framework for identifying schizophrenia biomarkers linking structural MRI and functional network connectivity. - Yuda Bi; Anees Abrol; Sihan Jia; Jing Sui; Vince D. Calhoun (NeuroImage, 2024)

Explainable spatio-temporal graph evolution learning with applications to dynamic brain network analysis during development. - Longyun Chen; Chen Qiao; Kai Ren; Gang Qu 002; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002 (NeuroImage, 2024)

Neurodevelopmental subtypes of functional brain organization in the ABCD study using a rigorous analytic framework. - Jacob Derosa; Naomi P. Friedman; Vince D. Calhoun; Marie T. Banich (NeuroImage, 2024)

Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities. - Zening Fu; Ishaan Batta; Lei Wu 013; Anees Abrol; Oktay Agcaoglu; Mustafa S. Salman; Yuhui Du; Armin Iraji; Sarah Shultz; Jing Sui; Vince D. Calhoun (NeuroImage, 2024)

A simple but tough-to-beat baseline for fMRI time-series classification. - Pavel Popov; Usman Mahmood; Zening Fu; Carl Yang 001; Vince D. Calhoun; Sergey M. Plis (NeuroImage, 2024)

Local-structure-preservation and redundancy-removal-based feature selection method and its application to the identification of biomarkers for schizophrenia. - Ying Xing; Godfrey D. Pearlson; Peter V. Kochunov; Vince D. Calhoun; Yuhui Du (NeuroImage, 2024)

Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC. - 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; et al. (Patterns, 2024)

Topological state-space estimation of functional human brain networks. - Moo K. Chung; Shih-Gu Huang; Ian C. Carroll; Vince D. Calhoun; H. Hill Goldsmith (PLoS Comput. Biol., 2024)

Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links. - Alex Fedorov; Eloy Geenjaar; Lei Wu 013; Tristan Sylvain; Thomas P. DeRamus; Margaux Luck; Maria B. Misiura; Girish Mittapalle; R. Devon Hjelm; Sergey M. Plis; Vince D. Calhoun (NeuroImage, 2024)

Intra-Atlas Node Size Effects on Graph Metrics in fMRI Data: Implications for Alzheimer's Disease and Cognitive Impairment. - Sahithi Kolla; Haleh Falakshahi; Anees Abrol; Zening Fu; Vince D. Calhoun (Sensors, 2024)

COINSTAC: Decentralizing the future of brain imaging analysis. - Vince D. Calhoun; Sergey M. Plis; Jessica A. Turner; Anand D. Sarwate (Zenodo, 2024)

Striatum- and Cerebellum-Modulated Epileptic Networks Varying Across States with and without Interictal Epileptic Discharges. - 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 001; et al. (Int. J. Neural Syst., 2024)

Decentralized Mixed Effects Modeling in COINSTAC. - Sunitha Basodi; Rajikha Raja; Harshvardhan Gazula; Javier Tomas Romero; Sandeep R. Panta; Thomas Maullin-Sapey; Thomas E. Nichols; Vince D. Calhoun (Neuroinformatics, 2024)

Maximum Classifier Discrepancy Generative Adversarial Network for Jointly Harmonizing Scanner Effects and Improving Reproducibility of Downstream Tasks. - Weizheng Yan; Zening Fu; Rongtao Jiang; Jing Sui; Vince D. Calhoun (IEEE Trans. Biomed. Eng., 2024)

Interpretable Cognitive Ability Prediction: A Comprehensive Gated Graph Transformer Framework for Analyzing Functional Brain Networks. - Gang Qu 002; Anton Orlichenko; Junqi Wang 001; Gemeng Zhang; Li Xiao 002; Kun Zhang 012; Tony W. Wilson; Julia M. Stephen; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Medical Imaging, 2024)

A Dynamic Entropy Approach Reveals Reduced Functional Network Connectivity Trajectory Complexity in Schizophrenia. - David Sutherland Blair; Robyn L. Miller; Vince D. Calhoun (Entropy, 2024)

Learning Spatiotemporal Brain Dynamics in Adolescents via Multimodal MEG and fMRI Data Fusion Using Joint Tensor/Matrix Decomposition. - Irina Belyaeva; Ben Gabrielson; Yu-Ping Wang 002; Tony W. Wilson; Vince D. Calhoun; Julia M. Stephen; Tülay Adali (IEEE Trans. Biomed. Eng., 2024)

The Brain Imaging Data Structure (BIDS) Specification. - 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; et al. (Zenodo, 2024)

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. - Aline Kotoski; Jingyu Liu 001; Robin Morris; Vince D. Calhoun (IEEE Trans. Biomed. Eng., 2024)

Constrained Independent Vector Analysis With Reference for Multi-Subject fMRI Analysis. - Trung Vu 001; Francisco Laport; Hanlu Yang 001; Vince D. Calhoun; Tülay Adali (IEEE Trans. Biomed. Eng., 2024)

A Deep Dynamic Causal Learning Model to Study Changes in Dynamic Effective Connectivity During Brain Development. - Yingying Wang; Chen Qiao; Gang Qu 002; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002 (IEEE Trans. Biomed. Eng., 2024)

Grassmannian Kernels for Efficient and Effective Detection of Group Differences in fMRI Data. - Ashfia Binte Habib; Ben Gabrielson; Hanlu Yang 001; Vince D. Calhoun; Tülay Adali (CISS, 2025)

Adaptive Constrained ICA with Mixing Matrix Column Constraints: Application to fMRI Data. - Chunying Jia; Weixin Wang 005; Trung Vu 001; Hanlu Yang 001; Ben Gabrielson; Vince D. Calhoun; Tülay Adali (CISS, 2025)

Fusion of Multitask fMRI Data with Constrained Independent Vector Analysis. - Emin Erdem Kumbasar; Hanlu Yang 001; Trung Vu 001; Vince D. Calhoun; Tülay Adali (CISS, 2025)

Reference-Guided Parallel Independent Component Analysis: Estimating Cognition Associated Multimodal Patterns In Schizophrenia. - Jingxian Hu; Chuang Liang; Tülay Adali; Qi Zhu 001; Daoqiang Zhang; Rongtao Jiang; Vince D. Calhoun; Shile Qi (ICASSP, 2025)

Adaptive-Similarity-Based Brain Dynamic Functional Connectivity with Spatial-Temporal Attention and Domain Adaptation for Schizophrenia Diagnosis. - Yixin Ji; Vince D. Calhoun; Rongtao Jiang; Daoqiang Zhang; Shile Qi (ICASSP, 2025)

Cooperative and Competitive Functional Connectivity Based on Improved Ising Model. - Gengqian Wei; Chuang Liang; Tülay Adali; Rongtao Jiang; Daoqiang Zhang; Vince D. Calhoun; Shile Qi (ICASSP, 2025)

Low-Rank Tucker Decomposition of Multi-Subject Complex-Valued fMRI Data. - Bin-Hua Zhao; Qiu-Hua Lin; Yue Han; Jia-Yang Song; Yan-Wei Niu; Vince D. Calhoun (ICASSP, 2025)

The Dynamics of Triple Interactions in Resting FMRI: Insights Into Psychotic Disorders. - Qiang Li 046; Vince D. Calhoun; Shiva Mirzaeian; Armin Iraji (ISBI, 2025)

Predictive Modeling of Mood Using Functional Network Connectivity: Differential Impacts in Exercise + Smart and Control Groups. - Meenu Ajith; Dawn M. Aycock; Erin B. Tone; Jingyu Liu 001; Maria B. Misiura; Rebecca Ellis; Sergey M. Plis; Tricia Z. King; Vonetta M. Dotson; Vince D. Calhoun (ISBI, 2025)

Linking Multi-Scale Brain Connectivity with Vigilance, Working Memory, and Behavior in Adolescents. - Prerana Bajracharya; Ram Ballem; Jiayu Chen 003; Pablo Andrés-Camazón; Nigar Khasayeva; Vince D. Calhoun; Jingyu Liu 001; Armin Iraji (ISBI, 2025)

Psychosis Multiscale Functional Network Connectivity Subspace Encodes Sex Specificity and Identifies Sex Biotypes. - Adithya Ram Ballem; Prerana Bajracharya; Pablo André S.-Camazón; Jiayu Chen 003; Vince D. Calhoun; Armin Iraji (ISBI, 2025)

Decentralized ComBat-Mega for Harmonizing FNC Data in Coinstac. - Sunitha Basodi; Charles A. Ellis; Biozid Bostami; Frank G. Hillary; Sandeep R. Panta; Vince D. Calhoun (ISBI, 2025)

Federated Analysis of Neuroimaging Data Using Coinstac. - Sunitha Basodi; Ross Kelly; Javier Tomas Romero; Dylan Martin; Sandeep R. Panta; Sergey M. Plis; Anand D. Sarwate; Vince D. Calhoun (ISBI, 2025)

A New Noisy Label Learning Method for Accurate Brain Age Prediction. - Yuhui Du; Ruotong Li; Zheng Wang; Vince D. Calhoun (ISBI, 2025)

MPIDS: Multi-Group Perturbation Based Individualized Differential Structural Brain Network. - Zixin Huang; Yijie Zhang; Tülay Adali; Rongtao Jiang; Daoqiang Zhang; Vince D. Calhoun; Shile Qi (ISBI, 2025)

Functional Network Connectivity in White Matter: A Group Informed ICA-Based Network Approach. - Vaibhavi S. Itkyal; Armin Iraji; Zening Fu; Vince D. Calhoun (ISBI, 2025)

[18F]Florbetapir Pet Uptake Differences in White Matter Across the Alzheimer's Disease Continuum: From Cognitively Normal to MCI and Dementia. - Nigar Khasayeva; Kyle M. Jensen; Cyrus Eierud; Helen Petropoulos; Vince D. Calhoun; Armin Iraji (ISBI, 2025)

Sex Differences in Coupled Dynamic Functional Connectivity and Structural Brain Morphology: Insights from the ABCD Study. - Aline Kotoski; Sir-Lord Wiafe; Vince D. Calhoun (ISBI, 2025)

Correlation of Correlation Networks: High-Order Interactions in the Topology of Brain Networks. - Qiang Li 046; Jingyu Liu 001; Vince D. Calhoun (ISBI, 2025)

Spontaneous Brain Dynamics Associated with Acceleration of Long-Term Functional Connectome in Postnatal Development. - Liang Ma; Sarah Shultz; Zening Fu; Masoud Seraji; Armin Iraji; Vince D. Calhoun (ISBI, 2025)

Genetics Encoded Joint Embedding of Multimodal Connectomes with Explainable Graph Neural Network for Schizophrenia Classification. - Badhan Mazumder; Lei Wu 013; Vince D. Calhoun; Dong Hye Ye (ISBI, 2025)

Ultra-High Order Independent Component Analysis for Intrinsic Connectivity Networks in Resting-State Functional Magnetic Resonance Imaging Data. - Shiva Mirzaeian; Kyle M. Jensen; Adithya Ram Ballem; Vince D. Calhoun; Armin Iraji (ISBI, 2025)

Longitudinal Patterns of Functional Network Changes Over Four-Year Period Associated with Sex in the Developing Brain. - Rekha Saha; Debbrata K. Saha; Zening Fu; Tülay Adali; Vince D. Calhoun (ISBI, 2025)

Investigating the Impact of Habitual Sleep Quality on Episodic Memory Performance: An Eeg-Based Representational Similarity Analysis. - Masoud Seraji; Soroush Mirjalili; Audrey Duarte; Vince D. Calhoun (ISBI, 2025)

Multi-Modal Imaging Genomics Transformer: Attentive Integration of Imaging with Genomic Biomarkers for Schizophrenia Classification. - Nagur Shareef Shaik; Teja Krishna Cherukuri; Vince D. Calhoun; Dong Hye Ye (ISBI, 2025)

Dynamic Convergence of Multiple Overlapping Brain States as a Biomarker for Mental Disorders. - Najme Soleimani; Vince D. Calhoun (ISBI, 2025)

SELF-Clustering Graph Transformer Approach to Model Resting State Functional Brain Activity. - Bishal Thapaliya; Esra Akbas; Ram Sapkota; Bhaskar Ray; Vince D. Calhoun; Jingyu Liu 001 (ISBI, 2025)

THIDS: Triplet High-Order Individual Differential Structural Brain Network. - Dailin Wen; Chunzhi Zhao; Tülay Adali; Daoqiang Zhang; Vince D. Calhoun; Shile Qi (ISBI, 2025)

Dynamic Fusion: Merging Structural and Functional Connectivity Dynamics Via Joint CMICA. - Lei Wu 013; Marlena Duda; Armin Iraji; Vince D. Calhoun (ISBI, 2025)

Multiset FMRI Data Analysis with Subject Group Information using Structured Dictionary Learning. - Shuai Xu; Rui Jin; Seung-Jun Kim 002; Vince D. Calhoun; Tülay Adali (ISBI, 2025)

Hierarchical Spatio-Temporal State-Space Modeling for fMRI Analysis. - Yuxiang Wei 004; Anees Abrol; Vince D. Calhoun (RECOMB, 2025)

Hybrid Dynamic High-Order Functional Correlations and Divisive Normalization for Improved Classification of Schizophrenia and Bipolar Disorder. - Qiang Li 046; Vince D. Calhoun (UniReps, 2025)

MJNMF-GAT: Multi-Task Joint Non-Negative Matrix Factorization Graph Attention Network for Understanding Adolescent Neurodevelopment. - Binish Patel; Tony W. Wilson; Julia M. Stephen; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Access, 2025)

A Flexible Constrained ICA Approach for Multisubject fMRI Analysis. - Hanlu Yang 001; Trung Vu 001; Ehsan Ahmed Dhrubo; Vince D. Calhoun; Tülay Adali (Int. J. Biomed. Imaging, 2025)

A cross-feature mutual learning framework integrating multiple features for brain disorder diagnosis. - Xiangxiang Cui; Min Zhao; Dongmei Zhi; Aichen Feng; Yuhui Du; Vince D. Calhoun; Jing Sui (Neurocomputing, 2025)

Integrated brain connectivity analysis with fMRI, DTI, and sMRI powered by interpretable graph neural networks. - Gang Qu 002; Ziyu Zhou; Vince D. Calhoun; Aiying Zhang; Yu-Ping Wang 002 (Medical Image Anal., 2025)

Brain networks and intelligence: A graph neural network based approach to resting state fMRI data. - Bishal Thapaliya; Esra Akbas; Jiayu Chen 003; Ram Sapkota; Bhaskar Ray; Pranav Suresh; Vince D. Calhoun; Jingyu Liu 001 (Medical Image Anal., 2025)

DSAM: A deep learning framework for analyzing temporal and spatial dynamics in brain networks. - Bishal Thapaliya; Robyn L. Miller; Jiayu Chen 003; Yu-Ping Wang 002; Esra Akbas; Ram Sapkota; Bhaskar Ray; Pranav Suresh; Santosh Ghimire; Vince D. Calhoun; Jingyu Liu 001 (Medical Image Anal., 2025)

Developmental trajectory of neural activity underlying motor control differs by sequence complexity and motor stage. - Thomas W. Ward; Jackson Derby; Jake J. Son; Peihan J. Huang; Danielle L. Rice; Grace C. Ende; Anna T. Coutant; Erica L. Steiner; Vince D. Calhoun; Yu-Ping Wang; Julia M. Stephen; Elizabeth Heinrichs-Graham; et al. (NeuroImage, 2025)

Tensor dictionary-based heterogeneous transfer learning to study emotion-related gender differences in brain. - Lan Yang 010; Chen Qiao; Takafumi Kanamori; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002 (Neural Networks, 2025)

Confound Controlled Multimodal Neuroimaging Data Fusion and Its Application to Developmental Disorders. - Chuang Liang; Rogers F. Silva; Tülay Adali; Rongtao Jiang; Daoqiang Zhang; Shile Qi; Vince D. Calhoun (IEEE Trans. Image Process., 2025)

Large-Scale Independent Vector Analysis (IVA-G) via Coresets. - Ben Gabrielson; Hanlu Yang 001; Trung Vu 001; Vince D. Calhoun; Tülay Adali (IEEE Trans. Signal Process., 2025)

Rethinking Functional Brain Connectome Analysis: Do Graph Deep Learning Models Help? - Keqi Han; Yao Su 003; Lifang He 001; Liang Zhan; Sergey M. Plis; Vince D. Calhoun; Carl Yang 001 (CoRR, 2025)

A Deep Spatio-Temporal Architecture for Dynamic Effective Connectivity Network Analysis Based on Dynamic Causal Discovery. - Faming Xu; Yiding Wang; Chen Qiao; Gang Qu 002; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002 (CoRR, 2025)

A Privacy-Preserving Domain Adversarial Federated learning for multi-site brain functional connectivity analysis. - Yipu Zhang; Likai Wang 010; Kuan-Jui Su; Aiying Zhang; Hao Zhu; Xiaowen Liu; Hui Shen; Vince D. Calhoun; Yuping Wang; Hong-Wen Deng (CoRR, 2025)

An Explainable Unified Framework of Spatio-Temporal Coupling Learning With Application to Dynamic Brain Functional Connectivity Analysis. - Bin Gao; Aiju Yu; Chen Qiao; Vince D. Calhoun; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002 (IEEE Trans. Medical Imaging, 2025)

4D Multimodal Co-attention Fusion Network with Latent Contrastive Alignment for Alzheimer's Diagnosis. - Yuxiang Wei; Yanteng Zhang; Xi Xiao; Tianyang Wang; Xiao Wang 004; Vince D. Calhoun (CoRR, 2025)

Alterations in Gray Matter Structure Linked to Frequency-Specific Cortico-Subcortical Connectivity in Schizophrenia via Multimodal Data Fusion. - 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; et al. (Neuroinformatics, 2025)

Mapping minds not averages: a scalable subject-specific manifold learning framework for neuroimaging data. - Eloy Geenjaar; Vince D. Calhoun (CoRR, 2025)

Unified Cross-Modal Attention-Mixer Based Structural-Functional Connectomics Fusion for Neuropsychiatric Disorder Diagnosis. - Badhan Mazumder; Lei Wu 013; Vince D. Calhoun; Dong Hye Ye (CoRR, 2025)

MoRE-Brain: Routed Mixture of Experts for Interpretable and Generalizable Cross-Subject fMRI Visual Decoding. - Yuxiang Wei; Yanteng Zhang; Xi Xiao; Tianyang Wang; Xiao Wang 004; Vince D. Calhoun (CoRR, 2025)

Causal Graph Recovery in Neuroimaging through Answer Set Programming. - Mohammadsajad Abavisani; Kseniya Solovyeva; David Danks; Vince D. Calhoun; Sergey M. Plis (CoRR, 2025)

GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis. - Hu Xu; Jingling Yang; Sihan Jia; Yuda Bi; Vince D. Calhoun (CoRR, 2025)

MultiViT2: A Data-augmented Multimodal Neuroimaging Prediction Framework via Latent Diffusion Model. - Yuda Bi; Sihan Jia; Yutong Gao 002; Anees Abrol; Zening Fu; Vince D. Calhoun (CoRR, 2025)

Sharing Neuroimaging Data with Squirrel - A Relational Data Format to Store Raw to Analyzed Data and Everything in Between. - Gregory A. Book; Vince D. Calhoun; Michael C. Stevens 001; Godfrey D. Pearlson (Neuroinformatics, 2025)

A graph transformer-based foundation model for brain functional connectivity network. - Yulong Wang; Vince D. Calhoun; Godfrey D. Pearlson; Peter V. Kochunov; Theo G. M. van Erp; Yuhui Du (Pattern Recognit., 2026)