Vince D. Calhoun

Orcid: 0000-0001-9058-0747

Affiliations:
  • University of New Mexico, Albuquerque, USA


According to our database1, Vince D. Calhoun authored at least 724 papers between 1999 and 2024.

Collaborative distances:

Awards

IEEE Fellow

IEEE Fellow 2013, "For contributions to data-driven processing of multimodal brain imaging and genetic data".

Timeline

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Bibliography

2024
Learning Spatiotemporal Brain Dynamics in Adolescents via Multimodal MEG and fMRI Data Fusion Using Joint Tensor/Matrix Decomposition.
IEEE Trans. Biomed. Eng., July, 2024

A Dynamic Entropy Approach Reveals Reduced Functional Network Connectivity Trajectory Complexity in Schizophrenia.
Entropy, July, 2024

Interpretable Cognitive Ability Prediction: A Comprehensive Gated Graph Transformer Framework for Analyzing Functional Brain Networks.
IEEE Trans. Medical Imaging, April, 2024

Maximum Classifier Discrepancy Generative Adversarial Network for Jointly Harmonizing Scanner Effects and Improving Reproducibility of Downstream Tasks.
IEEE Trans. Biomed. Eng., April, 2024

Decentralized Mixed Effects Modeling in COINSTAC.
Neuroinformatics, April, 2024

Striatum- and Cerebellum-Modulated Epileptic Networks Varying Across States with and without Interictal Epileptic Discharges.
Int. J. Neural Syst., April, 2024

COINSTAC: Decentralizing the future of brain imaging analysis.
Dataset, March, 2024

Intra-Atlas Node Size Effects on Graph Metrics in fMRI Data: Implications for Alzheimer's Disease and Cognitive Impairment.
Sensors, February, 2024

Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links.
NeuroImage, January, 2024

Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC.
Patterns, 2024

Local-structure-preservation and redundancy-removal-based feature selection method and its application to the identification of biomarkers for schizophrenia.
NeuroImage, 2024

Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities.
NeuroImage, 2024

Explainable spatio-temporal graph evolution learning with applications to dynamic brain network analysis during development.
NeuroImage, 2024

Gray matters: ViT-GAN framework for identifying schizophrenia biomarkers linking structural MRI and functional network connectivity.
NeuroImage, 2024

Multiview hyperedge-aware hypergraph embedding learning for multisite, multiatlas fMRI based functional connectivity network analysis.
Medical Image Anal., 2024

Efficient federated learning for distributed neuroimaging data.
Frontiers Neuroinformatics, 2024

Integrated Brain Connectivity Analysis with fMRI, DTI, and sMRI Powered by Interpretable Graph Neural Networks.
CoRR, 2024

Hierarchical Spatio-Temporal State-Space Modeling for fMRI Analysis.
CoRR, 2024

A deep spatio-temporal attention model of dynamic functional network connectivity shows sensitivity to Alzheimer's in asymptomatic individuals.
CoRR, 2024

Multi-modal Imaging Genomics Transformer: Attentive Integration of Imaging with Genomic Biomarkers for Schizophrenia Classification.
CoRR, 2024

Multimodal MRI-based Detection of Amyloid Status in Alzheimer's Disease Continuum.
CoRR, 2024

An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease.
CoRR, 2024

Spectral Introspection Identifies Group Training Dynamics in Deep Neural Networks for Neuroimaging.
CoRR, 2024

DSAM: A Deep Learning Framework for Analyzing Temporal and Spatial Dynamics in Brain Networks.
CoRR, 2024

Unmasking Efficiency: Learning Salient Sparse Models in Non-IID Federated Learning.
CoRR, 2024

A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds.
CoRR, 2024

Cross-Modality Translation with Generative Adversarial Networks to Unveil Alzheimer's Disease Biomarkers.
CoRR, 2024

Optimizing Brain-Computer Interface Performance: Advancing EEG Signals Channel Selection through Regularized CSP and SPEA II Multi-Objective Optimization.
CoRR, 2024

An Interpretable Cross-Attentive Multi-modal MRI Fusion Framework for Schizophrenia Diagnosis.
CoRR, 2024

Low-Rank Learning by Design: the Role of Network Architecture and Activation Linearity in Gradient Rank Collapse.
CoRR, 2024

A core tensor sparsity enhancement method for solving Tucker-2 model of multi-subject fMRI data.
Biomed. Signal Process. Control., 2024

A Method to Estimate Longitudinal Change Patterns in Functional Network Connectivity of the Developing Brain Relevant to Psychiatric Problems, Cognition, and Age.
Brain Connect., 2024

A Roundtable Discussion on Brain Connectivity.
Brain Connect., 2024

Identifying the Relationship Structure Among Multiple Datasets Using Independent Vector Analysis: Application to Multi-Task fMRI Data.
IEEE Access, 2024

Identifying EEG Biomarkers of Depression with Novel Explainable Deep Learning Architectures.
Proceedings of the Explainable Artificial Intelligence, 2024

Markov Spatial Flows in Bold FMRI: A Novel Lens on the Bold Signal Applied To an Imaging Study of Schizophrenia.
Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, 2024

Distribution of Connectivity Strengths Across Functional Regions has Higher Entropy in Schizophrenia Patients than in Controls.
Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, 2024

Complexity Measures of Psychotic Brain Activity In The FMRI Signal.
Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, 2024

Improving Age Prediction: Utilizing LSTM-Based Dynamic Forecasting For Data Augmentation in Multivariate Time Series Analysis.
Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, 2024

Physics-Guided Multi-view Graph Neural Network for Schizophrenia Classification via Structural-Functional Coupling.
Proceedings of the Predictive Intelligence in Medicine - 7th International Workshop, 2024

Capturing Stretching and Shrinking of Inter-Network Temporal Coupling in FMRI Via WARP Elasticity.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Privacy-Preserving Visualization of Brain Functional Network Connectivity.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Double Functionally Independent Primitives Provide Disorder Specific Fingerprints of Mental Illnesses.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Spatial Sequence Attention Network for Schizophrenia Classification from Structural Brain MR Images.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Replication and Refinement of Brain Age Model for Adolescent Development.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Coupling between Time-Varying EEG Spectral Bands and Spatial Dynamic FMRI Networks.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Voxelwise Intensity Projection for the Spatial Representation of Resting State Functional MRI Networks and Multimodal Deep Learning.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Cross-Sampling Rate Transfer Learning for Enhanced Raw EEG Deep Learning Classifier Performance in Major Depressive Disorder Diagnosis.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Dynamic Fusion of Multimodal MRI Data Captures Flexible, Time-Sensitive Structure-Function Linkages in the Brain.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Diffusion MRI Allows Capturing the Amyloid-β and τ Proteins Status in Alzheimer's Disease Continuum.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Multiscale Neuroimaging Features for the Identification of Medication Class and Non-Responders in Mood Disorder Treatment.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Subgroup Identification Through Multiplex Community Structure Within Functional Connectivity Networks.
Proceedings of the IEEE International Conference on Acoustics, 2024

A Robust and Scalable Method with an Analytic Solution for Multi-Subject FMRI Data Analysis.
Proceedings of the IEEE International Conference on Acoustics, 2024

Multimodal Imaging Feature Extraction with Reference Canonical Correlation Analysis Underlying Intelligence.
Proceedings of the IEEE International Conference on Acoustics, 2024

Analysis of High-Order Brain Networks Resolved in Time and Frequency Using CP Decomposition.
Proceedings of the IEEE International Conference on Acoustics, 2024

Cross-Modal Synthesis of Structural MRI and Functional Connectivity Networks via Conditional ViT-GANs.
Proceedings of the IEEE International Conference on Acoustics, 2024

Reproducibility and Replicability in Neuroimaging: Constrained IVA as an Effective Assessment Tool.
Proceedings of the 32nd European Signal Processing Conference, 2024

Fusion of Novel FMRI Features Using Independent Vector Analysis for a Multifaceted Characterization of Schizophrenia.
Proceedings of the 32nd European Signal Processing Conference, 2024

Assessing Pediatric Cognitive Development via Multisensory Brain Imaging Analysis.
Proceedings of the 32nd European Signal Processing Conference, 2024

A Deep Biclustering Framework for Brain Network Analysis.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

A Novel Deep Subspace Learning Framework to Automatically Uncover Assessment-Specific Independent Brain Networks.
Proceedings of the 58th Annual Conference on Information Sciences and Systems, 2024

2023
Deep learning with explainability for characterizing age-related intrinsic differences in dynamic brain functional connectivity.
Medical Image Anal., December, 2023

Explainable Multimodal Deep Dictionary Learning to Capture Developmental Differences From Three fMRI Paradigms.
IEEE Trans. Biomed. Eng., August, 2023

Disrupted Dynamic Functional Network Connectivity Among Cognitive Control Networks in the Progression of Alzheimer's Disease.
Brain Connect., August, 2023

Highlight results, don't hide them: Enhance interpretation, reduce biases and improve reproducibility.
NeuroImage, July, 2023

Interpretable LSTM model reveals transiently-realized patterns of dynamic brain connectivity that predict patient deterioration or recovery from very mild cognitive impairment.
Comput. Biol. Medicine, July, 2023

Latent Similarity Identifies Important Functional Connections for Phenotype Prediction.
IEEE Trans. Biomed. Eng., June, 2023

The Individualized Prediction of Neurocognitive Function in People Living With HIV Based on Clinical and Multimodal Connectome Data.
IEEE J. Biomed. Health Informatics, April, 2023

Federated Analysis in COINSTAC Reveals Functional Network Connectivity and Spectral Links to Smoking and Alcohol Consumption in Nearly 2,000 Adolescent Brains.
Neuroinformatics, April, 2023

Identification of Homogeneous Subgroups from Resting-State fMRI Data.
Sensors, March, 2023

Enhancing collaborative neuroimaging research: introducing COINSTAC Vaults for federated analysis and reproducibility.
Frontiers Neuroinformatics, March, 2023

Novel methods for elucidating modality importance in multimodal electrophysiology classifiers.
Frontiers Neuroinformatics, March, 2023

An explainable autoencoder with multi-paradigm fMRI fusion for identifying differences in dynamic functional connectivity during brain development.
Neural Networks, February, 2023

Correction to: Multi-Subject Analysis for Brain Developmental Patterns Discovery via Tensor Decomposition of MEG Data.
Neuroinformatics, January, 2023

Multi-Subject Analysis for Brain Developmental Patterns Discovery via Tensor Decomposition of MEG Data.
Neuroinformatics, January, 2023

A Novel Neighborhood Rough Set-Based Feature Selection Method and Its Application to Biomarker Identification of Schizophrenia.
IEEE J. Biomed. Health Informatics, 2023

A Scalable Approach to Independent Vector Analysis by Shared Subspace Separation for Multi-Subject fMRI Analysis.
Sensors, 2023

Brain Networks and Intelligence: A Graph Neural Network Based Approach to Resting State fMRI Data.
CoRR, 2023

Predictive Sparse Manifold Transform.
CoRR, 2023

Looking deeper into interpretable deep learning in neuroimaging: a comprehensive survey.
CoRR, 2023

Learning low-dimensional dynamics from whole-brain data improves task capture.
CoRR, 2023

SalientGrads: Sparse Models for Communication Efficient and Data Aware Distributed Federated Training.
CoRR, 2023

BrainForge: An online data analysis platform for integrative neuroimaging acquisition, analysis, and sharing.
Concurr. Comput. Pract. Exp., 2023

Joint Structural and Functional Connectivity Learning Based Independent Component Analysis.
Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

Objective Assessment of the Bias Introduced by Baseline Signals in XAI Attribution Methods.
Proceedings of the IEEE International Conference on Metrology for eXtended Reality, 2023

Effective Training Strategy for NN Models of Working Memory Classification with Limited Samples.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Topological Characteristics of 5d Spatially Dynamic Brain Networks in Schizophrenia.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Evaluating Trade-Offs in IVA of Multimodal Neuroimaging using Cross-Platform Multidataset Independent Subspace Analysis.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Multimodal Subspace Independent Vector Analysis Better Captures Hidden Relationships in Multimodal Neuroimaging Data.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Topological Correction of Subject-Level Intrinsic Connectivity Networks.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

The Nonlinear Brain: Towards Uncovering Hidden Brain Networks Using Explicitly Nonlinear Functional Interaction.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Capturing Spatial Dynamics Using Time-Resolved Referenced-Informed Network Estimation Techniques.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Identifying Neuropsychiatric Disorder Subtypes and Subtype-Dependent Variation in Diagnostic Deep Learning Classifier Performance.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Any-Way Independent Component Analysis with Reference.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

An Adaptive Semi-Supervised Deep Clustering and Its Application to Identifying Biotypes of Psychiatric Disorders.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Spatial Dynamic Propagation of Network Activity in Resting fMRI Data.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

MultiViT: Multimodal Vision Transformer for Schizophrenia Prediction using Structural MRI and Functional Network Connectivity Data.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

A Multimodal Deep Learning Approach for Automated Detection and Characterization of Distinctly Salient Features of Alzheimers Disease.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Federated Linear Mixed Effects Modeling for Voxel-Based Morphometry.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Functional Network Connectivity Based Mental Health Category Prediction from Rest-fMRI Data.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Extraction of One Time Point Dynamic Group Features via Tucker Decomposition of Multi-subject FMRI Data: Application to Schizophrenia.
Proceedings of the Neural Information Processing - 30th International Conference, 2023

A Multi-dimensional Joint ICA Model with Gaussian Copula.
Proceedings of the Image Analysis and Processing - ICIAP 2023 Workshops, 2023

Constrained Independent Component Analysis Based on Entropy Bound Minimization for Subgroup Identification from Multi-subject fMRI Data.
Proceedings of the IEEE International Conference on Acoustics, 2023

Local Spatial Flow Strengths in Bold FMRI are Strongly Impacted by Schizophrenia.
Proceedings of the IEEE International Conference on Acoustics, 2023

Glacier: Glass-Box Transformer for Interpretable Dynamic Neuroimaging.
Proceedings of the IEEE International Conference on Acoustics, 2023

Fusion of Multi-Modal Neuroimaging Data and Association With Cognitive Data.
Proceedings of the IEEE International Conference on Acoustics, 2023

Higher-Order Organization in the Human Brain From Matrix-Based Rényi's Entropy.
Proceedings of the IEEE International Conference on Acoustics, 2023

Multi-Modal Deep Learning on Imaging Genetics for Schizophrenia Classification.
Proceedings of the IEEE International Conference on Acoustics, 2023

New Interpretable Patterns and Discriminative Features from Brain Functional Network Connectivity using Dictionary Learning.
Proceedings of the IEEE International Conference on Acoustics, 2023

Independent Vector Analysis with Multivariate Gaussian Model: a Scalable Method by Multilinear Regression.
Proceedings of the IEEE International Conference on Acoustics, 2023

Novel Approach Explains Spatio-Spectral Interactions In Raw Electroencephalogram Deep Learning Classifiers.
Proceedings of the IEEE International Conference on Acoustics, 2023

Deep Generative Transfer Learning Predicts Conversion To Alzheimer'S Disease From Neuroimaging Genomics Data.
Proceedings of the IEEE International Conference on Acoustics, 2023

Coupled CP Tensor Decomposition with Shared and Distinct Components for Multi-Task Fmri Data Fusion.
Proceedings of the IEEE International Conference on Acoustics, 2023

Towards a multimodal neuroimaging-based risk score for Alzheimer's disease by combining clinical and large N>37000 population data.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

Phase and amplitude, two sides of functional connectivity.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

Functional and Structural Longitudinal Change Patterns in Adolescent Brain.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

A Multivariate Method for Estimating and comparing whole brain functional connectomes from fMRI and PET data.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

A Deep Learning Approach for Psychosis Spectrum Label Noise Detection from Multimodal Neuroimaging Data.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

Decentralized Parallel Independent Component Analysis for Multimodal, Multisite Data.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

Hyperlocal Spatial Flows in BOLD fMRI Expose Novel Brain-Based Correlates of Schizophrenia.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

ICA-based Individualized Differential Structure Similarity Networks for Predicting Symptom Scores in Adolescents with Major Depressive Disorder.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

Network Differential in Gaussian Graphical Models from Multimodal Neuroimaging Data.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

Neuropsychiatric Disorder Subtyping Via Clustered Deep Learning Classifier Explanations.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

A Convolutional Autoencoder-based Explainable Clustering Approach for Resting-State EEG Analysis.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

A Novel Explainable Fuzzy Clustering Approach for fMRI Dynamic Functional Network Connectivity Analysis.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

How Does Aging Affect Whole-brain Functional Network Connectivity? Evidence from An ICA Method.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

Improving Multichannel Raw Electroencephalography-based Diagnosis of Major Depressive Disorder via Transfer Learning with Single Channel Sleep Stage Data.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

Improving Explainability for Single-Channel EEG Deep Learning Classifiers via Interpretable Filters and Activation Analysis.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

An Explainable and Robust Deep Learning Approach for Automated Electroencephalography-Based Schizophrenia Diagnosis.
Proceedings of the 23rd IEEE International Conference on Bioinformatics and Bioengineering, 2023

Multimodal Fusion of Functional and Structural Data to Recognize Longitudinal Change Patterns in the Adolescent Brain.
Proceedings of the IEEE EMBS International Conference on Biomedical and Health Informatics, 2023

Reproducibility in Joint Blind Source Separation: Application to fMRI Analysis.
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

Flexible Multisubject Multiset FMRI Data Analysis Using Robust Discriminative Dictionary Learning.
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

REGRESSION-ASSISTED INDEPENDENT VECTOR ANALYSIS: A SOLUTION TO LARGE-SCALE FMRI DATA ANALYSIS.
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

2022
An AO-ADMM Approach to Constraining PARAFAC2 on All Modes.
SIAM J. Math. Data Sci., September, 2022

A Systematic Approach for Explaining Time and Frequency Features Extracted by Convolutional Neural Networks From Raw Electroencephalography Data.
Frontiers Neuroinformatics, August, 2022

Multi-Modal Imaging Genetics Data Fusion via a Hypergraph-Based Manifold Regularization: Application to Schizophrenia Study.
IEEE Trans. Medical Imaging, 2022

Low-Rank Tucker-2 Model for Multi-Subject fMRI Data Decomposition With Spatial Sparsity Constraint.
IEEE Trans. Medical Imaging, 2022

Group Sparse Joint Non-Negative Matrix Factorization on Orthogonal Subspace for Multi-Modal Imaging Genetics Data Analysis.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Distance Correlation-Based Brain Functional Connectivity Estimation and Non-Convex Multi-Task Learning for Developmental fMRI Studies.
IEEE Trans. Biomed. Eng., 2022

Deep Learning in Neuroimaging: Promises and challenges.
IEEE Signal Process. Mag., 2022

Deep Learning in Biological Image and Signal Processing [From the Guest Editors].
IEEE Signal Process. Mag., 2022

Reproducibility in Matrix and Tensor Decompositions: Focus on model match, interpretability, and uniqueness.
IEEE Signal Process. Mag., 2022

Association of Neuroimaging Data with Behavioral Variables: A Class of Multivariate Methods and Their Comparison Using Multi-Task FMRI Data.
Sensors, 2022

ENIGMA + COINSTAC: Improving Findability, Accessibility, Interoperability, and Re-usability.
Neuroinformatics, 2022

NeuroCrypt: Machine Learning Over Encrypted Distributed Neuroimaging Data.
Neuroinformatics, 2022

Federated Analysis of Neuroimaging Data: A Review of the Field.
Neuroinformatics, 2022

Building Models of Functional Interactions Among Brain Domains that Encode Varying Information Complexity: A Schizophrenia Case Study.
Neuroinformatics, 2022

Decentralized Brain Age Estimation Using MRI Data.
Neuroinformatics, 2022

A dynamic graph convolutional neural network framework reveals new insights into connectome dysfunctions in ADHD.
NeuroImage, 2022

Detecting abnormal connectivity in schizophrenia via a joint directed acyclic graph estimation model.
NeuroImage, 2022

Longitudinal changes in the neural oscillatory dynamics underlying abstract reasoning in children and adolescents.
NeuroImage, 2022

Individual differences in amygdala volumes predict changes in functional connectivity between subcortical and cognitive control networks throughout adolescence.
NeuroImage, 2022

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

Eyes-closed versus eyes-open differences in spontaneous neural dynamics during development.
NeuroImage, 2022

Through the looking glass: Deep interpretable dynamic directed connectivity in resting fMRI.
NeuroImage, 2022

Moving beyond the 'CAP' of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping.
NeuroImage, 2022

The development of sensorimotor cortical oscillations is mediated by pubertal testosterone.
NeuroImage, 2022

Cerebral blood flow and cardiovascular risk effects on resting brain regional homogeneity.
NeuroImage, 2022

An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data.
Medical Image Anal., 2022

SSPNet: An interpretable 3D-CNN for classification of schizophrenia using phase maps of resting-state complex-valued fMRI data.
Medical Image Anal., 2022

CommsVAE: Learning the brain's macroscale communication dynamics using coupled sequential VAEs.
CoRR, 2022

Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes.
CoRR, 2022

Pipeline-Invariant Representation Learning for Neuroimaging.
CoRR, 2022

Spatio-temporally separable non-linear latent factor learning: an application to somatomotor cortex fMRI data.
CoRR, 2022

Dynamic Persistent Homology for Brain Networks via Wasserstein Graph Clustering.
CoRR, 2022

An Approach to Automatically Label and Order Brain Activity/Component Maps.
Brain Connect., 2022

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

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

Lateralization of Resting-State Networks in Children: Association with Age, Sex, Handedness, Intelligence Quotient, and Behavior.
Brain Connect., 2022

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

Two-Dimensional Attentive Fusion for Multi-Modal Learning of Neuroimaging and Genomics Data.
Proceedings of the 32nd IEEE International Workshop on Machine Learning for Signal Processing, 2022

Going from lines to triangles: A formulation for time-frequency moments of time-series with application to study fMRI.
Proceedings of the 14th IEEE Image, Video, and Multidimensional Signal Processing Workshop, 2022

Multimodal fusion of brain imaging data with joint non-linear independent component analysis.
Proceedings of the 14th IEEE Image, Video, and Multidimensional Signal Processing Workshop, 2022

Longitudinal Whole-Brain Functional Network Change Patterns Over A Two-Year Period In The ABCD Data.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Decentralized Spatially Constrained Source-Based Morphometry.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

A Contrastive Learning-Based Approach To Measure Spatial Coupling Among Brain Networks: A Schizophrenia Study.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Single Sideband Modulation as a Tool To Improve Functional Connectivity Estimation.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Refacing Defaced MRI with PixelCNN.
Proceedings of the International Joint Conference on Neural Networks, 2022

Deep Dynamic Effective Connectivity Estimation from Multivariate Time Series.
Proceedings of the International Joint Conference on Neural Networks, 2022

Deep Learning From Imaging Genetics for Schizophrenia Classification.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

Explainable AI (XAI) In Biomedical Signal and Image Processing: Promises and Challenges.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

Independent Vector Analysis Based Subgroup Identification from Multisubject fMRI Data.
Proceedings of the IEEE International Conference on Acoustics, 2022

Multi-Task fMRI Data Fusion Using IVA and PARAFAC2.
Proceedings of the IEEE International Conference on Acoustics, 2022

An Accelerated Rank-(L, L, 1, 1) Block Term Decomposition Of Multi-Subject Fmri Data Under Spatial Orthonormality Constraint.
Proceedings of the IEEE International Conference on Acoustics, 2022

'Harmless' adversarial network harmonization approach for removing site effects and improving reproducibility in neuroimaging studies.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Comparison of Energy Signals from the 4D DWT of Resting State FMRI Data Obtained from a Study on Schizophrenia.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

A two-step clustering-based pipeline for big dynamic functional network connectivity data.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Default mode network dynamic functional network connectivity predicts psychotic symptom severity.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Mind the gap: functional network connectivity interpolation between schizophrenia patients and controls using a variational autoencoder.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

A 5D approach to study spatio-temporal dynamism of resting-state brain networks in schizophrenia.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

A Supervised Contrastive Learning-based Analysis of rs-tMRI Data Captures Gender Differences in Nonlinear Functional Network Coupling.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Transient Intervals of Significantly Different Whole Brain Connectivity Predict Recovery vs. Progression from Mild Cognitive Impairment: New Insights from Interpretable LSTM Classifiers.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Functional Connectivity Stability: A Signature of Neurocognitive Development and Psychiatric Problems in Children.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

A Unified Framework for Modularizing and Comparing Time-Resolved Functional Connectivity Methods.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

An Unsupervised Feature Learning Approach for Elucidating Hidden Dynamics in rs-fMRI Functional Network Connectivity.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

A Model Visualization-based Approach for Insight into Waveforms and Spectra Learned by CNNs.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Spatially Constrained ICA Enables Robust Detection of Schizophrenia from Very Short Resting-state fMRI.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Multi-Site Mild Traumatic Brain Injury Classification with Machine Learning and Harmonization.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

An ICA-based framework for joint analysis of cognitive scores and MEG event-related fields.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Deep Learning Prediction and Visualization of Gender Related Brain Changes from Longitudinal Structural MRI Data in the ABCD Study.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Learning Active Multimodal Subspaces in the Brain.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Longitudinal Changes in Resting State FMRI Spectra in Children.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Probing the link between the APOE-ε4 allele and whole-brain gray matter using deep learning.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Discovery and Replication of Time-Resolved Functional Network Connectivity Differences in Adolescence and Adulthood in over 50K fMRI Datasets.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Data-driven spatio-temporal dynamic brain connectivity analysis using fALFF: Application to sensorimotor task data.
Proceedings of the 56th Annual Conference on Information Sciences and Systems, 2022

Multimodal Analysis Uncovers Links between Grey Matter Volume and both Low-and High-frequency Dynamic Connectivity States in Schizophrenia.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

Exploring Relationships between Functional Network Connectivity and Cognition with an Explainable Clustering Approach.
Proceedings of the 22nd IEEE International Conference on Bioinformatics and Bioengineering, 2022

Examining Reproducibility of EEG Schizophrenia Biomarkers Across Explainable Machine Learning Models.
Proceedings of the 22nd IEEE International Conference on Bioinformatics and Bioengineering, 2022

Examining Effects of Schizophrenia on EEG with Explainable Deep Learning Models.
Proceedings of the 22nd IEEE International Conference on Bioinformatics and Bioengineering, 2022

An Approach for Estimating Explanation Uncertainty in fMRI dFNC Classification.
Proceedings of the 22nd IEEE International Conference on Bioinformatics and Bioengineering, 2022

A deep generative multimodal imaging genomics framework for Alzheimer's disease prediction.
Proceedings of the 22nd IEEE International Conference on Bioinformatics and Bioengineering, 2022

Relationship of Hemodynamic Delay and Sex Differences Among Adolescents Using Resting-state fMRI Data.
Proceedings of the IEEE-EMBS International Conference on Biomedical and Health Informatics, 2022

Classification of Schizophrenia and Alzheimer's Disease using Resting-State Functional Network Connectivity.
Proceedings of the IEEE-EMBS International Conference on Biomedical and Health Informatics, 2022

2021
A Correlated Noise-Assisted Decentralized Differentially Private Estimation Protocol, and its Application to fMRI Source Separation.
IEEE Trans. Signal Process., 2021

Interpretable Multimodal Fusion Networks Reveal Mechanisms of Brain Cognition.
IEEE Trans. Medical Imaging, 2021

A Joint Analysis of Multi-Paradigm fMRI Data With Its Application to Cognitive Study.
IEEE Trans. Medical Imaging, 2021

Multi-Paradigm fMRI Fusion via Sparse Tensor Decomposition in Brain Functional Connectivity Study.
IEEE J. Biomed. Health Informatics, 2021

Multidataset Independent Subspace Analysis With Application to Multimodal Fusion.
IEEE Trans. Image Process., 2021

A Latent Gaussian Copula Model for Mixed Data Analysis in Brain Imaging Genetics.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021

Correlation Guided Graph Learning to Estimate Functional Connectivity Patterns From fMRI Data.
IEEE Trans. Biomed. Eng., 2021

Ensemble Manifold Regularized Multi-Modal Graph Convolutional Network for Cognitive Ability Prediction.
IEEE Trans. Biomed. Eng., 2021

Multiview Diffusion Map Improves Prediction of Fluid Intelligence With Two Paradigms of fMRI Analysis.
IEEE Trans. Biomed. Eng., 2021

Sparse deep dictionary learning identifies differences of time-varying functional connectivity in brain neuro-developmental study.
Neural Networks, 2021

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

Tracking spatial dynamics of functional connectivity during a task.
NeuroImage, 2021

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

Respiratory, cardiac, EEG, BOLD signals and functional connectivity over multiple microsleep episodes.
NeuroImage, 2021

Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?
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NeuroImage, 2021

Spontaneous cortical MEG activity undergoes unique age- and sex-related changes during the transition to adolescence.
NeuroImage, 2021

Frequency drift in MR spectroscopy at 3T.
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NeuroImage, 2021

Dynamic state with covarying brain activity-connectivity: On the pathophysiology of schizophrenia.
NeuroImage, 2021

Accessing dynamic functional connectivity using l0-regularized sparse-smooth inverse covariance estimation from fMRI.
Neurocomputing, 2021

A deep autoencoder with sparse and graph Laplacian regularization for characterizing dynamic functional connectivity during brain development.
Neurocomputing, 2021

Multi network InfoMax: A pre-training method involving graph convolutional networks.
CoRR, 2021

Brain dynamics via Cumulative Auto-Regressive Self-Attention.
CoRR, 2021

Algorithm-Agnostic Explainability for Unsupervised Clustering.
CoRR, 2021

Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data.
CoRR, 2021

Efficient Distributed Auto-Differentiation.
CoRR, 2021

Ensemble manifold based regularized multi-modal graph convolutional network for cognitive ability prediction.
CoRR, 2021

Abnormal Dynamic Functional Network Connectivity Estimated from Default Mode Network Predicts Symptom Severity in Major Depressive Disorder.
Brain Connect., 2021

A Classification-Based Approach to Estimate the Number of Resting Functional Magnetic Resonance Imaging Dynamic Functional Connectivity States.
Brain Connect., 2021

Relationship between Dynamic Blood-Oxygen-Level-Dependent Activity and Functional Network Connectivity: Characterization of Schizophrenia Subgroups.
Brain Connect., 2021

The Influence of Cerebral Small Vessel Disease on Static and Dynamic Functional Network Connectivity in Subjects Along Alzheimer's Disease Continuum.
Brain Connect., 2021

A Deep Learning Model for Data-Driven Discovery of Functional Connectivity.
Algorithms, 2021

An Attention-Based Hybrid Deep Learning Framework Integrating Temporal Coherence And Dynamics For Discriminating Schizophrenia.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Statelets: A Novel Multi-Dimensional State-Shape Representation Of Brain Functional Connectivity Dynamics.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

3-way Parallel Fusion of Spatial (sMRI/dMRI) and Spatio-temporal (fMRI) Data with Application to Schizophrenia.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

On Self-Supervised Multimodal Representation Learning: An Application To Alzheimer's Disease.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

A New Hypergraph Clustering Method For Exploring Transdiagnostic Biotypes In Mental Illnesses: Application To Schizophrenia And Psychotic Bipolar Disorder.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

A New Semi-Supervised Non-Negative Matrix Factorization Method For Brain Dynamic Functional Connectivity Analysis.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

A Multimodal Learning Framework to Study Varying Information Complexity in Structural and Functional Sub-Domains in Schizophrenia.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Fusion of Multiple Spatial Networks Derived from Complex-Valued fMRI Data via CNN Classification.
Proceedings of the International Joint Conference on Neural Networks, 2021

Marginal Spectrum Modulated Hilbert-Huang Transform: Application to Time Courses Extracted by Independent Vector Analysis of Resting-State fMRI Data.
Proceedings of the Neural Information Processing - 28th International Conference, 2021

Can recurrent models know more than we do?
Proceedings of the 9th IEEE International Conference on Healthcare Informatics, 2021

Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease.
Proceedings of the 9th IEEE International Conference on Healthcare Informatics, 2021

Sparse Representation of Complex-Valued fMRI Data Based on Hard Thresholding of Spatial Source Phase.
Proceedings of the IEEE International Conference on Acoustics, 2021

Tucker Decomposition for Extracting Shared and Individual Spatial Maps from Multi-Subject Resting-State fMRI Data.
Proceedings of the IEEE International Conference on Acoustics, 2021

BNCPL: Brain-Network-based Convolutional Prototype Learning for Discriminating Depressive Disorders.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Evidence for Transcranial Magnetic Stimulation Induced Functional Connectivity Oscillations in the Brain.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Dynamic patterns within the default mode network in schizophrenia subgroups.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Brain age gap difference between healthy and mild dementia subjects: Functional network connectivity analysis.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Multimodal Brain Age Prediction with Feature Selection and Comparison.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Shared sets of correlated polygenic risk scores and voxel-wise grey matter across multiple traits identified via bi-clustering.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Multi-modal deep learning of functional and structural neuroimaging and genomic data to predict mental illness.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

A Method for Integrative Analysis of Local and Global Brain Dynamics.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Multiframe Evolving Dynamic Functional Network Connectivity Motifs (Evodfncs) from Continuity-Preserving Planar Embedding.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Investigating ADHD subtypes in children using temporal dynamics of the electroencephalogram (EEG) microstates <sup>*</sup>.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Fusing multimodal neuroimaging data with a variational autoencoder.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Explainable Sleep Stage Classification with Multimodal Electrophysiology Time-series<sup>*</sup>.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

A Transdiagnostic Biotype Detection Method for Schizophrenia and Autism Spectrum Disorder Based on Graph Kernel.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

SMART (splitting-merging assisted reliable) Independent Component Analysis for Brain Functional Networks.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

A multimodal IVA fusion approach to identify linked neuroimaging markers.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Uncovering Active Structural Subspaces Associated with Changes in Indicators for Alzheimer's Disease.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Federation of Brain Age Estimation in Structural Neuroimaging Data.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Deep learning in resting-state fMRI<sup>*</sup>.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Environmental and genome-wide association study on children anxiety and depression.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

Variational voxelwise rs-fMRI representation learning: Evaluation of sex, age, and neuropsychiatric signatures.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

Confirmatory Factor Analysis on Mental Health Status using ABCD Cohort.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

A Novel Activation Maximization-based Approach for Insight into Electrophysiology Classifiers.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

Machine Learning Predicts Treatment Response in Bipolar & Major Depression Disorders.
Proceedings of the 21st IEEE International Conference on Bioinformatics and Bioengineering, 2021

A Novel Local Ablation Approach for Explaining Multimodal Classifiers.
Proceedings of the 21st IEEE International Conference on Bioinformatics and Bioengineering, 2021

A Gradient-based Approach for Explaining Multimodal Deep Learning Classifiers.
Proceedings of the 21st IEEE International Conference on Bioinformatics and Bioengineering, 2021

A Novel Local Explainability Approach for Spectral Insight into Raw EEG-based Deep Learning Classifiers.
Proceedings of the 21st IEEE International Conference on Bioinformatics and Bioengineering, 2021

Stability of functional network connectivity (FNC) values across multiple spatial normalization pipelines in spatially constrained independent component analysis.
Proceedings of the 21st IEEE International Conference on Bioinformatics and Bioengineering, 2021

Harmonization of Multi-site Dynamic Functional Connectivity Network Data.
Proceedings of the 21st IEEE International Conference on Bioinformatics and Bioengineering, 2021

2020
Estimating Dynamic Functional Brain Connectivity With a Sparse Hidden Markov Model.
IEEE Trans. Medical Imaging, 2020

Joint Bayesian-Incorporating Estimation of Multiple Gaussian Graphical Models to Study Brain Connectivity Development in Adolescence.
IEEE Trans. Medical Imaging, 2020

Multi-Hypergraph Learning-Based Brain Functional Connectivity Analysis in fMRI Data.
IEEE Trans. Medical Imaging, 2020

Shift-Invariant Canonical Polyadic Decomposition of Complex-Valued Multi-Subject fMRI Data With a Phase Sparsity Constraint.
IEEE Trans. Medical Imaging, 2020

Causality-Based Feature Fusion for Brain Neuro-Developmental Analysis.
IEEE Trans. Medical Imaging, 2020

Optimized Combination of Multiple Graphs With Application to the Integration of Brain Imaging and (epi)Genomics Data.
IEEE Trans. Medical Imaging, 2020

Canonical Correlation Analysis of Imaging Genetics Data Based on Statistical Independence and Structural Sparsity.
IEEE J. Biomed. Health Informatics, 2020

Guest Editorial: Information Fusion for Medical Data: Early, Late, and Deep Fusion Methods for Multimodal Data.
IEEE J. Biomed. Health Informatics, 2020

Integration of Imaging (epi)Genomics Data for the Study of Schizophrenia Using Group Sparse Joint Nonnegative Matrix Factorization.
IEEE ACM Trans. Comput. Biol. Bioinform., 2020

A Manifold Regularized Multi-Task Learning Model for IQ Prediction From Two fMRI Paradigms.
IEEE Trans. Biomed. Eng., 2020

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

Meta-Modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia.
IEEE Trans. Biomed. Eng., 2020

Biomarker Identification Through Integrating fMRI and Epigenetics.
IEEE Trans. Biomed. Eng., 2020

Prediction and classification of sleep quality based on phase synchronization related whole-brain dynamic connectivity using resting state fMRI.
NeuroImage, 2020

Nonlinear ICA of fMRI reveals primitive temporal structures linked to rest, task, and behavioral traits.
NeuroImage, 2020

Independent vector analysis for common subspace analysis: Application to multi-subject fMRI data yields meaningful subgroups of schizophrenia.
NeuroImage, 2020

Development and sex modulate visuospatial oscillatory dynamics in typically-developing children and adolescents.
NeuroImage, 2020

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

Connectivity dynamics from wakefulness to sleep.
NeuroImage, 2020

Disambiguating the role of blood flow and global signal with partial information decomposition.
NeuroImage, 2020

Adaptive Constrained Independent Vector Analysis: An Effective Solution for Analysis of Large-Scale Medical Imaging Data.
IEEE J. Sel. Top. Signal Process., 2020

COINSTAC: Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation.
J. Open Source Softw., 2020

Log-sum enhanced sparse deep neural network.
Neurocomputing, 2020

Taxonomy of multimodal self-supervised representation learning.
CoRR, 2020

On self-supervised multi-modal representation learning: An application to Alzheimer's disease.
CoRR, 2020

A Bayesian incorporated linear non-Gaussian acyclic model for multiple directed graph estimation to study brain emotion circuit development in adolescence.
CoRR, 2020

Causal inference of brain connectivity from fMRI with ψ-Learning Incorporated Linear non-Gaussian Acyclic Model (ψ-LiNGAM).
CoRR, 2020

Interpretable multimodal fusion networks reveal mechanisms of brain cognition.
CoRR, 2020

Application of deep canonically correlated sparse autoencoder for the classification of schizophrenia.
Comput. Methods Programs Biomed., 2020

Weaker Cerebellocortical Connectivity Within Sensorimotor and Executive Networks in Schizophrenia Compared to Healthy Controls: Relationships with Processing Speed.
Brain Connect., 2020

Dynamic Resting-State Connectivity Differences in Eyes Open Versus Eyes Closed Conditions.
Brain Connect., 2020

Deep Principal Correlated Auto-Encoders With Application to Imaging and Genomics Data Integration.
IEEE Access, 2020

Nicotine Addiction Decreases Dynamic Connectivity Frequency In Functional Magnetic Resonance Imaging.
Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, 2020

A Machine Learning Model for Exploring Aberrant Functional Network Connectivity Transition in Schizophrenia.
Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, 2020

Transient Spectral Peak Analysis Reveals Distinct Temporal Activation Profiles for Different Functional Brain Networks.
Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, 2020

Hybrid dictionary learning-ICA approaches built on novel instantaneous dynamic connectivity metric provide new multiscale insights into dynamic brain connectivity.
Proceedings of the Medical Imaging 2020: Image Processing, 2020

A GICA-TVGL framework to study sex differences in resting state fMRI dynamic connectivity.
Proceedings of the Medical Imaging 2020: Image Processing, 2020

Whole MILC: Generalizing Learned Dynamics Across Tasks, Datasets, and Populations.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

A data-driven approach for stratifying psychotic and mood disorders subjects using structural magnitude resonance imaging data.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

Multi-modal component subspace-similarity-based multi-kernel SVM for schizophrenia classification.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

A causal brain network estimation method leveraging Bayesian analysis and the PC algorithm.
Proceedings of the Medical Imaging 2020: Biomedical Applications in Molecular, 2020

A hypergraph learning method for brain functional connectivity network construction from fMRI data.
Proceedings of the Medical Imaging 2020: Biomedical Applications in Molecular, 2020

Graph Laplacian learning based Fourier Transform for brain network analysis with resting state fMRI.
Proceedings of the Medical Imaging 2020: Biomedical Applications in Molecular, 2020

Identification of dementia subtypes based on a diffusion MRI multi-model approach.
Proceedings of the Medical Imaging 2020: Biomedical Applications in Molecular, 2020

Reduced sine hyperbolic polynomial model for brain neuro-developmental analysis.
Proceedings of the Medical Imaging 2020: Biomedical Applications in Molecular, 2020

Integration of multi-task fMRI for cognitive study by structure-enforced collaborative regression.
Proceedings of the Medical Imaging 2020: Biomedical Applications in Molecular, 2020

Functional Multi-Connectivity: A Novel Approach To Assess Multi-Way Entanglement Between Networks and Voxels.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Tracing Network Evolution Using The Parafac2 Model.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Aberrant Functional Network Connectivity Transition Probability in Major Depressive Disorder.
Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

aNy-way Independent Component Analysis.
Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

Visualizing Functional Network Connectivity Difference between Healthy Control and Major Depressive Disorder Using an Explainable Machine-learning Method.
Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

Fully automated ordering and labeling of ICA components.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

Visualizing functional network connectivity difference between middle adult and older subjects using an explainable machine-learning method.
Proceedings of the 20th IEEE International Conference on Bioinformatics and Bioengineering, 2020

BPARC: A novel spatio-temporal (4D) data-driven brain parcellation scheme based on deep residual networks.
Proceedings of the 20th IEEE International Conference on Bioinformatics and Bioengineering, 2020

Individualized Prediction of Brain Network Interactions using Deep Siamese Networks.
Proceedings of the 20th IEEE International Conference on Bioinformatics and Bioengineering, 2020

Time-varying Graphs: A Method to Identify Abnormal Integration and Disconnection in Functional Brain Connectivity with Application to Schizophrenia.
Proceedings of the 20th IEEE International Conference on Bioinformatics and Bioengineering, 2020

Varying Information Complexity in Functional Domain Interactions in Schizophrenia.
Proceedings of the 20th IEEE International Conference on Bioinformatics and Bioengineering, 2020

A deep learning fusion model for brain disorder classification: Application to distinguishing schizophrenia and autism spectrum disorder.
Proceedings of the BCB '20: 11th ACM International Conference on Bioinformatics, 2020

2019
Extraction of Time-Varying Spatiotemporal Networks Using Parameter-Tuned Constrained IVA.
IEEE Trans. Medical Imaging, 2019

Aberrant Brain Connectivity in Schizophrenia Detected via a Fast Gaussian Graphical Model.
IEEE J. Biomed. Health Informatics, 2019

Alternating Diffusion Map Based Fusion of Multimodal Brain Connectivity Networks for IQ Prediction.
IEEE Trans. Biomed. Eng., 2019

Deep Collaborative Learning With Application to the Study of Multimodal Brain Development.
IEEE Trans. Biomed. Eng., 2019

Capturing Dynamic Connectivity From Resting State fMRI Using Time-Varying Graphical Lasso.
IEEE Trans. Biomed. Eng., 2019

Translational Potential of Neuroimaging Genomic Analyses to Diagnosis and Treatment in Mental Disorders.
Proc. IEEE, 2019

Scanning the Issue.
Proc. IEEE, 2019

Efficacy of different dynamic functional connectivity methods to capture cognitively relevant information.
NeuroImage, 2019

The developmental trajectory of sensorimotor cortical oscillations.
NeuroImage, 2019

A framework for linking resting-state chronnectome/genome features in schizophrenia: A pilot study.
NeuroImage, 2019

The inner fluctuations of the brain in presymptomatic Frontotemporal Dementia: The chronnectome fingerprint.
NeuroImage, 2019

Association between the oral microbiome and brain resting state connectivity in smokers.
NeuroImage, 2019

Sex-related differences in intrinsic brain dynamism and their neurocognitive correlates.
NeuroImage, 2019

Transient increased thalamic-sensory connectivity and decreased whole-brain dynamism in autism.
NeuroImage, 2019

Neural dynamics of verbal working memory processing in children and adolescents.
NeuroImage, 2019

Decentralized temporal independent component analysis: Leveraging fMRI data in collaborative settings.
NeuroImage, 2019

Robust kernel canonical correlation analysis to detect gene-gene co-associations: A case study in genetics.
J. Bioinform. Comput. Biol., 2019

Learnt dynamics generalizes across tasks, datasets, and populations.
CoRR, 2019

Improved Differentially Private Decentralized Source Separation for fMRI Data.
CoRR, 2019

Dynamic Functional Network Connectivity in Schizophrenia with Magnetoencephalography and Functional Magnetic Resonance Imaging: Do Different Timescales Tell a Different Story?
Brain Connect., 2019

Transient Patterns of Functional Dysconnectivity in Clinical High Risk and Early Illness Schizophrenia Individuals Compared with Healthy Controls.
Brain Connect., 2019

Brain Development Includes Linear and Multiple Nonlinear Trajectories: A Cross-Sectional Resting-State Functional Magnetic Resonance Imaging Study.
Brain Connect., 2019

Improved estimation of dynamic connectivity from resting-state fMRI data.
Proceedings of the Medical Imaging 2019: Image Processing, 2019

Phase fMRI reveals sparser function connectivity than magnitude fMRI.
Proceedings of the Medical Imaging 2019: Biomedical Applications in Molecular, 2019

Extraction of co-expressed discriminative features of Schizophrenia in imaging epigenetics framework.
Proceedings of the Medical Imaging 2019: Biomedical Applications in Molecular, 2019

Classification of Schizophrenia Patients and Healthy Controls Using ICA of Complex-Valued fMRI Data and Convolutional Neural Networks.
Proceedings of the Advances in Neural Networks - ISNN 2019, 2019

ADHD Classification Within and Cross Cohort Using an Ensembled Feature Selection Framework.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Classification As a Criterion to Select Model Order For Dynamic Functional Connectivity States in Rest-fMRI Data.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Multimodal Neuroimaging Patterns Associated with Social Responsiveness Impairment in Autism: A Replication Study.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Using Gradient as a New Metric for Dynamic Connectivity Estimation from Resting fMRI Data.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Sparse Infomax Based on Hoyer Projection and its Application to Simulated Structural MRI and SNP Data.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Selection of Efficient Clustering Index to Estimate the Number of Dynamic Brain States from Functional Network Connectivity.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

Diagnostic and Prognostic Classification of Brain Disorders Using Residual Learning on Structural MRI Data.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

Multimodal Data Fusion of Deep Learning and Dynamic Functional Connectivity Features to Predict Alzheimer's Disease Progression.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

C-ICT for Discovery of Multiple Associations in Multimodal Imaging Data: Application to Fusion of fMRI and DTI Data.
Proceedings of the 53rd Annual Conference on Information Sciences and Systems, 2019

Disjoint Subspaces for Common and Distinct Component Analysis: Application to Task FMRI Data.
Proceedings of the 53rd Annual Conference on Information Sciences and Systems, 2019

Prediction of Progression to Alzheimer's disease with Deep InfoMax.
Proceedings of the 2019 IEEE EMBS International Conference on Biomedical & Health Informatics, 2019

2018
Discriminating Bipolar Disorder from Major Depression using Whole-Brain Functional Connectivity: a Feature Selection Analysis with SVM-FoBa Algorithm.
J. Signal Process. Syst., 2018

Enforcing Co-Expression Within a Brain-Imaging Genomics Regression Framework.
IEEE Trans. Medical Imaging, 2018

Fused Estimation of Sparse Connectivity Patterns From Rest fMRI - Application to Comparison of Children and Adult Brains.
IEEE Trans. Medical Imaging, 2018

Multimodal Fusion With Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia.
IEEE Trans. Medical Imaging, 2018

FDR-Corrected Sparse Canonical Correlation Analysis With Applications to Imaging Genomics.
IEEE Trans. Medical Imaging, 2018

Estimation of Dynamic Sparse Connectivity Patterns From Resting State fMRI.
IEEE Trans. Medical Imaging, 2018

Fast and Accurate Detection of Complex Imaging Genetics Associations Based on Greedy Projected Distance Correlation.
IEEE Trans. Medical Imaging, 2018

Integrating Imaging Genomic Data in the Quest for Biomarkers of Schizophrenia Disease.
IEEE ACM Trans. Comput. Biol. Bioinform., 2018

Adaptive Sparse Multiple Canonical Correlation Analysis With Application to Imaging (Epi)Genomics Study of Schizophrenia.
IEEE Trans. Biomed. Eng., 2018

Application of Graph Theory to Assess Static and Dynamic Brain Connectivity: Approaches for Building Brain Graphs.
Proc. IEEE, 2018

The Dangers of Following Trends in Research: Sparsity and Other Examples of Hammers in Search of Nails.
Proc. IEEE, 2018

Whole-brain connectivity dynamics reflect both task-specific and individual-specific modulation: A multitask study.
NeuroImage, 2018

An approach to directly link ICA and seed-based functional connectivity: Application to schizophrenia.
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.
NeuroImage, 2018

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

Characterizing dynamic amplitude of low-frequency fluctuation and its relationship with dynamic functional connectivity: An application to schizophrenia.
NeuroImage, 2018

Dynamic functional connectivity impairments in early schizophrenia and clinical high-risk for psychosis.
NeuroImage, 2018

Corrigendum to "Lateralization of resting state networks and relationship to age and gender" [NeuroImage 104 (2015) 310-325].
NeuroImage, 2018

Sparsity and Independence: Balancing Two Objectives in Optimization for Source Separation with Application to fMRI Analysis.
J. Frankl. Inst., 2018

Decentralized Analysis of Brain Imaging Data: Voxel-Based Morphometry and Dynamic Functional Network Connectivity.
Frontiers Neuroinformatics, 2018

Identifying outliers using multiple kernel canonical correlation analysis with application to imaging genetics.
Comput. Stat. Data Anal., 2018

Improving Classification Rate of Schizophrenia Using a Multimodal Multi-Layer Perceptron Model with Structural and Functional MR.
CoRR, 2018

Whole-Brain Connectivity in a Large Study of Huntington's Disease Gene Mutation Carriers and Healthy Controls.
Brain Connect., 2018

In-between and cross-frequency dependence-based summarization of resting-state fMRI data.
Proceedings of the 2018 IEEE Southwest Symposium on Image Analysis and Interpretation, 2018

Graph Modularity and Randomness Measures : A Comparative Study.
Proceedings of the 2018 IEEE Southwest Symposium on Image Analysis and Interpretation, 2018

Dynamic Whole Brain Polarity Regimes Strongly Distinguish Controls from Schizophrenia Patients.
Proceedings of the 2018 International Workshop on Pattern Recognition in Neuroimaging, 2018

Multi-modal Brain Connectivity Study Using Deep Collaborative Learning.
Proceedings of the Graphs in Biomedical Image Analysis - and - Integrating Medical Imaging and Non-Imaging Modalities, 2018

Brain functional mapping and network connectivity of reconstructed susceptibility data.
Proceedings of the Medical Imaging 2018: Biomedical Applications in Molecular, 2018

High dimensional latent Gaussian copula model for mixed data in imaging genetics.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

Integration of network topological features and graph Fourier transform for fMRI data analysis.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

Detection of differentially developed functional connectivity patterns in adolescents based on tensor discriminative analysis.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

Evaluating Models of Dynamic Functional Connectivity Using Predictive Classification Accuracy.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

IVA-Based Spatio-Temporal Dynamic Connectivity Analysis in Large-Scale FMRI Data.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Consecutive Independence and Correlation Transform for Multimodal Fusion: Application to Eeg and Fmri Data.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Abnormal Dynamic Functional Network Connectivity and Graph Theoretical Analysis in Major Depressive Disorder.
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

Discriminating ADHD From Healthy Controls Using a Novel Feature Selection Method Based on Relative Importance and Ensemble Learning.
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

Exploring different impaired speed of genetic-related brain function and structures in schizophrenic progress using multimodal analysis.
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

Weak Mutual Information Between Functional Domains in Schizophrenia.
Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

2017
Quantifying the Interaction and Contribution of Multiple Datasets in Fusion: Application to the Detection of Schizophrenia.
IEEE Trans. Medical Imaging, 2017

A Realistic Framework for Investigating Decision Making in the Brain With High Spatiotemporal Resolution Using Simultaneous EEG/fMRI and Joint ICA.
IEEE J. Biomed. Health Informatics, 2017

Multimodal Neuroimaging in Schizophrenia: Description and Dissemination.
Neuroinformatics, 2017

Regional and source-based patterns of [<sup>11</sup>C]-(+)-PHNO binding potential reveal concurrent alterations in dopamine D<sub>2</sub> and D<sub>3</sub> receptor availability in cocaine-use disorder.
NeuroImage, 2017

The effect of preprocessing pipelines in subject classification and detection of abnormal resting state functional network connectivity using group ICA.
NeuroImage, 2017

Alterations of resting state functional network connectivity in the brain of nicotine and alcohol users.
NeuroImage, 2017

Machine learning of structural magnetic resonance imaging predicts psychopathic traits in adolescent offenders.
NeuroImage, 2017

Chronnectomic patterns and neural flexibility underlie executive function.
NeuroImage, 2017

Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data.
NeuroImage, 2017

The real-time fMRI neurofeedback based stratification of Default Network Regulation Neuroimaging data repository.
NeuroImage, 2017

Multimodal neural correlates of cognitive control in the Human Connectome Project.
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.
NeuroImage, 2017

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

Prediction of Individual Differences from Neuroimaging Data.
NeuroImage, 2017

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls.
NeuroImage, 2017

Replicability of time-varying connectivity patterns in large resting state fMRI samples.
NeuroImage, 2017

Investigation of True High Frequency Electrical Substrates of fMRI-Based Resting State Networks Using Parallel Independent Component Analysis of Simultaneous EEG/fMRI Data.
Frontiers Neuroinformatics, 2017

COINSTAC: Decentralizing the future of brain imaging analysis.
F1000Research, 2017

Almost instant brain atlas segmentation for large-scale studies.
CoRR, 2017

Time-Resolved Resting-State Functional Magnetic Resonance Imaging Analysis: Current Status, Challenges, and New Directions.
Brain Connect., 2017

Enforcing Co-expression in Multimodal Regression Framework.
Proceedings of the Biocomputing 2017: Proceedings of the Pacific Symposium, 2017

Discriminating schizophrenia from normal controls using resting state functional network connectivity: A deep neural network and layer-wise relevance propagation method.
Proceedings of the 27th IEEE International Workshop on Machine Learning for Signal Processing, 2017

Predicting individualized intelligence quotient scores using brainnetome-atlas based functional connectivity.
Proceedings of the 27th IEEE International Workshop on Machine Learning for Signal Processing, 2017

Discriminating bipolar disorder from major depression based on kernel SVM using functional independent components.
Proceedings of the 27th IEEE International Workshop on Machine Learning for Signal Processing, 2017

Comparison of Functional Network Connectivity and Granger Causality for Resting State fMRI Data.
Proceedings of the Advances in Neural Networks - ISNN 2017 - 14th International Symposium, 2017

Tensor-based fusion of EEG and FMRI to understand neurological changes in schizophrenia.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2017

Group information guided ICA shows more sensitivity to group differences than dual-regression.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Model order effects on independent vector analysis applied to complex-valued fMRI data.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Cooperative learning: Decentralized data neural network.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

End-to-end learning of brain tissue segmentation from imperfect labeling.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

See without looking: joint visualization of sensitive multi-site datasets.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Fused estimation of sparse connectivity patterns from rest fMRI.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Decentralized independent vector analysis.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Integration of multiple genomic imaging data for the study of schizophrenia using joint nonnegative matrix factorization.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Identifying FMRI dynamic connectivity states using affinity propagation clustering method: Application to schizophrenia.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Two models for fusion of medical imaging data: Comparison and connections.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Post-ICA phase de-noising for resting-state complex-valued FMRI data.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Flexible large-scale fMRI analysis: A survey.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

A deep-learning approach to translate between brain structure and functional connectivity.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Non-orthogonal constrained independent vector analysis: Application to data fusion.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

ACMTF for fusion of multi-modal neuroimaging data and identification of biomarkers.
Proceedings of the 25th European Signal Processing Conference, 2017

A graph theoretical approach for performance comparison of ICA for fMRI analysis.
Proceedings of the 51st Annual Conference on Information Sciences and Systems, 2017

Brain language: Uncovering functional connectivity codes.
Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

2016
A Method for Intertemporal Functional-Domain Connectivity Analysis: Application to Schizophrenia Reveals Distorted Directional Information Flow.
IEEE Trans. Biomed. Eng., 2016

Time-Varying Brain Connectivity in fMRI Data: Whole-brain data-driven approaches for capturing and characterizing dynamic states.
IEEE Signal Process. Mag., 2016

Cross-Frequency rs-fMRI Network Connectivity Patterns Manifest Differently for Schizophrenia Patients and Healthy Controls.
IEEE Signal Process. Lett., 2016

Neuroimaging measures of error-processing: Extracting reliable signals from event-related potentials and functional magnetic resonance imaging.
NeuroImage, 2016

Genes influence the amplitude and timing of brain hemodynamic responses.
NeuroImage, 2016

Classification of schizophrenia and bipolar patients using static and dynamic resting-state fMRI brain connectivity.
NeuroImage, 2016

Sample-poor estimation of order and common signal subspace with application to fusion of medical imaging data.
NeuroImage, 2016

COINS Data Exchange: An open platform for compiling, curating, and disseminating neuroimaging data.
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.
NeuroImage, 2016

The Function Biomedical Informatics Research Network Data Repository.
NeuroImage, 2016

The connectivity domain: Analyzing resting state fMRI data using feature-based data-driven and model-based methods.
NeuroImage, 2016

SchizConnect: Mediating neuroimaging databases on schizophrenia and related disorders for large-scale integration.
NeuroImage, 2016

Blind Source Separation for Unimodal and Multimodal Brain Networks: A Unifying Framework for Subspace Modeling.
IEEE J. Sel. Top. Signal Process., 2016

A Tool for Interactive Data Visualization: Application to Over 10, 000 Brain Imaging and Phantom MRI Data Sets.
Frontiers Neuroinformatics, 2016

Recurrent Neural Networks for Spatiotemporal Dynamics of Intrinsic Networks from fMRI Data.
CoRR, 2016

Variational Autoencoders for Feature Detection of Magnetic Resonance Imaging Data.
CoRR, 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.
Brain Connect., 2016

Joint sparse canonical correlation analysis for detecting differential imaging genetics modules.
Bioinform., 2016

Multimodal fusion of brain structural and functional imaging with a deep neural machine translation approach.
Proceedings of the 2016 IEEE Southwest Symposium on Image Analysis and Interpretation, 2016

Iterative Refinement of the Approximate Posterior for Directed Belief Networks.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Time-varying frequency modes of resting fMRI brain networks reveal significant gender differences.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

An adaptive fixed-point IVA algorithm applied to multi-subject complex-valued FMRI data.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Randomness in resting state functional connectivity matrices.
Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016

Supervised multimodal fusion and its application in searching joint neuromarkers of working memory deficits in schizophrenia.
Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016

Integration of SNPs-FMRI-methylation data with sparse multi-CCA for schizophrenia study.
Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016

Predicting schizophrenia by fusing networks from SNPs, DNA methylation and fMRI data.
Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016

The chronnectome: Evaluating replicability of dynamic connectivity patterns in 7500 resting fMRI datasets.
Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016

Privacy-preserving source separation for distributed data using independent component analysis.
Proceedings of the 2016 Annual Conference on Information Science and Systems, 2016

Learning schizophrenia imaging genetics data via Multiple Kernel Canonical Correlation Analysis.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016

Schizophrenia genes discovery by mining the minimum spanning trees from multi-dimensional imaging genomic data integration.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016

Diagnosing schizophrenia by integrating genomic and imaging data through network fusion.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016

Robust Kernel Canonical Correlation Analysis to Detect Gene-Gene Interaction for Imaging Genetics Data.
Proceedings of the 7th ACM International Conference on Bioinformatics, 2016

Influence Function of Multiple Kernel Canonical Analysis to Identify Outliers in Imaging Genetics Data.
Proceedings of the 7th ACM International Conference on Bioinformatics, 2016

2015
General Nonunitary Constrained ICA and its Application to Complex-Valued fMRI Data.
IEEE Trans. Biomed. Eng., 2015

Independent Vector Analysis for Gradient Artifact Removal in Concurrent EEG-fMRI Data.
IEEE Trans. Biomed. Eng., 2015

Discriminating Bipolar Disorder From Major Depression Based on SVM-FoBa: Efficient Feature Selection With Multimodal Brain Imaging Data.
IEEE Trans. Auton. Ment. Dev., 2015

Multimodal Data Fusion Using Source Separation: Two Effective Models Based on ICA and IVA and Their Properties.
Proc. IEEE, 2015

Multimodal Data Fusion Using Source Separation: Application to Medical Imaging.
Proc. IEEE, 2015

Assessing dynamic brain graphs of time-varying connectivity in fMRI data: Application to healthy controls and patients with schizophrenia.
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.
NeuroImage, 2015

Dynamic coherence analysis of resting fMRI data to jointly capture state-based phase, frequency, and time-domain information.
NeuroImage, 2015

A group ICA based framework for evaluating resting fMRI markers when disease categories are unclear: application to schizophrenia, bipolar, and schizoaffective disorders.
NeuroImage, 2015

Comparison of PCA approaches for very large group ICA.
NeuroImage, 2015

Lateralization of resting state networks and relationship to age and gender.
NeuroImage, 2015

Iterative Refinement of Approximate Posterior for Training Directed Belief Networks.
CoRR, 2015

Shapelet Ensemble for Multi-dimensional Time Series.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Rate-Agnostic (Causal) Structure Learning.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Synthetic structural magnetic resonance image generator improves deep learning prediction of schizophrenia.
Proceedings of the 25th IEEE International Workshop on Machine Learning for Signal Processing, 2015

Deep independence network analysis of structural brain imaging: A simulation study.
Proceedings of the 25th IEEE International Workshop on Machine Learning for Signal Processing, 2015

Large scale collaboration with autonomy: Decentralized data ICA.
Proceedings of the 25th IEEE International Workshop on Machine Learning for Signal Processing, 2015

Resting fMRI measures are associated with cognitive deficits in schizophrenia assessed by the MATRICS consensus cognitive battery.
Proceedings of the Medical Imaging 2015: Biomedical Applications in Molecular, 2015

Classification of schizophrenia and bipolar patients using static and time-varying resting-state FMRI brain connectivity.
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015

Detection of genetic factors associated with multiple correlated imaging phenotypes by a sparse regression model.
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015

Identifying brain dynamic network states via GIG-ICA: Application to schizophrenia, bipolar and schizoaffective disorders.
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015

Dynamic default mode network connectivity diminished in patients with schizophrenia.
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015

Generation of synthetic structural magnetic resonance images for deep learning pre-training.
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015

Sensory load hierarchy-based classification of schizophrenia patients.
Proceedings of the 2015 IEEE International Conference on Image Processing, 2015

Multivariate Fusion of EEG and Functional MRI Data Using ICA: Algorithm Choice and Performance Analysis.
Proceedings of the Latent Variable Analysis and Signal Separation, 2015

The impact of data preprocessing in traumatic brain injury detection using functional magnetic resonance imaging.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015

Large scale fusion of brain imaging modalities and features using Markov-style dynamics in a feature meta-space.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015

Multimodal based classification of schizophrenia patients.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015

Terminology Development Towards Harmonizing Multiple Clinical Neuroimaging Research Repositories.
Proceedings of the Data Integration in the Life Sciences - 11th International Conference, 2015

SchizConnect: Virtual Data Integration in Neuroimaging.
Proceedings of the Data Integration in the Life Sciences - 11th International Conference, 2015

Parallel group ICA for multimodal biomedical data analyses.
Proceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine, 2015

2014
A three-way parallel ICA approach to analyze links among genetics, brain structure and brain function.
NeuroImage, 2014

Function-structure associations of the brain: Evidence from multimodal connectivity and covariance studies.
NeuroImage, 2014

A statistically motivated framework for simulation of stochastic data fusion models applied to multimodal neuroimaging.
NeuroImage, 2014

High-order interactions observed in multi-task intrinsic networks are dominant indicators of aberrant brain function in schizophrenia.
NeuroImage, 2014

Dynamic changes of spatial functional network connectivity in healthy individuals and schizophrenia patients using independent vector analysis.
NeuroImage, 2014

Functional and effective connectivity of stopping.
NeuroImage, 2014

Restricted Boltzmann machines for neuroimaging: An application in identifying intrinsic networks.
NeuroImage, 2014

Bipolar and borderline patients display differential patterns of functional connectivity among resting state networks.
NeuroImage, 2014

Functional connectivity in the developing brain: A longitudinal study from 4 to 9 months of age.
NeuroImage, 2014

Thalamus and posterior temporal lobe show greater inter-network connectivity at rest and across sensory paradigms in schizophrenia.
NeuroImage, 2014

A multiple kernel learning approach to perform classification of groups from complex-valued fMRI data analysis: Application to schizophrenia.
NeuroImage, 2014

Sparse representation based biomarker selection for schizophrenia with integrated analysis of fMRI and SNPs.
NeuroImage, 2014

Neuroimage: Special issue on multimodal data fusion.
NeuroImage, 2014

Impact of autocorrelation on functional connectivity.
NeuroImage, 2014

Correspondence between fMRI and SNP data by group sparse canonical correlation analysis.
Medical Image Anal., 2014

Harnessing modern web application technology to create intuitive and efficient data visualization and sharing tools.
Frontiers Neuroinformatics, 2014

Sharing privacy-sensitive access to neuroimaging and genetics data: a review and preliminary validation.
Frontiers Neuroinformatics, 2014

A review of multivariate analyses in imaging genetics.
Frontiers Neuroinformatics, 2014

Automated collection of imaging and phenotypic data to centralized and distributed data repositories.
Frontiers Neuroinformatics, 2014

Deep learning for neuroimaging: a validation study.
Proceedings of the 2nd International Conference on Learning Representations, 2014

Time of Acquisition and Network Stability in Pediatric Resting-State Functional Magnetic Resonance Imaging.
Brain Connect., 2014

Save the Global: Global Signal Connectivity as a Tool for Studying Clinical Populations with Functional Magnetic Resonance Imaging.
Brain Connect., 2014

Higher dimensional fMRI connectivity dynamics show reduced dynamism in schizophrenia patients.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2014

A study of spatial variation in fMRI brain networks via independent vector analysis: Application to schizophrenia.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2014

The tenth annual MLSP competition: Schizophrenia classification challenge.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

Semi-supervised learning of brain functional networks.
Proceedings of the IEEE 11th International Symposium on Biomedical Imaging, 2014

Multidataset independent subspace analysis extends independent vector analysis.
Proceedings of the 2014 IEEE International Conference on Image Processing, 2014

Performance of complex-valued ICA algorithms for fMRI analysis: Importance of taking full diversity into account.
Proceedings of the 2014 IEEE International Conference on Image Processing, 2014

A novel approach for assessing reliability of ICA for FMRI analysis.
Proceedings of the IEEE International Conference on Acoustics, 2014

Gradient artifact removal in concurrently acquired EEG data using independent vector analysis.
Proceedings of the IEEE International Conference on Acoustics, 2014

A quasi-local method for instantaneous frequency estimation with application to structural magnetic resonance images.
Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014

Three-way parallel independent component analysis for imaging genetics using multi-objective optimization.
Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014

Combination of FMRI-SMRI-EEG data improves discrimination of schizophrenia patients by ensemble feature selection.
Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014

Higher dimensional analysis shows reduced dynamism of time-varying network connectivity in schizophrenia patients.
Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014

Exploring difference and overlap between schizophrenia, schizoaffective and bipolar disorders using resting-state brain functional networks.
Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014

Brain functional networks extraction based on fMRI artifact removal: Single subject and group approaches.
Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014

Parallel ICA with multiple references: A semi-blind multivariate approach.
Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014

Identification of patterns of gray matter abnormalities in schizophrenia using source-based morphometry and bagging.
Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014

Detecting volumetric changes in fMRI connectivity networks in schizophrenia patients.
Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014

Accurate classification of schizophrenia patients based on novel resting-state fMRI features.
Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014

Data-driven fusion of EEG, functional and structural MRI: A comparison of two models.
Proceedings of the 48th Annual Conference on Information Sciences and Systems, 2014

2013
Guest Editorial for Special Section on Multimodal Biomedical Imaging: Algorithms and Applications.
IEEE Trans. Multim., 2013

The MCIC Collection: A Shared Repository of Multi-Modal, Multi-Site Brain Image Data from a Clinical Investigation of Schizophrenia.
Neuroinformatics, 2013

Task-related concurrent but opposite modulations of overlapping functional networks as revealed by spatial ICA.
NeuroImage, 2013

Three-way (N-way) fusion of brain imaging data based on mCCA + jICA and its application to discriminating schizophrenia.
NeuroImage, 2013

Using joint ICA to link function and structure using MEG and DTI in schizophrenia.
NeuroImage, 2013

Mind over chatter: Plastic up-regulation of the fMRI salience network directly after EEG neurofeedback.
NeuroImage, 2013

Dynamic functional connectivity: Promise, issues, and interpretations.
NeuroImage, 2013

Guided exploration of genomic risk for gray matter abnormalities in schizophrenia using parallel independent component analysis with reference.
NeuroImage, 2013

The spatiospectral characterization of brain networks: Fusing concurrent EEG spectra and fMRI maps.
NeuroImage, 2013

Block Coordinate Descent for Sparse NMF
Proceedings of the 1st International Conference on Learning Representations, 2013

Impact of Analysis Methods on the Reproducibility and Reliability of Resting-State Networks.
Brain Connect., 2013

Group sparse canonical correlation analysis for genomic data integration.
BMC Bioinform., 2013

Identifying genetic connections with brain functions in schizophrenia using group sparse canonical correlation analysis.
Proceedings of the 10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2013

Sparse representation based biomarker selection for schizophrenia with integrated analysis of fMRI and SNP data.
Proceedings of the 10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2013

Capturing group variability using IVA: A simulation study and graph-theoretical analysis.
Proceedings of the IEEE International Conference on Acoustics, 2013

MIGRAINE: MRI Graph Reliability Analysis and Inference for Connectomics.
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

Characterization of connectivity dynamics in intrinsic brain networks.
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

Multi-subject fMRI data analysis: Shift-invariant tensor factorization vs. group independent component analysis.
Proceedings of the 2013 IEEE China Summit and International Conference on Signal and Information Processing, 2013

Network-based investigation of genetic modules associated with functional brain networks in schizophrenia.
Proceedings of the 2013 IEEE International Conference on Bioinformatics and Biomedicine, 2013

2012
Order Selection of the Linear Mixing Model for Complex-Valued FMRI Data.
J. Signal Process. Syst., 2012

Group Study of Simulated Driving fMRI Data by Multiset Canonical Correlation Analysis.
J. Signal Process. Syst., 2012

De-noising, phase ambiguity correction and visualization techniques for complex-valued ICA of group fMRI data.
Pattern Recognit., 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].
NeuroImage, 2012

A large scale multivariate parallel ICA method reveals novel imaging-genetic relationships for Alzheimer's disease in the ADNI cohort.
NeuroImage, 2012

Modulations of functional connectivity in the healthy and schizophrenia groups during task and rest.
NeuroImage, 2012

SimTB, a simulation toolbox for fMRI data under a model of spatiotemporal separability.
NeuroImage, 2012

Joint ICA of ERP and fMRI during error-monitoring.
NeuroImage, 2012

TDCS guided using fMRI significantly accelerates learning to identify concealed objects.
NeuroImage, 2012

Multifaceted genomic risk for brain function in schizophrenia.
NeuroImage, 2012

A selective review of simulated driving studies: Combining naturalistic and hybrid paradigms, analysis approaches, and future directions.
NeuroImage, 2012

Capturing inter-subject variability with group independent component analysis of fMRI data: A simulation study.
NeuroImage, 2012

Correspondence between structure and function in the human brain at rest.
Frontiers Neuroinformatics, 2012

Constrained Source-Based Morphometry Identifies Structural Networks Associated with Default Mode Network.
Brain Connect., 2012

Volumetric BOLD fMRI simulation: from neurovascular coupling to multivoxel imaging.
BMC Medical Imaging, 2012

Complex-valued analysis and visualization of fMRI data for event-related and block-design paradigms.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

The eighth annual MLSP competition: Overview.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

Three-way FMRI-DTI-methylation data fusion based on mCCA+jICA and its application to schizophrenia.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012

ICA order selection based on consistency: Application to genotype data.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012

Bio marker identification for diagnosis of schizophrenia with integrated analysis of fMRI and SNPs.
Proceedings of the 2012 IEEE International Conference on Bioinformatics and Biomedicine, 2012

2011
Quality Map Thresholding for De-noising of Complex-Valued fMRI Data and Its Application to ICA of fMRI.
J. Signal Process. Syst., 2011

Correlated Noise: How it Breaks NMF, and What to Do About it.
J. Signal Process. Syst., 2011

Integrated Analysis of Gene Expression and Copy Number Data on Gene Shaving Using Independent Component Analysis.
IEEE ACM Trans. Comput. Biol. Bioinform., 2011

Automatic Identification of Functional Clusters in fMRI Data Using Spatial Dependence.
IEEE Trans. Biomed. Eng., 2011

Application of Independent Component Analysis With Adaptive Density Model to Complex-Valued fMRI Data.
IEEE Trans. Biomed. Eng., 2011

A Computational Multiresolution BOLD fMRI Model.
IEEE Trans. Biomed. Eng., 2011

Neuropsychological Testing and Structural Magnetic Resonance Imaging as Diagnostic Biomarkers Early in the Course of Schizophrenia and Related Psychoses.
Neuroinformatics, 2011

Discriminating schizophrenia and bipolar disorder by fusing fMRI and DTI in a multimodal CCA+ joint ICA model.
NeuroImage, 2011

Wavelet-based fMRI analysis: 3-D denoising, signal separation, and validation metrics.
NeuroImage, 2011

Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering.
NeuroImage, 2011

Characterization of groups using composite kernels and multi-source fMRI analysis data: Application to schizophrenia.
NeuroImage, 2011

Directional Statistics on Permutations.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

The Clinical Assessment and Remote Administration Tablet.
Frontiers Neuroinformatics, 2011

COINS: An Innovative Informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets.
Frontiers Neuroinformatics, 2011

EEGIFT: Group Independent Component Analysis for Event-Related EEG Data.
Comput. Intell. Neurosci., 2011

Effective connectivity analysis of fMRI and MEG data collected under identical paradigms.
Comput. Biol. Medicine, 2011

On Network Derivation, Classification, and Visualization: A Response to Habeck and Moeller.
Brain Connect., 2011

Source-Based Morphometry Analysis of Group Differences in Fractional Anisotropy in Schizophrenia.
Brain Connect., 2011

Semi-blind kurtosis maximization algorithm applied to complex-valued fMRI data.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

IVA for multi-subject FMRI analysis: A comparative study using a new simulation toolbox.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

A new metric to measure shape differences in fMRI activity.
Proceedings of the Medical Imaging 2011: Image Processing, 2011

Improved 3D wavelet-based de-noising of fMRI data.
Proceedings of the Medical Imaging 2011: Image Processing, 2011

Hierarchical and graphical analysis of fMRI network connectivity in healthy and schizophrenic groups.
Proceedings of the 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2011

Order detection for fMRI analysis: Joint estimation of downsampling depth and order by information theoretic criteria.
Proceedings of the 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2011

Wavelet-based denoising and independent component analysis for improving multi-group inference in fMRI data.
Proceedings of the 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2011

ICA of fMRI data: Performance of three ICA algorithms and the importance of taking correlation information into account.
Proceedings of the 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2011

Sparseness and a reduction from Totally Nonnegative Least Squares to SVM.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

A quantitative analysis of noncircularity for complex-valued fMRI based on semi-blind ICA.
Proceedings of the 3rd International Conference on Awareness Science and Technology, 2011

Deconvolution of neuronal signal from hemodynamic response.
Proceedings of the IEEE International Conference on Acoustics, 2011

Parallel independent component analysis using an optimized neurovascular coupling for concurrent EEG-fMRI sources.
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011

Estimation of neuronal responses from fMRI data.
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011

A pipeline for copy number variation detection based on principal component analysis.
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011

Functional network connectivity during rest and task: Comparison of healthy controls and schizophrenic patients.
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011

Classification of Schizophrenia Patients with Combined Analysis of SNP and fMRI Data Based on Sparse Representation.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2011

2010
Guest Editorial: Special Issue on Machine Learning for Signal Processing.
J. Signal Process. Syst., 2010

On entropy rate for the complex domain and its application to i.i.d. sampling.
IEEE Trans. Signal Process., 2010

Automatic Bayesian Classification of Healthy Controls, Bipolar Disorder, and Schizophrenia Using Intrinsic Connectivity Maps From fMRI Data.
IEEE Trans. Biomed. Eng., 2010

Canonical Correlation Analysis for Data Fusion and Group Inferences.
IEEE Signal Process. Mag., 2010

Identification of Imaging Biomarkers in Schizophrenia: A Coefficient-constrained Independent Component Analysis of the Mind Multi-site Schizophrenia Study.
Neuroinformatics, 2010

Reactivity of hemodynamic responses and functional connectivity to different states of alpha synchrony: A concurrent EEG-fMRI study.
NeuroImage, 2010

A CCA + ICA based model for multi-task brain imaging data fusion and its application to schizophrenia.
NeuroImage, 2010

Does function follow form?: Methods to fuse structural and functional brain images show decreased linkage in schizophrenia.
NeuroImage, 2010

A pilot multivariate parallel ICA study to investigate differential linkage between neural networks and genetic profiles in schizophrenia.
NeuroImage, 2010

Dynamic Granger causality based on Kalman filter for evaluation of functional network connectivity in fMRI data.
NeuroImage, 2010

Anomalous neural circuit function in schizophrenia during a virtual Morris water task.
NeuroImage, 2010

The COMT Val108/158Met polymorphism and medial temporal lobe volumetry in patients with schizophrenia and healthy adults.
NeuroImage, 2010

Multi-set canonical correlation analysis for the fusion of concurrent single trial ERP and functional MRI.
NeuroImage, 2010

Abnormal functional connectivity of default mode sub-networks in autism spectrum disorder patients.
NeuroImage, 2010

Changes in fMRI magnitude data and phase data observed in block-design and event-related tasks.
NeuroImage, 2010

MEG and fMRI fusion for nonlinear estimation of neural and BOLD signal changes.
Frontiers Neuroinformatics, 2010

Permutations as Angular Data: Efficient Inference in Factorial Spaces.
Proceedings of the ICDM 2010, 2010

Phase correction and denoising for ICA of complex FMRI data.
Proceedings of the IEEE International Conference on Acoustics, 2010

Independent subspace analysis with prior information for fMRI data.
Proceedings of the IEEE International Conference on Acoustics, 2010

Flexible complex ICA of fMRI data.
Proceedings of the IEEE International Conference on Acoustics, 2010

Fusion of concurrent single trial EEG data and fMRI data using multi-set canonical correlation analysis.
Proceedings of the IEEE International Conference on Acoustics, 2010

Correction of copy number variation data using principal component analysis.
Proceedings of the 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops, 2010

2009
Joint blind source separation by multiset canonical correlation analysis.
IEEE Trans. Signal Process., 2009

Feature-Based Fusion of Medical Imaging Data.
IEEE Trans. Inf. Technol. Biomed., 2009

Joint source based morphometry identifies linked gray and white matter group differences.
NeuroImage, 2009

An ICA-based method for the identification of optimal FMRI features and components using combined group-discriminative techniques.
NeuroImage, 2009

Age-related cognitive gains are mediated by the effects of white matter development on brain network integration.
NeuroImage, 2009

Genetic determinants of target and novelty-related event-related potentials in the auditory oddball response.
NeuroImage, 2009

Biophysical modeling of phase changes in BOLD fMRI.
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.
NeuroImage, 2009

A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data.
NeuroImage, 2009

Mining the mind research network: a novel framework for exploring large scale, heterogeneous translational neuroscience research data sources.
Frontiers Neuroinformatics, 2009

Multiplicative updates For Non-Negative Kernel SVM
CoRR, 2009

Efficient Multiplicative Updates for Support Vector Machines.
Proceedings of the SIAM International Conference on Data Mining, 2009

An ICA Framework for Integrating fMRI, ERP and Genetic Data.
Proceedings of the 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA, June 28, 2009

Fusion of fMRI, sMRI, and EEG data using canonical correlation analysis.
Proceedings of the IEEE International Conference on Acoustics, 2009

2008
A Parallel Independent Component Analysis Approach to Investigate Genomic Influence on Brain Function.
IEEE Signal Process. Lett., 2008

Measuring brain connectivity: Diffusion tensor imaging validates resting state temporal correlations.
NeuroImage, 2008

A method for multi-group inter-participant correlation: Abnormal synchrony in patients with schizophrenia during auditory target detection.
NeuroImage, 2008

Hybrid ICA-Bayesian network approach reveals distinct effective connectivity differences in schizophrenia.
NeuroImage, 2008

A method for functional network connectivity among spatially independent resting-state components in schizophrenia.
NeuroImage, 2008

A projection pursuit algorithm to classify individuals using fMRI data: Application to schizophrenia.
NeuroImage, 2008

Application of principal component analysis to distinguish patients with schizophrenia from healthy controls based on fractional anisotropy measurements.
NeuroImage, 2008

Multimodal and Multi-Tissue Measures of Connectivity Revealed by Joint Independent Component Analysis.
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.
IEEE J. Sel. Top. Signal Process., 2008

Introduction to the Issue on fMRI Analysis for Human Brain Mapping.
IEEE J. Sel. Top. Signal Process., 2008

Group learning using contrast NMF : Application to functional and structural MRI of schizophrenia.
Proceedings of the International Symposium on Circuits and Systems (ISCAS 2008), 2008

Examining associations between FMRI and EEG data using canonical correlation analysis.
Proceedings of the 2008 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2008

Source based morphometry using structural MRI phase images to identify sources of gray matter and white matter relative differences in schizophrenia versus controls.
Proceedings of the IEEE International Conference on Acoustics, 2008

On ICA of complex-valued fMRI: Advantages and order selection.
Proceedings of the IEEE International Conference on Acoustics, 2008

A constrained coefficient ica algorithm for group difference enhancement.
Proceedings of the IEEE International Conference on Acoustics, 2008

Extracting principle components for discriminant analysis of FMRI images.
Proceedings of the IEEE International Conference on Acoustics, 2008

CCA for joint blind source separation of multiple datasets with application to group FMRI analysis.
Proceedings of the IEEE International Conference on Acoustics, 2008

Exploration of the optimal group-discriminating features using CC-ICA.
Proceedings of the 42nd Asilomar Conference on Signals, Systems and Computers, 2008

Optimal sampling geometries for TV-norm reconstruction of fMRI data.
Proceedings of the 42nd Asilomar Conference on Signals, Systems and Computers, 2008

Session TP2: Analysis methods for functional and structural brain imaging.
Proceedings of the 42nd Asilomar Conference on Signals, Systems and Computers, 2008

2007
Complex ICA of Brain Imaging Data [Life Sciences].
IEEE Signal Process. Mag., 2007

A fast algorithm for one-unit ICA-R.
Inf. Sci., 2007

A Feature-Selective Independent Component Analysis Method for Functional MRI.
Int. J. Biomed. Imaging, 2007

Parallel Independent Component Analysis for Multimodal Analysis: Application to FMRI and EEG Data.
Proceedings of the 2007 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2007

A Maximal-Correlation Approach Using Ica for Testing Functional Network Connectivity Applied to Schizophrenia.
Proceedings of the 2007 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2007

2006
Complex Infomax: Convergence and Approximation of Infomax with Complex Nonlinearities.
J. VLSI Signal Process., 2006

Neuronal chronometry of target detection: Fusion of hemodynamic and event-related potential data.
NeuroImage, 2006

Neuroanatomic Organization of Sound Memory in Humans.
J. Cogn. Neurosci., 2006

Sample dependence correction for order selection in fMRI analysis.
Proceedings of the 2006 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2006

Fusion of Multisubject Hemodynamic and Event-Related Potential Data Using Independent Component Analysis.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Functional Classification of Schizophrenia Using Feed Forward Neural Networks.
Proceedings of the 28th International Conference of the IEEE Engineering in Medicine and Biology Society, 2006

A feature-based approach to combine functional MRI, structural MRI and EEG brain imaging data.
Proceedings of the 28th International Conference of the IEEE Engineering in Medicine and Biology Society, 2006

Functional Magnetic Resonance Imaging (fMRI).
Proceedings of the Neuroergonomics - the brain at work., 2006

2005
Regularized spectral matching for blind source separation. Application to fMRI imaging.
IEEE Trans. Signal Process., 2005

Hemispheric differences in hemodynamics elicited by auditory oddball stimuli.
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.
NeuroImage, 2005

Semi-blind ICA of fMRI: A method for utilizing hypothesis-derived time courses in a spatial ICA analysis.
NeuroImage, 2005

Bayesian blind source separation for brain imaging.
Proceedings of the 2005 International Conference on Image Processing, 2005

Feature-selective ICA and its convergence properties.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

Comparison of blind source separation algorithms for FMRI using a new Matlab toolbox: GIFT.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

2004
Independent Component Analysis Applied to fMRI Data: A Generative Model for Validating Results.
J. VLSI Signal Process., 2004

fMRI analysis with the general linear model: removal of latency-induced amplitude bias by incorporation of hemodynamic derivative terms.
NeuroImage, 2004

Independent Component Analysis of Complex-Valued Functional Magnetic Resonance Imaging Data by Complex Nonlinearities.
Proceedings of the 2004 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2004

Independent component analysis by complex nonlinearities.
Proceedings of the 2004 IEEE International Conference on Acoustics, 2004

2003
Latency (in)sensitive ICA: Group independent component analysis of fMRI data in the temporal frequency domain.
NeuroImage, 2003

Complex ICA for fMRI analysis: performance of several approaches.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

2002
On complex infomax applied to functional MRI data.
Proceedings of the IEEE International Conference on Acoustics, 2002

2001
fMRI Activation in a Visual-Perception Task: Network of Areas Detected Using the General Linear Model and Independent Components Analysis.
NeuroImage, 2001

1999
Adaptive Filtering of Visual Evoked Responses in FMRI: Variability of Response.
Proceedings of the Signal and Image Processing (SIP), 1999


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