J. Sui

Vince D. Calhoun, Dongdong Lin, Lin Tian, 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Brain function, structure and genomic data are linked but show different sensitivity to duration of illness and disease stage in schizophrenia

V. Calhoun, J. Turner, Fuquan Zhang, 2019, NeuroImage: Clinical.

Cross-Tissue Exploration of Genetic and Epigenetic Effects on Brain Gray Matter in Schizophrenia

V. Calhoun, J. Bustillo, Jingyu Liu, 2017, Schizophrenia bulletin.

Network modules linking expression and methylation in prefrontal cortex of schizophrenia

V. Calhoun, Jingyu Liu, N. Perrone-Bizzozero, 2020, Epigenetics.

Shared Genetic Risk of Schizophrenia and Gray Matter Reduction in 6p22.1

Dongdong Lin, Jiayu Chen, Yuhui Du, 2017, Schizophrenia bulletin.

Network modules linking expression and methylation in prefrontal cortex of schizophrenia

Vince D. Calhoun, Dongdong Lin, Jiayu Chen, 2018, bioRxiv.

A Schizophrenia-Related Genetic-Brain-Cognition Pathway Revealed in a Large Chinese Population

Vince D. Calhoun, Tianzi Jiang, Dongdong Lin, 2018, EBioMedicine.

Variability in Resting State Network and Functional Network Connectivity Associated With Schizophrenia Genetic Risk: A Pilot Study

Vince D. Calhoun, Dongdong Lin, Jiayu Chen, 2018, Front. Neurosci..

Multimodal neural correlates of cognitive control in the Human Connectome Project

Vince D. Calhoun, Jing Sui, Sridhar Kandala, 2017 .

CREB‐BDNF pathway influences alcohol cue‐elicited activation in drinkers

Jiayu Chen, Jing Sui, Jingyu Liu, 2015, Human brain mapping.

Preliminary prediction of individual response to electroconvulsive therapy using whole-brain functional magnetic resonance imaging data

V. Calhoun, K. Narr, J. Sui, 2019, NeuroImage: Clinical.

Neuroimaging-based Individualized Prediction of Cognition and Behavior for Mental Disorders and Health: Methods and Promises

V. Calhoun, J. Bustillo, J. Sui, 2020, Biological Psychiatry.

The effect of body-mind relaxation meditation induction on major depressive disorder: A resting-state fMRI study.

T. Jiang, J. Sui, L. Fan, 2015, Journal of affective disorders.

White matter microstructural differences across major depressive disorder, bipolar disorder and schizophrenia: A tract-based spatial statistics study.

T. Jiang, J. Sui, Yue Cui, 2019, Journal of affective disorders.

Inter and intra-hemispheric structural imaging markers predict depression relapse after electroconvulsive therapy: a multisite study

Shantanu H. Joshi, R. Woods, A. Leaver, 2017, Translational Psychiatry.

Multimodal data revealed different neurobiological correlates of intelligence between males and females

V. Calhoun, T. Jiang, Yuhui Du, 2019, Brain Imaging and Behavior.

Mapping Cortical Brain Asymmetry in 17,141 Healthy Individuals Worldwide via the ENIGMA Consortium

John J. Foxe, Colm G. Connolly, Erick Jorge Canales-Rodríguez, 2017 .

Machine Learning Predicts Treatment Response in Bipolar & Major Depressive Disorders

Bradley T. Baker, Mustafa S. Salman, E. Osuch, 2022, bioRxiv.

NR4A1 Methylation Associated Multimodal Neuroimaging Patterns Impaired in Temporal Lobe Epilepsy

V. Calhoun, J. Sui, Rongtao Jiang, 2020, Frontiers in Neuroscience.

Interpreting Brain Biomarkers: Challenges and solutions in interpreting machine learning-based predictive neuroimaging

J. Sui, Choong-Wan Woo, Rongtao Jiang, 2022, IEEE Signal Processing Magazine.

Task-induced brain connectivity promotes the detection of individual differences in brain-behavior relationships

Jessica A. Turner, Vince D. Calhoun, Judith M. Ford, 2019, NeuroImage.

Multimodal Fusion of Structural and Functional Brain Imaging Data

Vince D. Calhoun, Jing Sui, V. Calhoun, 2016 .

Determining Electroconvulsive Therapy Response With Machine Learning.

J. Sui, C. Abbott, Dyani Loo, 2016, JAMA psychiatry.

NeuroMark: an adaptive independent component analysis framework for estimating reproducible and comparable fMRI biomarkers among brain disorders

Vince D. Calhoun, Zening Fu, Peter Kochunov, 2019 .

Application of Graph Theory to Assess Static and Dynamic Brain Connectivity: Approaches for Building Brain Graphs

Vince D. Calhoun, Yuhui Du, Qingbao Yu, 2018, Proceedings of the IEEE.

Diagnosis of schizophrenia with functional connectome data: a graph-based convolutional neural network approach

Il-Seok Oh, J. Sui, Sung-Wan Kim, 2021, BMC neuroscience.

Plasma metabolomics and clinical predictors of survival differences in COPD patients

V. Calhoun, B. Celli, J. Sui, 2019, Respiratory Research.

A functional connectome signature of blood pressure in >30,000 participants from the UK Biobank.

D. Scheinost, J. Sui, Rongtao Jiang, 2022, Cardiovascular research.

Dynamic Functional Connectivity Predicts Treatment Response to Electroconvulsive Therapy in Major Depressive Disorder

V. Calhoun, K. Narr, H. Mayberg, 2021, Biological Psychiatry.

Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network

J. Turner, Daoqiang Zhang, P. Kochunov, 2022, Nature Communications.

Multimodal Fusion Signature as Transdiagnostic Psychiatric Biomarker

V. Calhoun, J. Sui, S. Qi, 2020, Biological Psychiatry.

Aberrant brain functional and structural developments in MECP2 duplication rats

Zhimin Huang, J. Sui, Rongtao Jiang, 2022, Neurobiology of Disease.

Canonical and Replicable Multi-Scale Intrinsic Connectivity Networks in 100k+ Resting-State fMRI Datasets

B. Mueller, S. Potkin, Adrian Preda, 2022, bioRxiv.

Aberrant brain dynamics and spectral power in children with ADHD and its subtypes

J. Sui, Yue Cui, Xiangsheng Luo, 2022, European Child & Adolescent Psychiatry.

Associations between grip strength, brain structure, and mental health in > 40,000 participants from the UK Biobank

D. Scheinost, J. Sui, Rongtao Jiang, 2022, BMC Medicine.

Cognition, Aryl Hydrocarbon Receptor Repressor Methylation, and Abstinence Duration-Associated Multimodal Brain Networks in Smoking and Long-Term Smoking Cessation

Stacey B. Daughters, Daoqiang Zhang, J. Sui, 2022, Frontiers in Neuroscience.

Aberrant brain functional and structural developments in MECP2 duplication rats

Zhimin Huang, J. Sui, Z. Qiu, 2022, Neurobiology of Disease.

Structural and Functional Brain Abnormalities in Human Immunodeficiency Virus Disease Revealed by Multimodal Magnetic Resonance Imaging Fusion: Association With Cognitive Function

P. Bell, J. Sui, S. Gadde, 2021 .

Structural and functional brain abnormalities in HIV disease revealed by multimodal MRI fusion: association with cognitive function.

J. Sui, S. Gadde, N. Chen, 2020, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

Machine Learning Predicts Treatment Response in Bipolar & Major Depressive Disorders

Bradley T. Baker, E. Osuch, J. Sui, 2021, bioRxiv.

Multi-model order spatially constrained ICA reveals highly replicable group differences and consistent predictive results from fMRI data

A. Belger, S. McEwen, D. Mathalon, 2022, bioRxiv.

Identifying dynamic functional connectivity biomarkers using GIG‐ICA: Application to schizophrenia, schizoaffective disorder, and psychotic bipolar disorder

Dongdong Lin, Jiayu Chen, Yuhui Du, 2017, Human brain mapping.

Links between electroconvulsive therapy responsive and cognitive impairment multimodal brain networks in late-life major depressive disorder

Daoqiang Zhang, K. Narr, Y. Sheline, 2022, BMC Medicine.

Multimodal data revealed different neurobiological correlates of intelligence between males and females

Yuhui Du, J. Sui, Jian Yang, 2019, Brain Imaging and Behavior.

Whole-brain Functional Connectivity Dynamics associated with Electroconvulsive Therapy Treatment Response.

V. Calhoun, K. Narr, J. Sui, 2021, Biological psychiatry. Cognitive neuroscience and neuroimaging.

Inhibition‐directed multimodal imaging fusion patterns in adults with ADHD and its potential underlying “gene‐brain‐cognition” relationship

V. Calhoun, Q. Cao, Yufeng Wang, 2021, CNS neuroscience & therapeutics.

The relevance of transdiagnostic shared networks to the severity of symptoms and cognitive deficits in schizophrenia: a multimodal brain imaging fusion study

V. Calhoun, J. Turner, Xiao-hong Ma, 2020, Translational Psychiatry.

Combination of FMRI-SMRI-EEG data improves discrimination of schizophrenia patients by ensemble feature selection

Hao He, Vince D. Calhoun, Tianzi Jiang, 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

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

Hao He, Bryon A. Mueller, Vince D. Calhoun, 2013, NeuroImage.

Deep Learning in Neuroimaging: Promises and challenges

J. Sui, S. Plis, A. Abrol, 2022, IEEE Signal Processing Magazine.

NeuroMark: An automated and adaptive ICA based pipeline to identify reproducible fMRI markers of brain disorders

V. Calhoun, P. Kochunov, E. Osuch, 2020, NeuroImage: Clinical.

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

Jessica A. Turner, Vince D. Calhoun, Jingyu Liu, 2013, NeuroImage.

Tensor-Based Multi-index Representation Learning for Major Depression Disorder Detection with Resting-State fMRI

Jing Sui, Dongren Yao, Hao Guan, 2021, MICCAI.

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

Vince D. Calhoun, Tülay Adali, Jing Sui, 2010, NeuroImage.

An ensemble learning system for a 4-way classification of Alzheimer’s disease and mild cognitive impairment

Vince D. Calhoun, Yuhui Du, Jing Sui, 2018, Journal of Neuroscience Methods.

Gender Differences in Connectome-based Predictions of Individualized Intelligence Quotient and Sub-domain Scores

Tianzi Jiang, Dongdong Lin, Zening Fu, 2019, Cerebral cortex.

A pilot study on commonality and specificity of copy number variants in schizophrenia and bipolar disorder

V. Calhoun, G. Pearlson, Jingyu Liu, 2016, Translational Psychiatry.

Brain imaging-based machine learning in autism spectrum disorder: methods and applications

Jing Sui, Vince Calhoun, Rongtao Jiang, 2021, Journal of Neuroscience Methods.

Opposite Epigenetic Associations With Alcohol Use and Exercise Intervention

V. Calhoun, E. Claus, Jingyu Liu, 2018, Front. Psychiatry.

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls

Vince D. Calhoun, Sergey M. Plis, Jing Sui, 2017, NeuroImage.

Semi-supervised learning of brain functional networks

Hao He, Vince D. Calhoun, Yuhui Du, 2014, 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI).

A review of multivariate methods for multimodal fusion of brain imaging data

Vince D. Calhoun, Tülay Adali, Qingbao Yu, 2012, Journal of Neuroscience Methods.

Discriminating schizophrenia using recurrent neural network applied on time courses of multi-site FMRI data

Jing Sui, Kaibin Xu, Tianzi Jiang, 2019, EBioMedicine.

Structural brain architectures match intrinsic functional networks and vary across domains: A study from 15000+ individuals

Jessica A. Turner, Zening Fu, Yong Xu, 2019, bioRxiv.

An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data

Yuhui Du, J. Sui, Z. Fu, 2022, Medical Image Anal..

Data-driven approaches to neuroimaging biomarkers for neurological and psychiatric disorders: emerging approaches and examples

V. Calhoun, G. Pearlson, J. Sui, 2021, Current opinion in neurology.

FUNCTIONAL NETWORK CONNECTIVITY (FNC)-BASED GENERATIVE ADVERSARIAL NETWORK (GAN) AND ITS APPLICATIONS IN CLASSIFICATION OF MENTAL DISORDERS

Jianlong Zhao, Vince D. Calhoun, Jing Sui, 2019, bioRxiv.

In search of multimodal brain alterations in Alzheimer's and Binswanger's disease

V. Calhoun, J. Adair, A. Caprihan, 2019, NeuroImage: Clinical.

NeuroMark: a fully automated ICA method to identify effective fMRI markers of brain disorders

V. Calhoun, P. Kochunov, E. Osuch, 2019 .

Group ICA for identifying biomarkers in schizophrenia: ‘Adaptive’ networks via spatially constrained ICA show more sensitivity to group differences than spatio-temporal regression

Vince D. Calhoun, Daniel H. Mathalon, Zening Fu, 2018, NeuroImage: Clinical.

Dynamic functional connectivity impairments in early schizophrenia and clinical high-risk for psychosis

Dongdong Lin, Zening Fu, Jiayu Chen, 2017, NeuroImage.

Whole-Brain Functional Network Connectivity Abnormalities in Affective and Non-Affective Early Phase Psychosis

V. Calhoun, J. Sui, Z. Fu, 2021, Frontiers in Neuroscience.

Aberrant Functional Network Connectivity Transition Probability in Major Depressive Disorder

Jessica A. Turner, Vince D. Calhoun, Zening Fu, 2020, 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

Editorial: Identifying Neuroimaging-Based Markers for Distinguishing Brain Disorders

Jing Sui, Yuhui Du, Dongdong Lin, 2020, Frontiers in Neuroscience.

Transient increased thalamic-sensory connectivity and decreased whole-brain dynamism in autism

Vince D. Calhoun, Zening Fu, Bharat B. Biswal, 2019, NeuroImage.

Parallel Group ICA + ICA: Joint Estimation of Linked Functional Network Variability and Structural Covariation with Application to Schizophrenia

Jessica A. Turner, Bryon A. Mueller, Vince D. Calhoun, 2019, bioRxiv.

FUNCTIONAL NETWORK CONNECTIVITY (FNC)-BASED GENERATIVE ADVERSARIAL NETWORK (GAN) AND ITS APPLICATIONS IN BRAIN DISEASE DIAGNOSIS

V. Calhoun, J. Sui, D. Zhi, 2019 .

Deep Chronnectome Learning via Full Bidirectional Long Short-Term Memory Networks for MCI Diagnosis

Dinggang Shen, Han Zhang, Jing Sui, 2018, MICCAI.

Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion

Adrian Preda, Tianzi Jiang, Dongdong Lin, 2018, Nature Communications.

Multimodal Fusion With Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia

Jessica A. Turner, Bryon A. Mueller, Vince D. Calhoun, 2018, IEEE Transactions on Medical Imaging.

Comparison of IVA and GIG-ICA in Brain Functional Network Estimation Using fMRI Data

Vince D. Calhoun, Dongdong Lin, Yuhui Du, 2017, Front. Neurosci..

Multimodal neural correlates of cognitive control in the Human Connectome Project

Vince D. Calhoun, Srinivas Rachakonda, Deanna M. Barch, 2017, NeuroImage.

Building an EEG-fMRI Multi-Modal Brain Graph: A Concurrent EEG-fMRI Study

Hao He, Vince D. Calhoun, Yuhui Du, 2016, Front. Hum. Neurosci..

Dynamic default mode network connectivity diminished in patients with schizophrenia

Hao He, Vince D. Calhoun, Lei Wu, 2015, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).

Exploring difference and overlap between schizophrenia, schizoaffective and bipolar disorders using resting-state brain functional networks

Hao He, Vince D. Calhoun, Yuhui Du, 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Multi-model Order ICA: A Data-driven Method for Evaluating Brain Functional Network Connectivity Within and Between Multiple Spatial Scales

A. Belger, G. Pearlson, D. Mathalon, 2021, bioRxiv.

Dynamic state with covarying brain activity-connectivity: On the pathophysiology of schizophrenia

Jessica A. Turner, Vince D. Calhoun, Zening Fu, 2020, NeuroImage.

Altered amygdala-based functional connectivity in individuals with attenuated psychosis syndrome and first-episode schizophrenia

J. Sui, Young-Chul Chung, Nam-In Kang, 2020, Scientific Reports.

Identifying functional network changing patterns in individuals at clinical high-risk for psychosis and patients with early illness schizophrenia: A group ICA study

Vince D. Calhoun, Daniel H. Mathalon, Dongdong Lin, 2017, NeuroImage: Clinical.

Artifact removal in the context of group ICA: A comparison of single‐subject and group approaches

Hao He, Yuhui Du, Jing Sui, 2016, Human brain mapping.

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

Jingyu Liu, Qingbao Yu, Hao He, 2015, NeuroImage.

Function–structure associations of the brain: Evidence from multimodal connectivity and covariance studies

Vince D. Calhoun, Qingbao Yu, Jing Sui, 2014, NeuroImage.

Multimodal fusion of multiple rest fMRI networks and MRI gray matter via multilink joint ICA reveals highly significant function/structure coupling in Alzheimer’s disease

T. Adalı, J. Sui, V. Calhoun, 2023, bioRxiv.

Meta-Modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia

Jessica A. Turner, Bryon A. Mueller, Vince D. Calhoun, 2020, IEEE Transactions on Biomedical Engineering.

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

Hao He, Vince D. Calhoun, Yuhui Du, 2015, NeuroImage.

Comparing brain graphs in which nodes are regions of interest or independent components: A simulation study

Hao He, Vince D. Calhoun, Yuhui Du, 2017, Journal of Neuroscience Methods.

Human Neuroscience

Vince D. Calhoun, Jingyu Liu, Jing Sui, 2022 .

Multimodal brain deficits shared in early‐onset and adult‐onset schizophrenia predict positive symptoms regardless of illness stage

J. Sui, W. Shi, Wentao Zhao, 2022, Human brain mapping.

Visualizing Functional Network Connectivity Difference between Healthy Control and Major Depressive Disorder Using an Explainable Machine-learning Method

Vince D. Calhoun, Jing Sui, Mohammad S. E. Sendi, 2020, 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

Discriminating schizophrenia from normal controls using resting state functional network connectivity: A deep neural network and layer-wise relevance propagation method

Vince D. Calhoun, Sergey M. Plis, Tianzi Jiang, 2017, 2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP).

Mapping relationships among schizophrenia, bipolar and schizoaffective disorders: A deep classification and clustering framework using fMRI time series

V. Calhoun, G. Pearlson, J. Sui, 2021, Schizophrenia Research.

Shared and distinct resting functional connectivity in children and adults with attention-deficit/hyperactivity disorder

V. Calhoun, Q. Cao, Yufeng Wang, 2020, Translational Psychiatry.

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

Vince D. Calhoun, Godfrey D. Pearlson, Manel Martínez-Ramón, 2011, NeuroImage.

Complexity in mood disorder diagnosis: fMRI connectivity networks predicted medication‐class of response in complex patients

V Calhoun, V. Calhoun, J. Théberge, 2018, Acta psychiatrica Scandinavica.

Three‐way parallel group independent component analysis: Fusion of spatial and spatiotemporal magnetic resonance imaging data

Rogers F. Silva, Daoqiang Zhang, J. Sui, 2021, Human brain mapping.

Abnormal Dynamic Functional Network Connectivity Estimated from Default Mode Network Predicts Symptom Severity in Major Depressive Disorder

Jessica A. Turner, Vince D. Calhoun, Zening Fu, 2021, Brain Connect..

Neuronal Signatures of Negative and Positive Schemas towards the Self and Others in Patients with Early Stage Schizophrenia

J. Sui, Young-Chul Chung, Woo-Sung Kim, 2021, Psychiatry investigation.

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

Vince D. Calhoun, Tülay Adali, Jing Sui, 2011, NeuroImage.

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

Vince D. Calhoun, Jing Sui, Srinivas Rachakonda, 2010, Neuroinformatics.

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

Vince D. Calhoun, Tülay Adali, Jing Sui, 2009, NeuroImage.

Exploration of the optimal group-discriminating features using CC-ICA

Jing Sui, V.D. Calhoun, V. Calhoun, 2008, 2008 42nd Asilomar Conference on Signals, Systems and Computers.

A review of multivariate methods in brain imaging data fusion

Vince D. Calhoun, Tulay Adali, Jing Sui, 2010, Medical Imaging.

Subtypes of depression characterized by different cognitive decline and brain activity alterations.

V. Calhoun, Xiao-hong Ma, Tao Li, 2021, Journal of psychiatric research.

Three-way FMRI-DTI-methylation data fusion based on mCCA+jICA and its application to schizophrenia

Hao He, Vince D. Calhoun, Tülay Adali, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

A method for accurate group difference detection by constraining the mixing coefficients in an ICA framework

Tülay Adali, Jing Sui, Godfrey D Pearlson, 2009, Human brain mapping.

Dynamic functional connectivity links with treatment response of electroconvulsive therapy in major depressive disorder

V. Calhoun, K. Narr, H. Mayberg, 2021, bioRxiv.

Cerebro-cerebellar functional neuroplasticity mediates the effect of electric field on electroconvulsive therapy outcomes

J. Sui, Z. Fu, Z. Deng, 2023, Translational Psychiatry.

Predictive signature of static and dynamic functional connectivity for ECT clinical outcomes

J. Sui, Z. Fu, C. Abbott, 2023, Frontiers in Pharmacology.

Multi-subject fMRI analysis via combined independent component analysis and shift-invariant canonical polyadic decomposition

Vince D. Calhoun, Fengyu Cong, Qiu-Hua Lin, 2015, Journal of Neuroscience Methods.

Discriminating Bipolar Disorder From Major Depression Based on SVM-FoBa: Efficient Feature Selection With Multimodal Brain Imaging Data

Vince D. Calhoun, Yu Zhang, Mao-Hu Zhu, 2015, IEEE Transactions on Autonomous Mental Development.

Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data

Vince D. Calhoun, Dongdong Lin, Jiayu Chen, 2017, NeuroImage.

DNA Methylation and Resting Brain Function Mediate the Association between Childhood Urbanicity and Better Speed of Processing

Dai Zhang, J. Sui, H. Tan, 2021, Cerebral cortex.

Multimodal Neuroimaging Patterns Associated with Social Responsiveness Impairment in Autism: A Replication Study

Zening Fu, Jing Sui, Shile Qi, 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

Supervised multimodal fusion and its application in searching joint neuromarkers of working memory deficits in schizophrenia

Theo G. M. van Erp, Jessica A. Turner, Bryon A. Mueller, 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

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

Vince D. Calhoun, Vamsi K. Potluru, Sergey M. Plis, 2014, NeuroImage.

Resting fMRI measures are associated with cognitive deficits in schizophrenia assessed by the MATRICS consensus cognitive battery

Hao He, Vince D. Calhoun, Tianzi Jiang, 2015, Medical Imaging.

Temporal-Adaptive Graph Convolutional Network for Automated Identification of Major Depressive Disorder Using Resting-State fMRI

Dinggang Shen, Erkun Yang, Mingxia Liu, 2020, MLMI@MICCAI.

Reward Processing in Novelty Seekers: A Transdiagnostic Psychiatric Imaging Biomarker

Rogers F. Silva, A. Belger, V. Calhoun, 2021, Biological Psychiatry.

Brain multimodal co-alterations related to delay discounting: a multimodal MRI fusion analysis in persons with and without cocaine use disorder

V. Calhoun, J. Sui, Ryan P. Bell, 2021, BMC neuroscience.

MicroRNA132 associated multimodal neuroimaging patterns in unmedicated major depressive disorder

Tianzi Jiang, Jing Sui, Shile Qi, 2018, Brain : a journal of neurology.

The Individualized Prediction of Neurocognitive Function in People Living With HIV Based on Clinical and Multimodal Connectome Data

Shana A. Hall, Xiang Li, J. Sui, 2023, IEEE Journal of Biomedical and Health Informatics.

Antidepressant treatment-related brain activity changes in remitted major depressive disorder

J. Sui, X. Yang, Poornima Kumar, 2023, Psychiatry Research: Neuroimaging.

Identification of Genetic and Epigenetic Marks Involved in Population Structure

Kent Hutchison, Jing Sui, Jingyu Liu, 2010, PloS one.

Connectome-based individualized prediction of temperament trait scores

Vince D. Calhoun, Tianzi Jiang, Dongdong Lin, 2018, NeuroImage.

Consistent brain structural abnormalities and multisite individualised classification of schizophrenia using deep neural networks

Dai Zhang, C. Li, Huawang Wu, 2022, The British Journal of Psychiatry.

The Shared and Distinct White Matter Networks Between Drug-Naive Patients With Obsessive-Compulsive Disorder and Schizophrenia

Fuquan Zhang, J. Sui, Zhenhe Zhou, 2019, Front. Neurosci..

Abnormal Dynamic Functional Network Connectivity and Graph Theoretical Analysis in Major Depressive Disorder

Miao Pan, Vince D. Calhoun, Tianzi Jiang, 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Electroconvulsive therapy treatment responsive multimodal brain networks

Jing Sui, Shile Qi, Vince D Calhoun, 2020, Human brain mapping.

Source-Based Morphometry Analysis of Group Differences in Fractional Anisotropy in Schizophrenia

Vince D. Calhoun, Jing Sui, Arvind Caprihan, 2011, Brain Connect..

A Mutual Multi-Scale Triplet Graph Convolutional Network for Classification of Brain Disorders Using Functional or Structural Connectivity

Dinggang Shen, Jing Sui, Mingxia Liu, 2021, IEEE Transactions on Medical Imaging.

Triplet Graph Convolutional Network for Multi-scale Analysis of Functional Connectivity Using Functional MRI

Jie Wei, Mingliang Wang, Chunfeng Lian, 2019, GLMI@MICCAI.

Multi-model order spatially constrained ICA reveals highly replicable group differences and consistent predictive results from resting data: A large N fMRI schizophrenia study

A. Belger, D. Mathalon, B. Mueller, 2023, NeuroImage: Clinical.

Elevated C-reactive protein mediates the liver-brain axis: a preliminary study

D. Scheinost, J. Sui, V. Calhoun, 2023, EBioMedicine.

Fusion of Multiple Spatial Networks Derived from Complex-Valued fMRI Data via CNN Classification

V. Calhoun, J. Sui, Yue Qiu, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

SSPNet: An interpretable 3D-CNN for classification of schizophrenia using phase maps of resting-state complex-valued fMRI data

V. Calhoun, J. Sui, C. Zhuo, 2022, Medical Image Anal..

SMRI Biomarkers Predict Electroconvulsive Treatment Outcomes: Accuracy with Independent Data Sets

Tianzi Jiang, Dongdong Lin, Jiayu Chen, 2018, Neuropsychopharmacology.

Deep learning methods and applications in neuroimaging

Jong-Hwan Lee, Vince Calhoun, Jing Sui, 2020, Journal of Neuroscience Methods.

Associations of physical frailty with health outcomes and brain structure in 483 033 middle-aged and older adults: a population-based study from the UK Biobank

D. Scheinost, J. Sui, K. Yoo, 2023, The Lancet. Digital health.

Alterations in grey matter structure linked to frequency-specific cortico-subcortical connectivity in schizophrenia via multimodal data fusion

A. Belger, G. Pearlson, D. Mathalon, 2023, bioRxiv.

Investigating ADHD subtypes in children using temporal dynamics of the electroencephalogram (EEG) microstates *

Jing Sui, Dongren Yao, Li Sun, 2021, 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

Multi-scale convolutional recurrent neural network for psychiatric disorder identification in resting-state EEG

J. Sui, Dandan Liu, Weizheng Yan, 2023, Frontiers in Psychiatry.

Multi-model Order ICA: A Data-driven Method for Evaluating Brain Functional Network Connectivity Within and Between Multiple Spatial Scales

A. Belger, V. Calhoun, G. Pearlson, 2021, bioRxiv.

Multi-study evaluation of neuroimaging-based prediction of medication class in mood disorders

Bradley T. Baker, E. Osuch, J. Sui, 2023, Psychiatry Research: Neuroimaging.

Biological Subtypes Bridge Diagnoses and Biomarkers: A Novel Research Track for Mental Disorders

Ming Song, T. Jiang, J. Sui, 2017, Neuroscience Bulletin.

Association of the soluble CTLA4 with schizophrenia: an observational study

Fuquan Zhang, Lin He, Shengying Qin, 2020 .

ADHD Classification Within and Cross Cohort Using an Ensembled Feature Selection Framework

Xiaojie Guo, Jing Sui, Vince D Calhoun, 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

BNCPL: Brain-Network-based Convolutional Prototype Learning for Discriminating Depressive Disorders

Vince D. Calhoun, Jing Sui, Shile Qi, 2021, 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

Application of Graph Theory to Assess Static and Dynamic Brain Connectivity: Approaches for Building Brain Graphs

V. Calhoun, G. Pearlson, Qingbao Yu, 2018, Proceedings of the IEEE.

Subdivisions of the posteromedial cortex in disorders of consciousness

Ming Song, T. Jiang, J. Sui, 2018, NeuroImage: Clinical.

Functional network connectivity (FNC)-based generative adversarial network (GAN) and its applications in classification of mental disorders

Jianlong Zhao, Jing Sui, Dongmei Zhi, 2020, Journal of Neuroscience Methods.

An Automatic Artifact Removal Method for Independent Components Derived from Second-level FMRI Analysis

T. Adalı, J. Sui, G. Pearlson, 2009, NeuroImage.

Multimodal fusion of multiple rest fMRI networks and MRI gray matter via parallel multilink joint ICA reveals highly significant function/structure coupling in Alzheimer's disease

T. Adalı, J. Sui, V. Calhoun, 2023, Human brain mapping.

Functional Connectivity Hubs Could Serve as a Potential Biomarker in Alzheimer's Disease: A Reproducible Study.

Tianzi Jiang, Jing Sui, Xinqing Zhang, 2015, Current Alzheimer research.

Data-driven cluster selection for subcortical shape and cortical thickness predicts recovery from depressive symptoms

Paul M. Thompson, Jing Sui, Shantanu H. Joshi, 2017, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).

Discriminating ADHD From Healthy Controls Using a Novel Feature Selection Method Based on Relative Importance and Ensemble Learning

Vince D. Calhoun, Yufeng Wang, Lu Liu, 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Discriminating Bipolar Disorder from Major Depression using Whole-Brain Functional Connectivity: a Feature Selection Analysis with SVM-FoBa Algorithm

V. Calhoun, E. Osuch, J. Sui, 2016, Journal of Signal Processing Systems.

Discriminating Bipolar Disorder from Major Depression using Whole-Brain Functional Connectivity: a Feature Selection Analysis with SVM-FoBa Algorithm

Vince D. Calhoun, Tianzi Jiang, Mao-Hu Zhu, 2015, Journal of Signal Processing Systems.

Artifact removal in the context of group ICA: A comparison of single‐subject and group approaches

V. Calhoun, E. Allen, Hao He, 2016, Human brain mapping.

Aberrant brain dynamics and spectral power in children with ADHD and its subtypes

J. Sui, Yue Cui, Xiangsheng Luo, 2022, European Child & Adolescent Psychiatry.

Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness.

V. Calhoun, J. Sui, 2016, Biological psychiatry. Cognitive neuroscience and neuroimaging.

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

A. Belger, V. Calhoun, G. Pearlson, 2022, Brain Connect..

Predicting individualized intelligence quotient scores using brainnetome-atlas based functional connectivity

Vince D. Calhoun, Tianzi Jiang, Yuhui Du, 2017, 2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP).