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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Image Analysis Using Convolutional Neural Networks for Modeling 2D Fracture Propagation. - Robyn L. Miller; Bryan A. Moore; Hari S. Viswanathan; Gowri Srinivasan (ICDM Workshops, 2017)

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

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

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

Reduced-Order Modeling through Machine Learning Approaches for Brittle Fracture Applications. - A. Hunter; Bryan A. Moore; Maruti Kumar Mudunuru; Viet T. Chau; Robyn L. Miller; Roselyne B. Tchoua; C. Nyshadham; Satish Karra; Dan O'Malley; Esteban Rougier; Hari S. Viswanathan; Gowri Srinivasan (CoRR, 2018)

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

Mapping and interpreting the dynamic connectivity of the brain. - Catie Chang; Shella D. Keilholz; Robyn L. Miller; Mark W. Woolrich (NeuroImage, 2018)

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

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

Aberrant Functional Network Connectivity Transition Probability in Major Depressive Disorder. - Elaheh Zendehrouh; Mohammad S. Eslampanah Sendi; Jing Sui; Zening Fu; Dongmei Zhi; Luxian Lv; Xiaohong Ma; Qing Ke; Xianbin Li; Chuanyue Wang; Christopher C. Abbott; Jessica A. Turner; et al. (EMBC, 2020)

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

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

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

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

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

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

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

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

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

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

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

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

Abnormal Dynamic Functional Network Connectivity Estimated from Default Mode Network Predicts Symptom Severity in Major Depressive Disorder. - Mohammad S. Eslampanah Sendi; Elaheh Zendehrouh; Jing Sui; Zening Fu; Dongmei Zhi; Luxian Lv; Xiaohong Ma; Qing Ke; Xianbin Li; Chuanyue Wang; Christopher C. Abbott; Jessica A. Turner; et al. (Brain Connect., 2021)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

DSAM: A deep learning framework for analyzing temporal and spatial dynamics in brain networks. - Bishal Thapaliya; Robyn L. Miller; Jiayu Chen 003; Yu-Ping Wang 002; Esra Akbas; Ram Sapkota; Bhaskar Ray; Pranav Suresh; Santosh Ghimire; Vince D. Calhoun; Jingyu Liu 001 (Medical Image Anal., 2025)