Optimal data acquisition in fMRI using prolate spheroidal wave functions. - Martin A. Lindquist (Int. J. Imaging Syst. Technol., 2003)

A generalization of the two-dimensional prolate spheroidal wave function method for nonrectilinear MRI data acquisition methods. - Martin A. Lindquist; Cun-Hui Zhang; Gary Glover; Larry Shepp; Qing X. Yang (IEEE Trans. Image Process., 2006)

Modeling state-related fMRI activity using change-point theory. - Martin A. Lindquist; Christian E. Waugh; Tor D. Wager (NeuroImage, 2007)

Detection of time-varying signals in event-related fMRI designs. - Jack Grinband; Tor D. Wager; Martin A. Lindquist; Vincent P. Ferrera; Joy Hirsch (NeuroImage, 2008)

Modeling the hemodynamic response function in fMRI: Efficiency, bias and mis-modeling. - Martin A. Lindquist; Ji Meng Loh; Lauren Y. Atlas; Tor D. Wager (NeuroImage, 2009)

Brain mediators of cardiovascular responses to social threat, Part II: Prefrontal-subcortical pathways and relationship with anxiety. - Tor D. Wager; Vanessa A. van Ast; Brent L. Hughes; Matthew L. Davidson; Martin A. Lindquist; Kevin N. Ochsner (NeuroImage, 2009)

Evaluating the consistency and specificity of neuroimaging data using meta-analysis. - Tor D. Wager; Martin A. Lindquist; Thomas E. Nichols; Hedy Kober; Jared X. Van Snellenberg (NeuroImage, 2009)

Brain mediators of cardiovascular responses to social threat: Part I: Reciprocal dorsal and ventral sub-regions of the medial prefrontal cortex and heart-rate reactivity. - Tor D. Wager; Christian E. Waugh; Martin A. Lindquist; Douglas C. Noll; Barbara L. Fredrickson; Stephan F. Taylor (NeuroImage, 2009)

The benefits of rapid 3D fMRI. - Martin A. Lindquist (Int. J. Imaging Syst. Technol., 2010)

Change point estimation in multi-subject fMRI studies. - Lucy F. Robinson; Tor D. Wager; Martin A. Lindquist (NeuroImage, 2010)

Graphical models, potential outcomes and causal inference: Comment on Ramsey, Spirtes and Glymour. - Martin A. Lindquist; Michael E. Sobel (NeuroImage, 2011)

Dynamic connectivity regression: Determining state-related changes in brain connectivity. - Ivor Cribben; Ragnheidur Haraldsdottir; Lauren Y. Atlas; Tor D. Wager; Martin A. Lindquist (NeuroImage, 2012)

Estimating and testing variance components in a multi-level GLM. - Martin A. Lindquist; Julie Spicer; Iris Asllani; Tor D. Wager (NeuroImage, 2012)

Detecting functional connectivity change points for single-subject fMRI data. - Ivor Cribben; Tor D. Wager; Martin A. Lindquist (Frontiers Comput. Neurosci., 2013)

Ironing out the statistical wrinkles in "ten ironic rules". - Martin A. Lindquist; Brian C. Caffo; Ciprian M. Crainiceanu (NeuroImage, 2013)

Cloak and DAG: A response to the comments on our comment. - Martin A. Lindquist; Michael E. Sobel (NeuroImage, 2013)

A hierarchical model for simultaneous detection and estimation in multi-subject fMRI studies. - David Degras; Martin A. Lindquist (NeuroImage, 2014)

Evaluating dynamic bivariate correlations in resting-state fMRI: A comparison study and a new approach. - Martin A. Lindquist; Yuting Xu; Mary Beth Nebel; Brian S. Caffo (NeuroImage, 2014)

Shrinkage prediction of seed-voxel brain connectivity using resting state fMRI. - Haochang Shou; Ani Eloyan; Mary Beth Nebel; Amanda F. Mejia; James J. Pekar; Stewart H. Mostofsky; Brian S. Caffo; Martin A. Lindquist; Ciprian M. Crainiceanu (NeuroImage, 2014)

Improving reliability of subject-level resting-state fMRI parcellation with shrinkage estimators. - Amanda F. Mejia; Mary Beth Nebel; Haochang Shou; Ciprian M. Crainiceanu; James J. Pekar; Stewart H. Mostofsky; Brian Caffo; Martin A. Lindquist (NeuroImage, 2015)

fslr: Connecting the FSL Software with R. - John Muschelli; Elizabeth M. Sweeney; Martin A. Lindquist; Ciprian M. Crainiceanu (R J., 2015)

Demonstration of Brain Tumor-Induced Neurovascular Uncoupling in Resting-State fMRI at Ultrahigh Field. - Shruti Agarwal; Haris I. Sair; Raag D. Airan; Jun Hua; Craig K. Jones; Hye-Young Heo; Alessandro Olivi; Martin A. Lindquist; James J. Pekar; Jay J. Pillai (Brain Connect., 2016)

Dynamic Functional Connectivity States Between the Dorsal and Ventral Sensorimotor Networks Revealed by Dynamic Conditional Correlation Analysis of Resting-State Functional Magnetic Resonance Imaging. - Maleeha F. Syed; Martin A. Lindquist; Jay J. Pillai; Shruti Agarwal; Sachin K. Gujar; Ann S. Choe; Brian Caffo; Haris I. Sair (Brain Connect., 2017)

Slow-5 dynamic functional connectivity reflects the capacity to sustain cognitive performance during pain. - Joshua C. Cheng; Rachael L. Bosma; Kasey S. Hemington; Aaron Kucyi; Martin A. Lindquist; Karen D. Davis (NeuroImage, 2017)

Comparing test-retest reliability of dynamic functional connectivity methods. - Ann S. Choe; Mary Beth Nebel; Anita D. Barber; Jessica R. Cohen; Yuting Xu; James J. Pekar; Brian Caffo; Martin A. Lindquist (NeuroImage, 2017)

A Bayesian heteroscedastic GLM with application to fMRI data with motion spikes. - Anders Eklund 002; Martin A. Lindquist; Mattias Villani (NeuroImage, 2017)

Assessing uncertainty in dynamic functional connectivity. - Maria Kudela; Jaroslaw Harezlak; Martin A. Lindquist (NeuroImage, 2017)

Group-regularized individual prediction: theory and application to pain. - Martin A. Lindquist; Anjali Krishnan; Marina López-Solà; Marieke Jepma; Choong-Wan Woo; Leonie Koban; Mathieu Roy; Lauren Y. Atlas; Liane Schmidt; Luke J. Chang; Elizabeth A. Reynolds Losin; Hedwig Eisenbarth; et al. (NeuroImage, 2017)

An M-estimator for reduced-rank system identification. - Shaojie Chen; Kai Liu; Yuguang Yang 002; Yuting Xu; Seonjoo Lee; Martin A. Lindquist; Brian S. Caffo; Joshua T. Vogelstein (Pattern Recognit. Lett., 2017)

Hill Climbing Optimized Twin Classification Using Resting-State Functional MRI. - Andrey Gritsenko; Martin A. Lindquist; Gregory R. Kirk; Moo K. Chung (CoRR, 2018)

Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage. - Amanda F. Mejia; Mary Beth Nebel; Anita D. Barber; Ann S. Choe; James J. Pekar; Brian S. Caffo; Martin A. Lindquist (NeuroImage, 2018)

Connectivity in fMRI: Blind Spots and Breakthroughs. - Victor Solo; Jean-Baptiste Poline; Martin A. Lindquist; Sean L. Simpson; F. DuBois Bowman; Moo K. Chung; Ben Cassidy (IEEE Trans. Medical Imaging, 2018)

Circular Pearson Correlation Using Cosine Series Expansion. - Shih-Gu Huang; Andrey Gritsenko; Martin A. Lindquist; Moo K. Chung (ISBI, 2019)

Investigating the impact of autocorrelation on time-varying connectivity. - Hamed Honari; Ann S. Choe; James J. Pekar; Martin A. Lindquist (NeuroImage, 2019)

Improved state change estimation in dynamic functional connectivity using hidden semi-Markov models. - Heather Shappell; Brian S. Caffo; James J. Pekar; Martin A. Lindquist (NeuroImage, 2019)

Twin Classification in Resting-State Brain Connectivity. - Andrey Gritsenko; Martin A. Lindquist; Moo K. Chung (ISBI, 2020)

Sparse principal component based high-dimensional mediation analysis. - Yi Zhao; Martin A. Lindquist; Brian S. Caffo (Comput. Stat. Data Anal., 2020)

Detecting Task-Dependent Functional Connectivity in Group Iterative Multiple Model Estimation with Person-Specific Hemodynamic Response Functions. - Kelly A. Duffy; Zachary F. Fisher; Cara A. Arizmendi; Peter C. M. Molenaar; Joseph B. Hopfinger; Jessica R. Cohen; Adriene M. Beltz; Martin A. Lindquist; Michael N. Hallquist; Kathleen M. Gates (Brain Connect., 2021)

Evaluating phase synchronization methods in fMRI: A comparison study and new approaches. - Hamed Honari; Ann S. Choe; Martin A. Lindquist (NeuroImage, 2021)

Children with attention-deficit/hyperactivity disorder spend more time in hyperconnected network states and less time in segregated network states as revealed by dynamic connectivity analysis. - Heather Shappell; Kelly A. Duffy; Keri Rosch; James J. Pekar; Stewart H. Mostofsky; Martin A. Lindquist; Jessica R. Cohen (NeuroImage, 2021)

Moderated t-tests for group-level fMRI analysis. - Guoqing Wang; John Muschelli; Martin A. Lindquist (NeuroImage, 2021)

Mode decomposition-based time-varying phase synchronization for fMRI Data. - Hamed Honari; Martin A. Lindquist (CoRR, 2022)

Mode decomposition-based time-varying phase synchronization for fMRI. - Hamed Honari; Martin A. Lindquist (NeuroImage, 2022)

A machine learning based approach towards high-dimensional mediation analysis. - Tanmay Nath; Brian Caffo; Tor D. Wager; Martin A. Lindquist (NeuroImage, 2023)

A Tensor Based Varying-Coefficient Model for Multi-Modal Neuroimaging Data Analysis. - Pratim Guha Niyogi; Martin A. Lindquist; Tapabrata Maiti (IEEE Trans. Signal Process., 2024)

Graph-constrained analysis for multivariate functional data. - Debangan Dey; Sudipto Banerjee; Martin A. Lindquist; Abhirup Datta (J. Multivar. Anal., 2025)

BrainMT: A Hybrid Mamba-Transformer Architecture for Modeling Long-Range Dependencies in Functional MRI Data. - Arunkumar Kannan; Martin A. Lindquist; Brian Caffo (CoRR, 2025)