Martin A. Lindquist

According to our database, Martin A. Lindquist authored at least 45 papers between 2003 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

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

2023

A machine learning based approach towards high-dimensional mediation analysis.

Tanmay Nath, Brian Caffo, Tor D. Wager, Martin A. Lindquist

NeuroImage, March, 2023

2022

Mode decomposition-based time-varying phase synchronization for fMRI.

Hamed Honari, Martin A. Lindquist

NeuroImage, 2022

Mode decomposition-based time-varying phase synchronization for fMRI Data.

Hamed Honari, Martin A. Lindquist

CoRR, 2022

2021

Moderated <i>t-</i>tests for group-level fMRI analysis.

Guoqing Wang, John Muschelli, 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

Evaluating phase synchronization methods in fMRI: A comparison study and new approaches.

Hamed Honari, Ann S. Choe, Martin A. Lindquist

NeuroImage, 2021

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

2020

Sparse principal component based high-dimensional mediation analysis.

Yi Zhao, Martin A. Lindquist, Brian S. Caffo

Comput. Stat. Data Anal., 2020

Twin Classification in Resting-State Brain Connectivity.

Andrey Gritsenko, Martin A. Lindquist, Moo K. Chung

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

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

Investigating the impact of autocorrelation on time-varying connectivity.

Hamed Honari, Ann S. Choe, James J. Pekar, Martin A. Lindquist

NeuroImage, 2019

Circular Pearson Correlation Using Cosine Series Expansion.

Shih-Gu Huang, Andrey Gritsenko, Martin A. Lindquist, Moo K. Chung

Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

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

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

Hill Climbing Optimized Twin Classification Using Resting-State Functional MRI.

Andrey Gritsenko, Martin A. Lindquist, Gregory R. Kirk, Moo K. Chung

CoRR, 2018

2017

An M-estimator for reduced-rank system identification.

Shaojie Chen, Kai Liu, Yuguang Yang, Yuting Xu, Seonjoo Lee, Martin A. Lindquist, Brian S. Caffo, Joshua T. Vogelstein

Pattern Recognit. Lett., 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, Yoni K. Ashar, Elizabeth Delk, Tor D. Wager

NeuroImage, 2017

Assessing uncertainty in dynamic functional connectivity.

Maria Kudela, Jaroslaw Harezlak, Martin A. Lindquist

NeuroImage, 2017

A Bayesian heteroscedastic GLM with application to fMRI data with motion spikes.

Anders Eklund, Martin A. Lindquist, Mattias Villani

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

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

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

2016

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

2015

fslr: Connecting the FSL Software with R.

John Muschelli, Elizabeth M. Sweeney, Martin A. Lindquist, Ciprian M. Crainiceanu

R J., 2015

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

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

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

A hierarchical model for simultaneous detection and estimation in multi-subject fMRI studies.

David Degras, Martin A. Lindquist

NeuroImage, 2014

2013

Cloak and DAG: A response to the comments on our comment.

Martin A. Lindquist, Michael E. Sobel

NeuroImage, 2013

Ironing out the statistical wrinkles in "ten ironic rules".

Martin A. Lindquist, Brian C. Caffo, Ciprian M. Crainiceanu

NeuroImage, 2013

Detecting functional connectivity change points for single-subject fMRI data.

Ivor Cribben, Tor D. Wager, Martin A. Lindquist

Frontiers Comput. Neurosci., 2013

2012

Estimating and testing variance components in a multi-level GLM.

Martin A. Lindquist, Julie Spicer, Iris Asllani, Tor D. Wager

NeuroImage, 2012

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

2011

Graphical models, potential outcomes and causal inference: Comment on Ramsey, Spirtes and Glymour.

Martin A. Lindquist, Michael E. Sobel

NeuroImage, 2011

2010

Change point estimation in multi-subject fMRI studies.

Lucy F. Robinson, Tor D. Wager, Martin A. Lindquist

NeuroImage, 2010

The benefits of rapid 3D fMRI.

Martin A. Lindquist

Int. J. Imaging Syst. Technol., 2010

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

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 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

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

2008

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

2007

Modeling state-related fMRI activity using change-point theory.

Martin A. Lindquist, Christian E. Waugh, Tor D. Wager

NeuroImage, 2007

2006

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

2003

Optimal data acquisition in fMRI using prolate spheroidal wave functions.

Martin A. Lindquist

Int. J. Imaging Syst. Technol., 2003