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ORCIDMartin A. Lindquist
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2020 – today
- 2024
[j41]Pratim Guha Niyogi
, Martin A. Lindquist, Tapabrata Maiti:
A Tensor Based Varying-Coefficient Model for Multi-Modal Neuroimaging Data Analysis. IEEE Trans. Signal Process. 72: 1607-1619 (2024)- 2023
- [j40]Tanmay Nath, Brian Caffo, Tor D. Wager, Martin A. Lindquist:
A machine learning based approach towards high-dimensional mediation analysis. NeuroImage 268: 119843 (2023) - 2022
- [j39]Hamed Honari, Martin A. Lindquist:
Mode decomposition-based time-varying phase synchronization for fMRI. NeuroImage 261: 119519 (2022) - [i3]Hamed Honari, Martin A. Lindquist:
Mode decomposition-based time-varying phase synchronization for fMRI Data. CoRR abs/2203.13955 (2022) - 2021
- [j38]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:
Detecting Task-Dependent Functional Connectivity in Group Iterative Multiple Model Estimation with Person-Specific Hemodynamic Response Functions. Brain Connect. 11(6): 418-429 (2021) - [j37]Hamed Honari, Ann S. Choe, Martin A. Lindquist:
Evaluating phase synchronization methods in fMRI: A comparison study and new approaches. NeuroImage 228: 117704 (2021) - [j36]Heather Shappell, Kelly A. Duffy, Keri Rosch, James J. Pekar, Stewart H. Mostofsky, Martin A. Lindquist, Jessica R. Cohen:
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. NeuroImage 229: 117753 (2021) - [j35]Guoqing Wang, John Muschelli, Martin A. Lindquist:
Moderated t-tests for group-level fMRI analysis. NeuroImage 237: 118141 (2021) - 2020
- [j34]Yi Zhao, Martin A. Lindquist, Brian S. Caffo:
Sparse principal component based high-dimensional mediation analysis. Comput. Stat. Data Anal. 142 (2020) - [c2]Andrey Gritsenko, Martin A. Lindquist, Moo K. Chung:
Twin Classification in Resting-State Brain Connectivity. ISBI 2020: 1391-1394 - [i2]Hamed Honari, Ann S. Choe, Martin A. Lindquist:
Evaluating phase synchronization methods in fMRI: a comparison study and new approaches. CoRR abs/2009.10126 (2020)
2010 – 2019
- 2019
- [j33]Heather Shappell, Brian S. Caffo, James J. Pekar, Martin A. Lindquist:
Improved state change estimation in dynamic functional connectivity using hidden semi-Markov models. NeuroImage 191: 243-257 (2019) - [j32]Hamed Honari, Ann S. Choe, James J. Pekar, Martin A. Lindquist:
Investigating the impact of autocorrelation on time-varying connectivity. NeuroImage 197: 37-48 (2019) - [c1]Shih-Gu Huang, Andrey Gritsenko, Martin A. Lindquist, Moo K. Chung:
Circular Pearson Correlation Using Cosine Series Expansion. ISBI 2019: 1774-1777 - 2018
- [j31]Amanda F. Mejia, Mary Beth Nebel, Anita D. Barber, Ann S. Choe, James J. Pekar, Brian S. Caffo, Martin A. Lindquist:
Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage. NeuroImage 172: 478-491 (2018) - [j30]Victor Solo, Jean-Baptiste Poline, Martin A. Lindquist, Sean L. Simpson, F. DuBois Bowman, Moo K. Chung, Ben Cassidy:
Connectivity in fMRI: Blind Spots and Breakthroughs. IEEE Trans. Medical Imaging 37(7): 1537-1550 (2018) - [i1]Andrey Gritsenko, Martin A. Lindquist, Gregory R. Kirk, Moo K. Chung:
Hill Climbing Optimized Twin Classification Using Resting-State Functional MRI. CoRR abs/1807.00244 (2018) - 2017
- [j29]Maleeha F. Syed, Martin A. Lindquist, Jay J. Pillai, Shruti Agarwal, Sachin K. Gujar, Ann S. Choe, Brian Caffo, Haris I. Sair:
Dynamic Functional Connectivity States Between the Dorsal and Ventral Sensorimotor Networks Revealed by Dynamic Conditional Correlation Analysis of Resting-State Functional Magnetic Resonance Imaging. Brain Connect. 7(10): 635-642 (2017) - [j28]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:
Group-regularized individual prediction: theory and application to pain. NeuroImage 145: 274-287 (2017) - [j27]Maria Kudela, Jaroslaw Harezlak, Martin A. Lindquist:
Assessing uncertainty in dynamic functional connectivity. NeuroImage 149: 165-177 (2017) - [j26]Anders Eklund, Martin A. Lindquist, Mattias Villani:
A Bayesian heteroscedastic GLM with application to fMRI data with motion spikes. NeuroImage 155: 354-369 (2017) - [j25]Joshua C. Cheng, Rachael L. Bosma, Kasey S. Hemington, Aaron Kucyi, Martin A. Lindquist, Karen D. Davis:
Slow-5 dynamic functional connectivity reflects the capacity to sustain cognitive performance during pain. NeuroImage 157: 61-68 (2017) - [j24]Ann S. Choe, Mary Beth Nebel, Anita D. Barber, Jessica R. Cohen, Yuting Xu, James J. Pekar, Brian Caffo, Martin A. Lindquist:
Comparing test-retest reliability of dynamic functional connectivity methods. NeuroImage 158: 155-175 (2017) - [j23]Shaojie Chen, Kai Liu, Yuguang Yang, Yuting Xu, Seonjoo Lee, Martin A. Lindquist, Brian S. Caffo, Joshua T. Vogelstein:
An M-estimator for reduced-rank system identification. Pattern Recognit. Lett. 86: 76-81 (2017) - 2016
- [j22]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:
Demonstration of Brain Tumor-Induced Neurovascular Uncoupling in Resting-State fMRI at Ultrahigh Field. Brain Connect. 6(4): 267-272 (2016) - 2015
- [j21]Amanda F. Mejia, Mary Beth Nebel, Haochang Shou, Ciprian M. Crainiceanu, James J. Pekar, Stewart H. Mostofsky, Brian Caffo, Martin A. Lindquist:
Improving reliability of subject-level resting-state fMRI parcellation with shrinkage estimators. NeuroImage 112: 14-29 (2015) - [j20]John Muschelli, Elizabeth M. Sweeney, Martin A. Lindquist, Ciprian M. Crainiceanu:
fslr: Connecting the FSL Software with R. R J. 7(1): 163 (2015) - 2014
- [j19]David Degras, Martin A. Lindquist:
A hierarchical model for simultaneous detection and estimation in multi-subject fMRI studies. NeuroImage 98: 61-72 (2014) - [j18]Martin A. Lindquist, Yuting Xu, Mary Beth Nebel, Brian S. Caffo:
Evaluating dynamic bivariate correlations in resting-state fMRI: A comparison study and a new approach. NeuroImage 101: 531-546 (2014) - [j17]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:
Shrinkage prediction of seed-voxel brain connectivity using resting state fMRI. NeuroImage 102: 938-944 (2014) - 2013
- [j16]Ivor Cribben, Tor D. Wager, Martin A. Lindquist:
Detecting functional connectivity change points for single-subject fMRI data. Frontiers Comput. Neurosci. 7: 143 (2013) - [j15]Martin A. Lindquist, Michael E. Sobel:
Cloak and DAG: A response to the comments on our comment. NeuroImage 76: 446-449 (2013) - [j14]Martin A. Lindquist, Brian C. Caffo, Ciprian M. Crainiceanu:
Ironing out the statistical wrinkles in "ten ironic rules". NeuroImage 81: 499-502 (2013) - 2012
- [j13]Martin A. Lindquist, Julie Spicer, Iris Asllani, Tor D. Wager:
Estimating and testing variance components in a multi-level GLM. NeuroImage 59(1): 490-501 (2012) - [j12]Ivor Cribben, Ragnheidur Haraldsdottir, Lauren Y. Atlas, Tor D. Wager, Martin A. Lindquist:
Dynamic connectivity regression: Determining state-related changes in brain connectivity. NeuroImage 61(4): 907-920 (2012) - 2011
- [j11]Martin A. Lindquist, Michael E. Sobel:
Graphical models, potential outcomes and causal inference: Comment on Ramsey, Spirtes and Glymour. NeuroImage 57(2): 334-336 (2011) - 2010
- [j10]Martin A. Lindquist:
The benefits of rapid 3D fMRI. Int. J. Imaging Syst. Technol. 20(1): 14-22 (2010) - [j9]Lucy F. Robinson, Tor D. Wager, Martin A. Lindquist:
Change point estimation in multi-subject fMRI studies. NeuroImage 49(2): 1581-1592 (2010)
2000 – 2009
- 2009
- [j8]Martin A. Lindquist, Ji Meng Loh, Lauren Y. Atlas, Tor D. Wager:
Modeling the hemodynamic response function in fMRI: Efficiency, bias and mis-modeling. NeuroImage 45(1): S187-S198 (2009) - [j7]Tor D. Wager, Martin A. Lindquist, Thomas E. Nichols, Hedy Kober, Jared X. Van Snellenberg:
Evaluating the consistency and specificity of neuroimaging data using meta-analysis. NeuroImage 45(1): S210-S221 (2009) - [j6]Tor D. Wager, Christian E. Waugh, Martin A. Lindquist, Douglas C. Noll, Barbara L. Fredrickson, Stephan F. Taylor:
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. NeuroImage 47(3): 821-835 (2009) - [j5]Tor D. Wager, Vanessa A. van Ast, Brent L. Hughes, Matthew L. Davidson, Martin A. Lindquist, Kevin N. Ochsner:
Brain mediators of cardiovascular responses to social threat, Part II: Prefrontal-subcortical pathways and relationship with anxiety. NeuroImage 47(3): 836-851 (2009) - 2008
- [j4]Jack Grinband, Tor D. Wager, Martin A. Lindquist, Vincent P. Ferrera, Joy Hirsch:
Detection of time-varying signals in event-related fMRI designs. NeuroImage 43(3): 509-520 (2008) - 2007
- [j3]Martin A. Lindquist, Christian E. Waugh, Tor D. Wager:
Modeling state-related fMRI activity using change-point theory. NeuroImage 35(3): 1125-1141 (2007) - 2006
- [j2]Martin A. Lindquist, Cun-Hui Zhang, Gary Glover, Larry Shepp, Qing X. Yang:
A generalization of the two-dimensional prolate spheroidal wave function method for nonrectilinear MRI data acquisition methods. IEEE Trans. Image Process. 15(9): 2792-2804 (2006) - 2003
- [j1]Martin A. Lindquist:
Optimal data acquisition in fMRI using prolate spheroidal wave functions. Int. J. Imaging Syst. Technol. 13(2): 126-132 (2003)
Coauthor Index
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last updated on 2024-10-07 21:26 CEST by the dblp team
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