Sort by
Items per page

Send to

Choose Destination

Search results

Items: 1 to 50 of 75


Investigating the impact of autocorrelation on time-varying connectivity.

Honari H, Choe AS, Pekar JJ, Lindquist MA.

Neuroimage. 2019 Apr 22;197:37-48. doi: 10.1016/j.neuroimage.2019.04.042. [Epub ahead of print]


Fatigue induces long-lasting detrimental changes in motor-skill learning.

Branscheidt M, Kassavetis P, Anaya M, Rogers D, Huang HD, Lindquist MA, Celnik P.

Elife. 2019 Mar 5;8. pii: e40578. doi: 10.7554/eLife.40578.


Improved state change estimation in dynamic functional connectivity using hidden semi-Markov models.

Shappell H, Caffo BS, Pekar JJ, Lindquist MA.

Neuroimage. 2019 May 1;191:243-257. doi: 10.1016/j.neuroimage.2019.02.013. Epub 2019 Feb 10.


Pain-related nucleus accumbens function: modulation by reward and sleep disruption.

Seminowicz DA, Remeniuk B, Krimmel SR, Smith MT, Barrett FS, Wulff AB, Furman AJ, Geuter S, Lindquist MA, Irwin MR, Finan PH.

Pain. 2019 May;160(5):1196-1207. doi: 10.1097/j.pain.0000000000001498.


The Pain of Sleep Loss: A Brain Characterization in Humans.

Krause AJ, Prather AA, Wager TD, Lindquist MA, Walker MP.

J Neurosci. 2019 Mar 20;39(12):2291-2300. doi: 10.1523/JNEUROSCI.2408-18.2018. Epub 2019 Jan 28.


Modular preprocessing pipelines can reintroduce artifacts into fMRI data.

Lindquist MA, Geuter S, Wager TD, Caffo BS.

Hum Brain Mapp. 2019 Jun 1;40(8):2358-2376. doi: 10.1002/hbm.24528. Epub 2019 Jan 21.


Exposure-based therapy changes amygdala and hippocampus resting-state functional connectivity in patients with posttraumatic stress disorder.

Zhu X, Suarez-Jimenez B, Lazarov A, Helpman L, Papini S, Lowell A, Durosky A, Lindquist MA, Markowitz JC, Schneier F, Wager TD, Neria Y.

Depress Anxiety. 2018 Oct;35(10):974-984. doi: 10.1002/da.22816. Epub 2018 Sep 10.


Connectivity in fMRI: Blind Spots and Breakthroughs.

Solo V, Poline JB, Lindquist MA, Simpson SL, Bowman FD, Chung MK, Cassidy B.

IEEE Trans Med Imaging. 2018 Jul;37(7):1537-1550. doi: 10.1109/TMI.2018.2831261.


Dynamic Functional Connectivity States Reflecting Psychotic-like Experiences.

Barber AD, Lindquist MA, DeRosse P, Karlsgodt KH.

Biol Psychiatry Cogn Neurosci Neuroimaging. 2018 May;3(5):443-453. doi: 10.1016/j.bpsc.2017.09.008. Epub 2017 Sep 28.


Multivariate machine learning distinguishes cross-network dynamic functional connectivity patterns in state and trait neuropathic pain.

Cheng JC, Rogachov A, Hemington KS, Kucyi A, Bosma RL, Lindquist MA, Inman RD, Davis KD.

Pain. 2018 Sep;159(9):1764-1776. doi: 10.1097/j.pain.0000000000001264.


Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage.

Mejia AF, Nebel MB, Barber AD, Choe AS, Pekar JJ, Caffo BS, Lindquist MA.

Neuroimage. 2018 May 15;172:478-491. doi: 10.1016/j.neuroimage.2018.01.029. Epub 2018 Feb 14.


Big Data and Neuroimaging.

Webb-Vargas Y, Chen S, Fisher A, Mejia A, Xu Y, Crainiceanu C, Caffo B, Lindquist MA.

Stat Biosci. 2017 Dec;9(2):543-558. doi: 10.1007/s12561-017-9195-y. Epub 2017 May 22.


Dynamic Functional Connectivity States Between the Dorsal and Ventral Sensorimotor Networks Revealed by Dynamic Conditional Correlation Analysis of Resting-State Functional Magnetic Resonance Imaging.

Syed MF, Lindquist MA, Pillai JJ, Agarwal S, Gujar SK, Choe AS, Caffo B, Sair HI.

Brain Connect. 2017 Dec;7(10):635-642. doi: 10.1089/brain.2017.0533.


Altered cortical brain activity in end stage liver disease assessed by multi-channel near-infrared spectroscopy: Associations with delirium.

Yoshimura A, Goodson C, Johns JT, Towe MM, Irvine ES, Rendradjaja NA, Max LK, LaFlam A, Ledford EC, Probert J, Tieges Z, Edwin DH, MacLullich AMJ, Hogue CW, Lindquist MA, Gurakar A, Neufeld KJ, Kamiya A.

Sci Rep. 2017 Aug 23;7(1):9258. doi: 10.1038/s41598-017-10024-7.


Comparing test-retest reliability of dynamic functional connectivity methods.

Choe AS, Nebel MB, Barber AD, Cohen JR, Xu Y, Pekar JJ, Caffo B, Lindquist MA.

Neuroimage. 2017 Sep;158:155-175. doi: 10.1016/j.neuroimage.2017.07.005. Epub 2017 Jul 5.


High-dimensional multivariate mediation with application to neuroimaging data.

Chén OY, Crainiceanu C, Ogburn EL, Caffo BS, Wager TD, Lindquist MA.

Biostatistics. 2018 Apr 1;19(2):121-136. doi: 10.1093/biostatistics/kxx027.


Slow-5 dynamic functional connectivity reflects the capacity to sustain cognitive performance during pain.

Cheng JC, Bosma RL, Hemington KS, Kucyi A, Lindquist MA, Davis KD.

Neuroimage. 2017 Aug 15;157:61-68. doi: 10.1016/j.neuroimage.2017.06.005. Epub 2017 Jun 3.


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

Eklund A, Lindquist MA, Villani M.

Neuroimage. 2017 Jul 15;155:354-369. doi: 10.1016/j.neuroimage.2017.04.069. Epub 2017 May 1.


Response variability of different anodal transcranial direct current stimulation intensities across multiple sessions.

Ammann C, Lindquist MA, Celnik PA.

Brain Stimul. 2017 Jul - Aug;10(4):757-763. doi: 10.1016/j.brs.2017.04.003. Epub 2017 Apr 10.


Presurgical Brain Mapping of the Ventral Somatomotor Network in Patients with Brain Tumors Using Resting-State fMRI.

Yahyavi-Firouz-Abadi N, Pillai JJ, Lindquist MA, Calhoun VD, Agarwal S, Airan RD, Caffo B, Gujar SK, Sair HI.

AJNR Am J Neuroradiol. 2017 May;38(5):1006-1012. doi: 10.3174/ajnr.A5132. Epub 2017 Mar 31.


PCA leverage: outlier detection for high-dimensional functional magnetic resonance imaging data.

Mejia AF, Nebel MB, Eloyan A, Caffo B, Lindquist MA.

Biostatistics. 2017 Jul 1;18(3):521-536. doi: 10.1093/biostatistics/kxw050.


Parallel group independent component analysis for massive fMRI data sets.

Chen S, Huang L, Qiu H, Nebel MB, Mostofsky SH, Pekar JJ, Lindquist MA, Eloyan A, Caffo BS.

PLoS One. 2017 Mar 9;12(3):e0173496. doi: 10.1371/journal.pone.0173496. eCollection 2017.


Building better biomarkers: brain models in translational neuroimaging.

Woo CW, Chang LJ, Lindquist MA, Wager TD.

Nat Neurosci. 2017 Feb 23;20(3):365-377. doi: 10.1038/nn.4478. Review.


Quantifying cerebral contributions to pain beyond nociception.

Woo CW, Schmidt L, Krishnan A, Jepma M, Roy M, Lindquist MA, Atlas LY, Wager TD.

Nat Commun. 2017 Feb 14;8:14211. doi: 10.1038/ncomms14211.


Assessing uncertainty in dynamic functional connectivity.

Kudela M, Harezlak J, Lindquist MA.

Neuroimage. 2017 Apr 1;149:165-177. doi: 10.1016/j.neuroimage.2017.01.056. Epub 2017 Jan 27.


Effect Size Estimation in Neuroimaging.

Reddan MC, Lindquist MA, Wager TD.

JAMA Psychiatry. 2017 Mar 1;74(3):207-208. doi: 10.1001/jamapsychiatry.2016.3356. No abstract available.


Generalizability of Neuroimaging Studies in 5 Common Psychiatric Disorders Based on the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC).

Blanco C, Wall MM, Lindquist MA, Rodríguez-Fernández JM, Franco S, Wang S, Olfson M.

J Clin Psychiatry. 2016 Dec;77(12):e1618-e1625. doi: 10.4088/JCP.15m10264.


Altered resting state functional connectivity of fear and reward circuitry in comorbid PTSD and major depression.

Zhu X, Helpman L, Papini S, Schneier F, Markowitz JC, Van Meter PE, Lindquist MA, Wager TD, Neria Y.

Depress Anxiety. 2017 Jul;34(7):641-650. doi: 10.1002/da.22594. Epub 2016 Dec 28.


Neural changes in extinction recall following prolonged exposure treatment for PTSD: A longitudinal fMRI study.

Helpman L, Marin MF, Papini S, Zhu X, Sullivan GM, Schneier F, Neria M, Shvil E, Malaga Aragon MJ, Markowitz JC, Lindquist MA, Wager T, Milad M, Neria Y.

Neuroimage Clin. 2016 Oct 10;12:715-723. eCollection 2016.


Two-way principal component analysis for matrix-variate data, with an application to functional magnetic resonance imaging data.

Huang L, Reiss PT, Xiao L, Zipunnikov V, Lindquist MA, Crainiceanu CM.

Biostatistics. 2017 Apr 1;18(2):214-229. doi: 10.1093/biostatistics/kxw040.


Demonstration of Brain Tumor-Induced Neurovascular Uncoupling in Resting-State fMRI at Ultrahigh Field.

Agarwal S, Sair HI, Airan R, Hua J, Jones CK, Heo HY, Olivi A, Lindquist MA, Pekar JJ, Pillai JJ.

Brain Connect. 2016 May;6(4):267-72. doi: 10.1089/brain.2015.0402. Epub 2016 Feb 26.


Presurgical brain mapping of the language network in patients with brain tumors using resting-state fMRI: Comparison with task fMRI.

Sair HI, Yahyavi-Firouz-Abadi N, Calhoun VD, Airan RD, Agarwal S, Intrapiromkul J, Choe AS, Gujar SK, Caffo B, Lindquist MA, Pillai JJ.

Hum Brain Mapp. 2016 Mar;37(3):913-23. doi: 10.1002/hbm.23075. Epub 2015 Dec 10.


Group-regularized individual prediction: theory and application to pain.

Lindquist MA, Krishnan A, López-Solà M, Jepma M, Woo CW, Koban L, Roy M, Atlas LY, Schmidt L, Chang LJ, Reynolds Losin EA, Eisenbarth H, Ashar YK, Delk E, Wager TD.

Neuroimage. 2017 Jan 15;145(Pt B):274-287. doi: 10.1016/j.neuroimage.2015.10.074. Epub 2015 Nov 17.


Reproducibility and Temporal Structure in Weekly Resting-State fMRI over a Period of 3.5 Years.

Choe AS, Jones CK, Joel SE, Muschelli J, Belegu V, Caffo BS, Lindquist MA, van Zijl PC, Pekar JJ.

PLoS One. 2015 Oct 30;10(10):e0140134. doi: 10.1371/journal.pone.0140134. eCollection 2015.


Dynamic connectivity detection: an algorithm for determining functional connectivity change points in fMRI data.

Xu Y, Lindquist MA.

Front Neurosci. 2015 Sep 4;9:285. doi: 10.3389/fnins.2015.00285. eCollection 2015.


An fMRI-Based Neural Signature of Decisions to Smoke Cannabis.

Bedi G, Lindquist MA, Haney M.

Neuropsychopharmacology. 2015 Nov;40(12):2657-65. doi: 10.1038/npp.2015.135. Epub 2015 May 12.


Explicit knowledge enhances motor vigor and performance: motivation versus practice in sequence tasks.

Wong AL, Lindquist MA, Haith AM, Krakauer JW.

J Neurophysiol. 2015 Jul;114(1):219-32. doi: 10.1152/jn.00218.2015. Epub 2015 Apr 22.


Improving reliability of subject-level resting-state fMRI parcellation with shrinkage estimators.

Mejia AF, Nebel MB, Shou H, Crainiceanu CM, Pekar JJ, Mostofsky S, Caffo B, Lindquist MA.

Neuroimage. 2015 May 15;112:14-29. doi: 10.1016/j.neuroimage.2015.02.042. Epub 2015 Feb 28.


Resting brain activity in disorders of consciousness: a systematic review and meta-analysis.

Hannawi Y, Lindquist MA, Caffo BS, Sair HI, Stevens RD.

Neurology. 2015 Mar 24;84(12):1272-80. doi: 10.1212/WNL.0000000000001404. Epub 2015 Feb 20. Review. Erratum in: Neurology. 2016 Jan 12;86(2):202.


Zen and the art of multiple comparisons.

Lindquist MA, Mejia A.

Psychosom Med. 2015 Feb-Mar;77(2):114-25. doi: 10.1097/PSY.0000000000000148.


Separate neural representations for physical pain and social rejection.

Woo CW, Koban L, Kross E, Lindquist MA, Banich MT, Ruzic L, Andrews-Hanna JR, Wager TD.

Nat Commun. 2014 Nov 17;5:5380. doi: 10.1038/ncomms6380.


Health effects of lesion localization in multiple sclerosis: spatial registration and confounding adjustment.

Eloyan A, Shou H, Shinohara RT, Sweeney EM, Nebel MB, Cuzzocreo JL, Calabresi PA, Reich DS, Lindquist MA, Crainiceanu CM.

PLoS One. 2014 Sep 18;9(9):e107263. doi: 10.1371/journal.pone.0107263. eCollection 2014.


Evaluating dynamic bivariate correlations in resting-state fMRI: a comparison study and a new approach.

Lindquist MA, Xu Y, Nebel MB, Caffo BS.

Neuroimage. 2014 Nov 1;101:531-46. doi: 10.1016/j.neuroimage.2014.06.052. Epub 2014 Jun 30.


Shrinkage prediction of seed-voxel brain connectivity using resting state fMRI.

Shou H, Eloyan A, Nebel MB, Mejia A, Pekar JJ, Mostofsky S, Caffo B, Lindquist MA, Crainiceanu CM.

Neuroimage. 2014 Nov 15;102 Pt 2:938-44. doi: 10.1016/j.neuroimage.2014.05.043. Epub 2014 May 29.


Brain mediators of the effects of noxious heat on pain.

Atlas LY, Lindquist MA, Bolger N, Wager TD.

Pain. 2014 Aug;155(8):1632-48. doi: 10.1016/j.pain.2014.05.015. Epub 2014 May 17.


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

Degras D, Lindquist MA.

Neuroimage. 2014 Sep;98:61-72. doi: 10.1016/j.neuroimage.2014.04.052. Epub 2014 May 2.


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

Cribben I, Wager TD, Lindquist MA.

Front Comput Neurosci. 2013 Oct 30;7:143. doi: 10.3389/fncom.2013.00143. eCollection 2013.


Quantifying the reliability of image replication studies: the image intraclass correlation coefficient (I2C2).

Shou H, Eloyan A, Lee S, Zipunnikov V, Crainiceanu AN, Nebel NB, Caffo B, Lindquist MA, Crainiceanu CM.

Cogn Affect Behav Neurosci. 2013 Dec;13(4):714-24.


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

Lindquist MA, Caffo B, Crainiceanu C.

Neuroimage. 2013 Nov 1;81:499-502. doi: 10.1016/j.neuroimage.2013.02.056. Epub 2013 Apr 12.

Supplemental Content

Loading ...
Support Center