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Items: 1 to 50 of 99

1.

Unraveling Diagnostic Biomarkers of Schizophrenia Through Structure-Revealing Fusion of Multi-Modal Neuroimaging Data.

Acar E, Schenker C, Levin-Schwartz Y, Calhoun VD, Adali T.

Front Neurosci. 2019 May 3;13:416. doi: 10.3389/fnins.2019.00416. eCollection 2019.

2.

Parallel group ICA+ICA: Joint estimation of linked functional network variability and structural covariation with application to schizophrenia.

Qi S, Sui J, Chen J, Liu J, Jiang R, Silva R, Iraji A, Damaraju E, Salman M, Lin D, Fu Z, Zhi D, Turner JA, Bustillo J, Ford JM, Mathalon DH, Voyvodic J, McEwen S, Preda A, Belger A, Potkin SG, Mueller BA, Adali T, Calhoun VD.

Hum Brain Mapp. 2019 May 16. doi: 10.1002/hbm.24632. [Epub ahead of print]

PMID:
31099151
3.

Intimate Partner Violence During Pregnancy in Turkey: Determinants From Nationwide Surveys.

Yüksel-Kaptanoğlu İ, Adalı T.

J Interpers Violence. 2019 Mar 27:886260519837652. doi: 10.1177/0886260519837652. [Epub ahead of print]

PMID:
30913951
4.

Guest editorial.

Adali T, Yavuz DO.

Int J Biol Macromol. 2019 Apr 15;127:701. doi: 10.1016/j.ijbiomac.2019.01.160. Epub 2019 Jan 29. No abstract available.

PMID:
30708023
5.

Extraction of time-varying spatio-temporal networks using parameter-tuned constrained IVA.

Bhinge S, Mowakeaa R, Calhoun VD, Adali T.

IEEE Trans Med Imaging. 2019 Jan 23. doi: 10.1109/TMI.2019.2893651. [Epub ahead of print]

PMID:
30676948
6.

Chitosan-graft-poly(N-hydroxy ethyl acrylamide) copolymers: Synthesis, characterization and preliminary blood compatibility in vitro.

Bahramzadeh E, Yilmaz E, Adali T.

Int J Biol Macromol. 2019 Feb 15;123:1257-1266. doi: 10.1016/j.ijbiomac.2018.12.023. Epub 2018 Dec 3.

PMID:
30521908
7.

The chondrocyte cell proliferation of a chitosan/silk fibroin/egg shell membrane hydrogels.

Adali T, Kalkan R, Karimizarandi L.

Int J Biol Macromol. 2019 Mar 1;124:541-547. doi: 10.1016/j.ijbiomac.2018.11.226. Epub 2018 Nov 26.

PMID:
30496865
8.

A method to compare the discriminatory power of data-driven methods: Application to ICA and IVA.

Levin-Schwartz Y, Calhoun VD, Adalı T.

J Neurosci Methods. 2019 Jan 1;311:267-276. doi: 10.1016/j.jneumeth.2018.10.008. Epub 2018 Oct 30.

PMID:
30389489
9.

Application of Graph Theory to Assess Static and Dynamic Brain Connectivity: Approaches for Building Brain Graphs.

Yu Q, Du Y, Chen J, Sui J, Adali T, Pearlson G, Calhoun VD.

Proc IEEE Inst Electr Electron Eng. 2018 May;106(5):886-906. doi: 10.1109/JPROC.2018.2825200. Epub 2018 Apr 25.

10.

The Use of Scaffolds in Cartilage Regeneration.

Kalkan R, Nwekwo CW, Adali T.

Crit Rev Eukaryot Gene Expr. 2018;28(4):343-348. doi: 10.1615/CritRevEukaryotGeneExpr.2018024574.

PMID:
30311583
11.

The role of diversity in data-driven analysis of multi-subject fMRI data: Comparison of approaches based on independence and sparsity using global performance metrics.

Long Q, Bhinge S, Levin-Schwartz Y, Boukouvalas Z, Calhoun VD, Adalı T.

Hum Brain Mapp. 2019 Feb 1;40(2):489-504. doi: 10.1002/hbm.24389. Epub 2018 Sep 21.

12.

Resting-State fMRI Dynamics and Null Models: Perspectives, Sampling Variability, and Simulations.

Miller RL, Abrol A, Adali T, Levin-Schwarz Y, Calhoun VD.

Front Neurosci. 2018 Sep 6;12:551. doi: 10.3389/fnins.2018.00551. eCollection 2018.

13.

The Wonders of Silk Fibroin Biomaterials in the Treatment of Breast Cancer.

Tulay P, Galam N, Adali T.

Crit Rev Eukaryot Gene Expr. 2018;28(2):129-134. doi: 10.1615/CritRevEukaryotGeneExpr.2018021331.

PMID:
30055539
14.

Shared and Subject-Specific Dictionary Learning (ShSSDL) Algorithm for Multisubject fMRI Data Analysis.

Iqbal A, Seghouane AK, Adali T.

IEEE Trans Biomed Eng. 2018 Nov;65(11):2519-2528. doi: 10.1109/TBME.2018.2806958. Epub 2018 Feb 16.

PMID:
29993508
15.

A Shared Vision for Machine Learning in Neuroscience.

Vu MT, Adalı T, Ba D, Buzsáki G, Carlson D, Heller K, Liston C, Rudin C, Sohal VS, Widge AS, Mayberg HS, Sapiro G, Dzirasa K.

J Neurosci. 2018 Feb 14;38(7):1601-1607. doi: 10.1523/JNEUROSCI.0508-17.2018. Epub 2018 Jan 26. Review.

16.

A window-less approach for capturing time-varying connectivity in fMRI data reveals the presence of states with variable rates of change.

Yaesoubi M, Adalı T, Calhoun VD.

Hum Brain Mapp. 2018 Apr;39(4):1626-1636. doi: 10.1002/hbm.23939. Epub 2018 Jan 9.

17.

Comparison of IVA and GIG-ICA in Brain Functional Network Estimation Using fMRI Data.

Du Y, Lin D, Yu Q, Sui J, Chen J, Rachakonda S, Adali T, Calhoun VD.

Front Neurosci. 2017 May 19;11:267. doi: 10.3389/fnins.2017.00267. eCollection 2017.

18.

Blind Source Separation for Unimodal and Multimodal Brain Networks: A Unifying Framework for Subspace Modeling.

Silva RF, Plis SM, Sui J, Pattichis MS, Adalı T, Calhoun VD.

IEEE J Sel Top Signal Process. 2016 Oct;10(7):1134-1149. doi: 10.1109/JSTSP.2016.2594945. Epub 2016 Jul 27.

19.

Quantifying the Interaction and Contribution of Multiple Datasets in Fusion: Application to the Detection of Schizophrenia.

Levin-Schwartz Y, Calhoun VD, Adali T.

IEEE Trans Med Imaging. 2017 Jul;36(7):1385-1395. doi: 10.1109/TMI.2017.2678483. Epub 2017 Mar 6.

20.

Sample-poor estimation of order and common signal subspace with application to fusion of medical imaging data.

Levin-Schwartz Y, Song Y, Schreier PJ, Calhoun VD, Adalı T.

Neuroimage. 2016 Jul 1;134:486-493. doi: 10.1016/j.neuroimage.2016.03.058. Epub 2016 Mar 31.

21.

The role of diversity in complex ICA algorithms for fMRI analysis.

Du W, Levin-Schwartz Y, Fu GS, Ma S, Calhoun VD, Adalı T.

J Neurosci Methods. 2016 May 1;264:129-135. doi: 10.1016/j.jneumeth.2016.03.012. Epub 2016 Mar 15.

22.

Higher Dimensional Meta-State Analysis Reveals Reduced Resting fMRI Connectivity Dynamism in Schizophrenia Patients.

Miller RL, Yaesoubi M, Turner JA, Mathalon D, Preda A, Pearlson G, Adali T, Calhoun VD.

PLoS One. 2016 Mar 16;11(3):e0149849. doi: 10.1371/journal.pone.0149849. eCollection 2016.

23.

Independent Vector Analysis for SSVEP Signal Enhancement, Detection, and Topographical Mapping.

Emge DK, Vialatte FB, Dreyfus G, Adalı T.

Brain Topogr. 2018 Jan;31(1):117-124. doi: 10.1007/s10548-016-0478-2. Epub 2016 Mar 3.

PMID:
26936596
24.

Silk fibroin as a non-thrombogenic biomaterial.

Adalı T, Uncu M.

Int J Biol Macromol. 2016 Sep;90:11-9. doi: 10.1016/j.ijbiomac.2016.01.088. Epub 2016 Jan 27.

PMID:
26826290
25.

Multi-modal data fusion using source separation: Two effective models based on ICA and IVA and their properties.

Adali T, Levin-Schwartz Y, Calhoun VD.

Proc IEEE Inst Electr Electron Eng. 2015 Sep 1;103(9):1478-93. doi: 10.1109/JPROC.2015.2461624.

26.

Quantifying motor recovery after stroke using independent vector analysis and graph-theoretical analysis.

Laney J, Adalı T, McCombe Waller S, Westlake KP.

Neuroimage Clin. 2015 Apr 22;8:298-304. doi: 10.1016/j.nicl.2015.04.014. eCollection 2015.

27.

Spatial Variance in Resting fMRI Networks of Schizophrenia Patients: An Independent Vector Analysis.

Gopal S, Miller RL, Michael A, Adali T, Cetin M, Rachakonda S, Bustillo JR, Cahill N, Baum SA, Calhoun VD.

Schizophr Bull. 2016 Jan;42(1):152-60. doi: 10.1093/schbul/sbv085. Epub 2015 Jun 23.

28.

Comparison of PCA approaches for very large group ICA.

Calhoun VD, Silva RF, Adalı T, Rachakonda S.

Neuroimage. 2015 Sep;118:662-6. doi: 10.1016/j.neuroimage.2015.05.047. Epub 2015 May 27.

29.

Capturing subject variability in fMRI data: A graph-theoretical analysis of GICA vs. IVA.

Laney J, Westlake KP, Ma S, Woytowicz E, Calhoun VD, Adalı T.

J Neurosci Methods. 2015 May 30;247:32-40. doi: 10.1016/j.jneumeth.2015.03.019. Epub 2015 Mar 20.

30.

Independent Vector Analysis for Gradient Artifact Removal in Concurrent EEG-fMRI Data.

Acharjee PP, Phlypo R, Wu L, Calhoun VD, Adali T.

IEEE Trans Biomed Eng. 2015 Jul;62(7):1750-8. doi: 10.1109/TBME.2015.2403298. Epub 2015 Feb 13.

PMID:
25700437
31.

General nonunitary constrained ICA and its application to complex-valued fMRI data.

Rodriguez PA, Anderson M, Calhoun VD, Adali T.

IEEE Trans Biomed Eng. 2015 Mar;62(3):922-9. doi: 10.1109/TBME.2014.2371791. Epub 2014 Nov 20.

PMID:
25420255
32.

The chronnectome: time-varying connectivity networks as the next frontier in fMRI data discovery.

Calhoun VD, Miller R, Pearlson G, Adalı T.

Neuron. 2014 Oct 22;84(2):262-74. doi: 10.1016/j.neuron.2014.10.015. Epub 2014 Oct 22. Review.

33.

Impact of autocorrelation on functional connectivity.

Arbabshirani MR, Damaraju E, Phlypo R, Plis S, Allen E, Ma S, Mathalon D, Preda A, Vaidya JG, Adali T, Calhoun VD.

Neuroimage. 2014 Nov 15;102 Pt 2:294-308. doi: 10.1016/j.neuroimage.2014.07.045. Epub 2014 Jul 27.

34.

Preserving subject variability in group fMRI analysis: performance evaluation of GICA vs. IVA.

Michael AM, Anderson M, Miller RL, Adalı T, Calhoun VD.

Front Syst Neurosci. 2014 Jun 26;8:106. doi: 10.3389/fnsys.2014.00106. eCollection 2014.

35.

A statistically motivated framework for simulation of stochastic data fusion models applied to multimodal neuroimaging.

Silva RF, Plis SM, Adalı T, Calhoun VD.

Neuroimage. 2014 Nov 15;102 Pt 1:92-117. doi: 10.1016/j.neuroimage.2014.04.035. Epub 2014 Apr 18. Review.

PMID:
24747087
36.

Restricted Boltzmann machines for neuroimaging: an application in identifying intrinsic networks.

Hjelm RD, Calhoun VD, Salakhutdinov R, Allen EA, Adali T, Plis SM.

Neuroimage. 2014 Aug 1;96:245-60. doi: 10.1016/j.neuroimage.2014.03.048. Epub 2014 Mar 28.

37.

Dynamic changes of spatial functional network connectivity in healthy individuals and schizophrenia patients using independent vector analysis.

Ma S, Calhoun VD, Phlypo R, Adalı T.

Neuroimage. 2014 Apr 15;90:196-206. doi: 10.1016/j.neuroimage.2013.12.063. Epub 2014 Jan 10.

38.

Independent component analysis for brain FMRI does indeed select for maximal independence.

Calhoun VD, Potluru VK, Phlypo R, Silva RF, Pearlmutter BA, Caprihan A, Plis SM, Adalı T.

PLoS One. 2013 Aug 29;8(8):e73309. doi: 10.1371/journal.pone.0073309. eCollection 2013. Erratum in: PLoS One. 2013;8(10). doi:10.1371/annotation/52c7b854-2d52-4b49-9f9f-6560830f9428.

39.

Synthesis and characterization of noncytotoxic and biodegradable polymethacrylates-grafted chitosan gels.

Adalı T.

Biomed Mater Eng. 2013;23(5):349-59. doi: 10.3233/BME-130759.

PMID:
23988707
40.

PEG-calf thymus DNA interactions: conformational, morphological and spectroscopic thermal studies.

Adali T, Bentaleb A, Elmarzugi N, Hamza AM.

Int J Biol Macromol. 2013 Oct;61:373-8. doi: 10.1016/j.ijbiomac.2013.07.024. Epub 2013 Aug 5.

PMID:
23928012
41.

Group Study of Simulated Driving fMRI Data by Multiset Canonical Correlation Analysis.

Li YO, Adalı T, Calhoun VD.

J Signal Process Syst. 2012 Jul 1;68(1):31-48.

42.

Order Selection of the Linear Mixing Model for Complex-valued FMRI Data.

Xiong W, Li YO, Correa N, Adalı T, Calhoun VD.

J Signal Process Syst. 2012 May 1;67(2):117-128.

43.

Three-way FMRI-DTI-methylation data fusion based on mCCA+jICA and its application to schizophrenia.

Sui J, He H, Liu J, Yu Q, Adali T, Pearlson GD, Calhoun VD.

Conf Proc IEEE Eng Med Biol Soc. 2012;2012:2692-5. doi: 10.1109/EMBC.2012.6346519.

PMID:
23366480
44.

Multisubject independent component analysis of fMRI: a decade of intrinsic networks, default mode, and neurodiagnostic discovery.

Calhoun VD, Adalı T.

IEEE Rev Biomed Eng. 2012;5:60-73. doi: 10.1109/RBME.2012.2211076. Review.

45.

Three-way (N-way) fusion of brain imaging data based on mCCA+jICA and its application to discriminating schizophrenia.

Sui J, He H, Pearlson GD, Adali T, Kiehl KA, Yu Q, Clark VP, Castro E, White T, Mueller BA, Ho BC, Andreasen NC, Calhoun VD.

Neuroimage. 2013 Feb 1;66:119-32. doi: 10.1016/j.neuroimage.2012.10.051. Epub 2012 Oct 26.

47.

High classification accuracy for schizophrenia with rest and task FMRI data.

Du W, Calhoun VD, Li H, Ma S, Eichele T, Kiehl KA, Pearlson GD, Adali T.

Front Hum Neurosci. 2012 Jun 4;6:145. doi: 10.3389/fnhum.2012.00145. eCollection 2012.

48.

Modulations of functional connectivity in the healthy and schizophrenia groups during task and rest.

Ma S, Calhoun VD, Eichele T, Du W, Adalı T.

Neuroimage. 2012 Sep;62(3):1694-704. doi: 10.1016/j.neuroimage.2012.05.048. Epub 2012 May 24.

49.

Decomposing the brain: components and modes, networks and nodes.

Calhoun VD, Eichele T, Adalı T, Allen EA.

Trends Cogn Sci. 2012 May;16(5):255-6. doi: 10.1016/j.tics.2012.03.008. Epub 2012 Apr 7.

50.

Constrained source-based morphometry identifies structural networks associated with default mode network.

Luo L, Xu L, Jung R, Pearlson G, Adali T, Calhoun VD.

Brain Connect. 2012;2(1):33-43. doi: 10.1089/brain.2011.0026.

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