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Items: 1 to 20 of 101

1.

Dynamic thresholding networks for schizophrenia diagnosis.

Zou H, Yang J.

Artif Intell Med. 2019 May;96:25-32. doi: 10.1016/j.artmed.2019.03.007. Epub 2019 Mar 18.

PMID:
31164208
2.

Characterizing dynamic amplitude of low-frequency fluctuation and its relationship with dynamic functional connectivity: An application to schizophrenia.

Fu Z, Tu Y, Di X, Du Y, Pearlson GD, Turner JA, Biswal BB, Zhang Z, Calhoun VD.

Neuroimage. 2018 Oct 15;180(Pt B):619-631. doi: 10.1016/j.neuroimage.2017.09.035. Epub 2017 Sep 20.

PMID:
28939432
3.

Topological Filtering of Dynamic Functional Brain Networks Unfolds Informative Chronnectomics: A Novel Data-Driven Thresholding Scheme Based on Orthogonal Minimal Spanning Trees (OMSTs).

Dimitriadis SI, Salis C, Tarnanas I, Linden DE.

Front Neuroinform. 2017 Apr 26;11:28. doi: 10.3389/fninf.2017.00028. eCollection 2017.

4.

Non-negative discriminative brain functional connectivity for identifying schizophrenia on resting-state fMRI.

Zhu Q, Huang J, Xu X.

Biomed Eng Online. 2018 Mar 13;17(1):32. doi: 10.1186/s12938-018-0464-x.

5.

Extraction of dynamic functional connectivity from brain grey matter and white matter for MCI classification.

Chen X, Zhang H, Zhang L, Shen C, Lee SW, Shen D.

Hum Brain Mapp. 2017 Oct;38(10):5019-5034. doi: 10.1002/hbm.23711. Epub 2017 Jun 30.

6.

Test-retest reliability of dynamic functional connectivity in resting state fMRI.

Zhang C, Baum SA, Adduru VR, Biswal BB, Michael AM.

Neuroimage. 2018 Dec;183:907-918. doi: 10.1016/j.neuroimage.2018.08.021. Epub 2018 Aug 16.

PMID:
30120987
7.

Multivariate graph learning for detecting aberrant connectivity of dynamic brain networks in autism.

Aggarwal P, Gupta A.

Med Image Anal. 2019 May 25;56:11-25. doi: 10.1016/j.media.2019.05.007. [Epub ahead of print]

PMID:
31150935
8.

Assessment of dynamic functional connectivity in resting-state fMRI using the sliding window technique.

Savva AD, Mitsis GD, Matsopoulos GK.

Brain Behav. 2019 Apr;9(4):e01255. doi: 10.1002/brb3.1255. Epub 2019 Mar 18.

9.

Alzheimer Classification Using a Minimum Spanning Tree of High-Order Functional Network on fMRI Dataset.

Guo H, Liu L, Chen J, Xu Y, Jie X.

Front Neurosci. 2017 Dec 1;11:639. doi: 10.3389/fnins.2017.00639. eCollection 2017.

10.

Disentangling dynamic networks: Separated and joint expressions of functional connectivity patterns in time.

Leonardi N, Shirer WR, Greicius MD, Van De Ville D.

Hum Brain Mapp. 2014 Dec;35(12):5984-95. doi: 10.1002/hbm.22599. Epub 2014 Jul 31.

PMID:
25081921
11.

Temporal and spectral characteristics of dynamic functional connectivity between resting-state networks reveal information beyond static connectivity.

Chiang S, Vankov ER, Yeh HJ, Guindani M, Vannucci M, Haneef Z, Stern JM.

PLoS One. 2018 Jan 10;13(1):e0190220. doi: 10.1371/journal.pone.0190220. eCollection 2018.

12.

Hybrid High-order Functional Connectivity Networks Using Resting-state Functional MRI for Mild Cognitive Impairment Diagnosis.

Zhang Y, Zhang H, Chen X, Lee SW, Shen D.

Sci Rep. 2017 Jul 26;7(1):6530. doi: 10.1038/s41598-017-06509-0.

13.

Identifying Dynamic Functional Connectivity Changes in Dementia with Lewy Bodies Based on Product Hidden Markov Models.

Sourty M, Thoraval L, Roquet D, Armspach JP, Foucher J, Blanc F.

Front Comput Neurosci. 2016 Jun 23;10:60. doi: 10.3389/fncom.2016.00060. eCollection 2016.

14.

A Tensor Statistical Model for Quantifying Dynamic Functional Connectivity.

Zhu Y, Zhu X, Kim M, Yan J, Wu G.

Inf Process Med Imaging. 2017 Jun;10265:398-410. doi: 10.1007/978-3-319-59050-9_32. Epub 2017 May 23.

15.

Classification and Prediction of Brain Disorders Using Functional Connectivity: Promising but Challenging.

Du Y, Fu Z, Calhoun VD.

Front Neurosci. 2018 Aug 6;12:525. doi: 10.3389/fnins.2018.00525. eCollection 2018. Review.

16.

Heredity characteristics of schizophrenia shown by dynamic functional connectivity analysis of resting-state functional MRI scans of unaffected siblings.

Su J, Shen H, Zeng LL, Qin J, Liu Z, Hu D.

Neuroreport. 2016 Aug 3;27(11):843-8. doi: 10.1097/WNR.0000000000000622.

PMID:
27295028
18.

Reveal Consistent Spatial-Temporal Patterns from Dynamic Functional Connectivity for Autism Spectrum Disorder Identification.

Zhu Y, Zhu X, Zhang H, Gao W, Shen D, Wu G.

Med Image Comput Comput Assist Interv. 2016 Oct;9900:106-114. doi: 10.1007/978-3-319-46720-7_13. Epub 2016 Oct 2.

19.

Integration of temporal and spatial properties of dynamic connectivity networks for automatic diagnosis of brain disease.

Jie B, Liu M, Shen D.

Med Image Anal. 2018 Jul;47:81-94. doi: 10.1016/j.media.2018.03.013. Epub 2018 Apr 4.

PMID:
29702414
20.

Impact of 36 h of total sleep deprivation on resting-state dynamic functional connectivity.

Xu H, Shen H, Wang L, Zhong Q, Lei Y, Yang L, Zeng LL, Zhou Z, Hu D, Yang Z.

Brain Res. 2018 Jun 1;1688:22-32. doi: 10.1016/j.brainres.2017.11.011. Epub 2017 Nov 22.

PMID:
29174693

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