Browse > Article
http://dx.doi.org/10.9717/kmms.2020.24.5.684

Combined Analysis Using Functional Connectivity of Default Mode Network Based on Independent Component Analysis of Resting State fMRI and Structural Connectivity Using Diffusion Tensor Imaging Tractography  

Choi, Hyejeong (Dept. of Medical & Biological Eng., Graduate School, Kyungpook National University)
Chang, Yongmin (Dept. of Molecular Medicine, School of Medicine, Kyungpook National University and Dept. of Radiology, Kyungpook National University Hospital)
Publication Information
Journal of Korea Multimedia Society / v.24, no.5, 2021 , pp. 684-694 More about this Journal
Abstract
Resting-state Functional Magnetic Resonance Imaging(fMRI) data detects the temporal correlations in Blood Oxygen Level Dependent(BOLD) signal and these temporal correlations are regarded to reflect intrinsic cortical connectivity, which is deactivated during attention demanding, non-self referential tasks, called Default Mode Network(DMN). The relationship between fMRI and anatomical connectivity has not been studied in detail, however, the preceded studies have tried to clarify this relationship using Diffusion Tensor Imaging(DTI) and fMRI. These studies use method that fMRI data assists DTI data or vice versa and it is used as guider to perform DTI tractography on the brain image. In this study, we hypothesized that functional connectivity in resting state would reflect anatomical connectivity of DMN and the combined images include information of fMRI and DTI showed visible connection between brain regions related in DMN. In the previous study, functional connectivity was determined by subjective region of interest method. However, in this study, functional connectivity was determined by objective and advanced method through Independent Component Analysis. There was a stronger connection between Posterior Congulate Cortex(PCC) and PHG(Parahippocampa Gyrus) than Anterior Cingulate Cortex(ACC) and PCC. This technique might be used in several clinical field and will be the basis for future studies related to aging and the brain diseases, which are needed to be translated not only functional connectivity, but structural connectivity.
Keywords
Diffusion Tensor Imaging; Tractography; Functional Magnetic Resonance Imaging; Default Mode Network; Independet Component Analysis;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 A.C. Julio and J.N. Peter, "Diffusion Tensor Imaging in Alzheimer's Disease: Insights into the Limbic-Diencephalic Network and Methodological Considerations," Frontiers in Aging Neuroscience, Vol. 6, pp. 1-21, 2014.   DOI
2 R. Sperling, "The Potential of Functional MRI as a Biomarker in Early Alzheimer's Disease," Neurobiology and Aging, Vol. 32, pp. 1-11, 2011.   DOI
3 B. bIRUR, N.V. Kraguljac, R.C. Shelton, and A.C. Lahti, "Brain Structure, Function, and Neurochemistry in Schizophrenia and Bipolar Disorder: A Systemci Review of the Magnetic Resonance Neuroimaging Literature," Schizophrenia, Vol. 15, pp. 1-15, 2017.
4 S. Li, N. Hu, W. Zhang, B. Tao, J. Dai, G. Yao et al., "Dysconnectivity of Multiple Brain Networks in Schizophrenia: A Meta-Analysis of Resting-State Functional Connectivity," Frontiers in Psychiatry, Vol 10, pp. 1-11, 2019.   DOI
5 L.C. Rachel, R. Elliott, and W.R. Peter, "fMRI and Cognitive Dysfunction in Schizophrenia," Trends in Cognitive Science, Vol. 5, No. 2, 2001.
6 D. Zhu, T. Zhang, X. Jiang, X. Hu, .H. Chen, N. Yang et al., "Fusing DTI and fMRI data: A survey of methods and applications," Neuroimage, Vol. 102, pp. 184-191, 2014.   DOI
7 J.S Damoiseaux and M.D. Greicius, "Greather than the sum of its parts: a review of studies combining structural connectivity and resting- state functional connectivity," Brain Structure and Function, Vol. 213, pp. 525-553, 2009.   DOI
8 W. Liao, Z. Zhang, Z. Pan, D. Mantini, J. Ding, X. Duan et al., "Default Mode Network Abnormalities in Mesial Temporal Lobe Epilepsy: A Study Combining fMRI and DTI," Human Brain Mapping, Vol. 32, pp. 883-895, 2011.   DOI
9 C.Y. Tang, E. Eaves, K.D. Connor, L. Ho, E. Leung, and E. Wong, "Diffuse Disconnectivity in TBI: A Resting State fMRI and DTI Study," Translational Neuroscience, Vol. 3 No. 1, pp. 9-14, 2012.   DOI
10 M. Ystad, E. Hodneland, S. Adolfsdottir, J Haasz, A.J. Lundervold, T. Eichele et al., "Cortico-striatla Connectivity and Cognition in Normal Aging: A Combined DTI and Resting-State fMRI study," Neuroimage, Vol. 55, pp. 24-31, 2011.   DOI
11 W.G. Jeon, Y.S. Izmantoko, J.H. Son, and H.K. Choi, "Hippocampus Volume Measurement for the determination of MCI," Journal of Korea Multimedia Society, Vol. 15, No. 12, pp. 1449-1455, 2012.   DOI
12 F.P. Laia, .G.O. Joan, and P.C. Maribel, "Mild Cognitive Impairment and fMRI Studies of Brain Functional Connectivity: the State of the Art," Frontiers in Psychology, Vol. 6, pp. 1-18, 2015.   DOI
13 G.J. Ruten and N.F. Ramsey, "The Role of Fucntional Magnetic Resonance Imaging in Brain Surgery," Neurosurgery Focus, Vol. 28, pp. 1-13, 2009.
14 A. Crofts, M.E. Kelly, and C.L. Gibson, "Imaging Functional Recovery Following Ischemic Stroke: Clnical and Preclinical fMRI Studies," Journal of Neuroimaging, Vol. 30, pp. 5-14, 2020.   DOI
15 C.C. Maria, .C.M. Cristina, P.C. Maribel. and G.O. Joan, "Using fMRI to Access Brain Activity in Peopel With Down Syndrome: A Systemic Review," Frontiers in Human Neuroscience, Vol. 14, pp. 1-11, 2020.   DOI
16 N. Madusanka, Y.Y. Choi, K.Y. Choi, K.H. Lee, and H.K. Choi, "Hippocampus Segmentation and Classification in Alzheimer's Disease and Mild Cognitive Impairment Applied on MR Images," Journal of Korea Multimedia Society, Vol. 20, No. 2, pp. 205-215, 2017.   DOI
17 S.D. Jessica, "Resting-State fMRI as a Biomarker for Alzheimer's Disease?," Alzheimer's Research and Therapy, Vol. 4, pp. 1-2, 2012.   DOI
18 G.T. Stebbins and C.M. Murpphy, "Diffusion Tensor Imaging in Alzheimer's Disease and Mild Cognitive Impairment," Behavioural Neurology, Vol. 21, pp. 39-49, 2009.   DOI
19 K. Oishi, M.M. Michelle, M. Albert, G.L. Constantine, and S. Mori, "DTI Analysis and Clinical Applications in Alzheimer's Disease," Journal of Alzheimers Disease, Vol. 26, pp. 287-296, 2011.   DOI
20 D.B. Parenta, E.L. Gasparetto, L.C. Cruz, R.C. Domingues, A.C. Baptista, A.C. Carvelho et al., "Potential Role of Diffusion Tensor MRI in the Differnetial Diagnosis of Mild Cognitive Impairment and Alzheimer's Disease," American Journal of Neuroradiology, Vol. 190, 1369-1374, 2008.
21 L.T. Wsetlye, K.B. Walhovd, A.M. Dale, A. Bjornerud, P.D. Tonnessen, A. Engvig, et al. "Life-Span Changes of the Human Brain White Matter: Diffusion Tensor Imaging (DTI) and Volumetry," Cerebral Cortex, Vol. 20, pp. 2055-2068, 2009.   DOI
22 J.W. Seok, "Ensemble Learning for Underwater Target Classification," Journal of Korea Multimedia Society, Vol. 18, No. 11, pp. 1261-1267, 2015.   DOI
23 Medical Image Navigation and Research Tool by MedINRIA 1.9. http://www.sop.inria.fr/asclepios/software/MedINRIA (accesed April 1, 2021).
24 Graph Pad Prism 5.0v, https://www.graphpad.com/scientific-software/prism/ (accesed April 1, 2021).
25 xjView. http://www.alivelearn.net/xjview8/ (accesed April 1, 2021).
26 K. Lee, "Clinical Application of Functional MRI," Korean Neurological Association, Vol. 19. No. 5, pp. 441-446, 2001.
27 L. Sun, Q. Cao, X. Long, M. Sui, X. Cao, and C. Zhu, "Abnormal Functional Connectivity between the Anterior Cingulate and the Default Mode Network in Drug-naive Boys with Attention Deficit Hyperactivity Disorder," Psychiatry Research: NeuroImaging, Vol. 201, pp. 120-127, 2012.   DOI
28 P. Fransson and G. Marrelec, "The Precuneus/Posterior Cingulate Cortex Plays a Pivotal Role in the Default Mode Network: Evidence from a Partial Correlation Network Analysis," Neuroimage, Vol. 42, pp-1178-1184, 2008.   DOI
29 R. Leech and D.J. Sharp, "The Role of the Posterior Cingulate Cortex in Cognition and Disease," A Journal of Neurology: Brain, Vol. 37, pp. 12-32, 2014.
30 A.M. Ward, A.P. Schultz, W. Huijbers, K.R. Dijk, T. Hedden, and R.A. Sperling, "The Parahippocampal Gyrus Links the Default Mode Network with the Medial Temporal Lobe Memory System," Human Brain Mappling, Vol. 35, pp. 1061-1073, 2014.   DOI
31 K. Koch, G. Wagner, R. Dahnke, C. Schachtzabel, D. Gullmar, and J.R. Reichenbach, "Structure-Function Relationship in the Context of Reinforcement-Related Learning: A combined Diffusion Tensor Imaging-Functional Magnetic Resonance Imaging Study," Neuroscience, Vol. 168, pp. 190-199, 2010.   DOI
32 P. Fransson, "How Default is the Default Mode of Brain Function? Further Evidence from Intrinsic BOLD Signal Fluctuations," Neuropsychologia, Vol. 44 pp. 2836-2845, 2006.   DOI
33 J.H. Jang, W.H. Jung, D. Kang, M.S. Byun, S.J. Kwon C.H. Choi et al., "Increased Default Mode Network Connectivity Associated with Meditation," Neurosceince Letters, Vol. 487, pp. 358-362, 2011.   DOI
34 M.D. Grecius, K. Supekar, V. Menon, and R.F. Dougherty, "Resting-State Functional Connectivity Reflects Structural Connectivity in the Default Mode Network," Cerebral Cortex, Vol. 19, pp, 72-78, 2009.   DOI
35 X.W. Song, Z.Y. Dong, X.Y. Long, S.F. Li, X.N. Zuo, C.Z. Zhu et al., "REST: A Toolkit for Resting-State FUnctional Magnetic Resonance Imaging Data Processing," Plosone, Vol. 6. No 9, pp. 1-12, 2011.
36 A. Hyvarinen and E. Oja, "Independent Component Analysis: Algorithms and Applications," Neural Network, Vol. 13, pp. 411-430, 2000.   DOI
37 D. Langlois, S. Chartier, and D. Gosselin, "An Introduction to Indepdent Component Analysis: InfoMax and FastICA algorigthms," Tutorials in Quantitative Methods for Psychology, Vol. 6, No. 1, pp. 31-38, 2010.   DOI
38 M. Guye, J.M. Parker, M. Symms, P. Boulby, A.M. Claudia, and S.H. Afraim, "Combined Functional MRI and Tractography to Demonstrate the Connectivity of the Human Primary Motor Cortex in vivo," Neuroimage, Vol. 19, pp. 1349-1360, 2003.   DOI
39 C. Rosazza, L. Minati, F. Ghielmetti, M.L. Mandelli, and M.G. Bruzzone, "Functional Connectivity During Resting-State Functional MR Imaging: Study of the Correspondence between Independent Component Analysis and Region-of-Interest Based Methods," American Journal of Neruoradiology, Vol. 33, pp. 180-187, 2012.   DOI
40 D.J. Madden, J. Spaniol, W.L. Whiting, B. Bucur, J.M. Provenzale, R. Cabeza et al. "Adult Age Differences in the Functional Neuroanatomy of Visual Attention: A Combined fMRI and DTI Study," Neurobiology of Aging, Vol. 28, pp. 459-476, 2007.   DOI
41 M.H. Lee, C.D. Smyser, and J.S. Shimony, "Resting-State fMRI: A Review of Methods and Clinical Applications," American Journal of Neuroradiology, Vol. 3, pp. 1866-1872, 2013.
42 J. Xu, S. Zhang, V.D. Calhoun, J. Monteross, R.L. Chaingshan, P.D. Worhunsky, et al. "Task-realted concurrent but opposite modulations of overlapping functional networks as revealed by spatial ICA," NeuroImage, Vol. 79, pp. 62-71, 2013.   DOI
43 Y.H. Cho and S.J. Min, "Performance Improvement of Independent Component Analysis by Adaptive Learning Parameters," Journal of Korea Multimedia Society, pp. 210-213, 2003.
44 Y.H. Cho, "Face Recognition Using First Momemt of Image and Eigenvectors," Journal of Korea Multimedia Society, Vol. 9, No. 1, pp. 33-40, 2006.
45 D.L. Bogomolny, N.M. Petrovich, B.L. Hou, K.K. Peck, J.J. Kim, and A.I. Holodny, "Functional MRI in the Brain Tumor Patient," Magnetic Resonance Imaging, Vol. 15, pp. 325-335, 2004.   DOI
46 P.J. Broser, S. Groeschel, T.K. Hauser, K. Lidzba, and M. Wilke, "Functional MRI-Guided Probabilistic Tractogarphy of Cortico-Cortical and Cortico-Subcortical Language Networks in Children," Neuroimage, Vol. 63, pp. 1561-1570, 2012.   DOI
47 S. Lim, C.E. Han, P.J. Uhlhaas, M. Kaiser, "Prefrontal Detachment During Human Brain Development: Age- and Sex-Specific Structural Connectivity in Diffusion Tensor Imaging (DTI) Data," Cerebal Cortex, Vol. 25, pp. 1477-1489, 2015.   DOI
48 C.K. Tamnes, D.R. Roalf, A.L. Goddings, and C. Lebel, "Diffusion MRI of White Matter Microstructure Development in Childhood and Adolescence: Methods, Challenges and Progress," Developmental Cognitive Neuro- science, Vol. 33, pp. 161-175, 2018.   DOI
49 P. Skudlarski, K. Jagannathan, K. Anderson, M.C Stevenes, V.D. Galhoun, and B.A Skudiarska, "Brain Connectivity is Not Only Lower But Different in Schizhophrenia: A Combined Anatomical and Fucntional Approach," Biology Psychiatry, Vol. 68, No. 1 pp. 61-69, 2010.   DOI
50 J. Upadhyay, M. Ducros, T.A. Knaus, K.A. Lindgren, A. Silver, and T.F. Halen, "Function and Connectivity in Human Primary Auditory Cortex: A Combined fMRI and DTI Study at 3 Tesla," Cerebal Cortex, Vol. 17, pp. 2420-2432, 2007.   DOI
51 V. Schopf, C. Windischberger, C.H. Kasess, R. Lanzenberger, and E. Moser, "Group ICA of Resting-State Data: A Comparison," Magnetic Resonance Material and Physics, Vol. 23, pp. 317-325, 2010.   DOI
52 Statistical Parametric Mapping Software (SPM5). http://www.fil.ion.ucl.ac.kr/spm/ (accessed April 1, 2021).
53 GIFT v 3.0a, Group ICA/IVA, Mialab. http://mialab.mrn.org/software/gift/index.contract (accessed April 1, 2021).
54 P.M. Matthews and P. Jezzard, "Functional Magnetic Resonance Imaging," Neuroscience for Neurologists, Vol. 75, pp. 6-12, 2004.
55 S.M. Smith, D. Vidaurre, C.F. Beckmann, M.F. Glasser, M. Jenkinson, K.L. Miller et al., "Functional Connectomics from Resting-state fMRI," Trends in Cognitive Sciences, Vol. 17, No. 12, pp. 666-682, 2013.   DOI
56 M.D. Greicius, B.H. Flores, V. Menon, G.H. Glover, H.B. Sovason, H.K. Kenna, et al., "Resting-State Functional Connectivity in Major Depression: Abnormally Increased Contributions from Subgenual Cingulate Cortex and Thalamus," Biology Psychiatry, Vol. 62, pp. 429-437, 2007.   DOI