Altered functional brain networks in amnestic mild cognitive impairment: a resting-state fMRI study
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Amnestic mild cognitive impairment MCI (aMCI) has a high progression to Alzheimer’s disease (AD). Recently, resting-state functional MRI (RS-fMRI) has been increasingly utilized in studying the pathogenesis of aMCI, especially in resting-state networks (RSNs). In the current study, we aimed to explore abnormal RSNs related to memory deficits in aMCI patients compared to the aged-matched healthy control group using RS-fMRI techniques. Firstly, we used ALFF (amplitude of low-frequency fluctuation) method to define the regions of interest (ROIs) which exhibited significant changes in aMCI compared with the control group. Then, we divided these ROIs into different networks in line with prior studies. The aim of this study is to explore the functional connectivity between these ROIs within networks and also to investigate the connectivity between networks. Comparing aMCI to the control group, our results showed that 1) the hippocampus (HIPP) had decreased FC with the medial prefrontal cortex (mPFC) and inferior parietal lobe (IPL), and the mPFC showed increased connectivity to IPL in the default mode network; 2) the thalamus showed decreased FC with the putamen and HIPP, and the HIPP showed increased connectivity to the putamen in the limbic system; 3) the supplementary motor area had decreased FC with the middle temporal gyrus and increased FC with the superior parietal lobe in the sensorimotor network; 4) increased connectivity between the lingual gyrus and middle occipital gyrus in the visual network; and 5) the DMN has reduced inter-network connectivities with the SMN and VN. These findings indicated that functional brain networks involved in cognition such as episodic memory, sensorimotor and visual cognition in aMCI were altered, and provided a new sight in understanding the important subtype of aMCI.
KeywordsDefault mode network Limbic system Sensorimotor network Visual network Functional connectivity Amnestic mild cognitive impairment
This study was funded by the National Natural Science Foundation of China under grant NOs.81071221 and 31271063; the Fundamental Science Research Funds for the Central Universities under grant NO. NSIY131409. Also, all of the authors disclose no conflict of interest for the current study.
Data collection and sharing for this project were funded by the ADNI (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-20012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; F.Hoffmann-La Roche Ltd. and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. Private sector contributions were facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.
Compliance with ethical standards
Conflict of interest
Suping Cai, Tao Chong, Jun Li, Yanlin Peng, Wenyue Shen, Karen M. von Deneen, Liyu Huang and Alzheimer’s Disease Neuroimaging Initiative declare that they have no conflict of interest.
- Allen, E. A., Erhardt, E. B., Damaraju, E., Gruner, W., Segall, J. M., Silva, R. F., Havlicek, M., Rachakonda, S., Fries, J., Kalyanam, R., Michael, A. M., Caprihan, A., Turner, J. A., Eichele, T., Adelsheim, S., Bryan, A. D., Bustillo, J., Clark, V. P., Feldstein Ewing, S. W., Filbey, F., Ford, C. C., Hutchison, K., Jung, R. E., Kiehl, K. A., Kodituwakku, P., Komesu, Y. M., Mayer, A. R., Pearlson, G. D., Phillips, J. P., Sadek, J. R., Stevens, M., Teuscher, U., Thoma, R. J., & Calhoun, V. D. (2011). A baseline for the multivariate comparison of resting-state networks. Frontiers in Systems Neuroscience, 5, 2.PubMedPubMedCentralGoogle Scholar
- Biswal, B., Yetkin, F.Z., Haughton, V.M., Hyde, J.S., 1995. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magnetic Resonance in Medicine: Official Journal of the Society Of Magnetic Resonance in Medicine/Society Of Magnetic Resonance in Medicine 34, 537–541.Google Scholar
- Bokde, A. L., Lopez-Bayo, P., Born, C., Dong, W., Meindl, T., Leinsinger, G., Teipel, S. J., Faltraco, F., Reiser, M., Moller, H. J., & Hampel, H. (2008). Functional abnormalities of the visual processing system in subjects with mild cognitive impairment: an fMRI study. Psychiatry Research, 163, 248–259.CrossRefPubMedGoogle Scholar
- Cabeza, R., Prince, S. E., Daselaar, S. M., Greenberg, D. L., Budde, M., Dolcos, F., LaBar, K. S., & Rubin, D. B. (2004). Brain activity during episodic retrieval of autobiographical and laboratory events: an fMRI study using a novel photo paradigm. Journal of Cognitive Neuroscience, 16, 1583–1594.CrossRefPubMedGoogle Scholar
- Cai, S., Huang, L., Zou, J., Jing, L., Zhai, B., Ji, G., von Deneen, K. M., Ren, J., Ren, A., & Initiative, A.s. D. N. (2014). Changes in thalamic connectivity in the early and late stages of amnestic mild cognitive impairment: A resting-state functional magnetic resonance study from ADNI. PloS One, 10, e0115573–e0115573.Google Scholar
- Cai, S., Chong, T., Zhang, Y., Li, J., von Deneen, K. M., Ren, J., Dong, M., Huang, L., & Initiative, A. s. D. N. (2015). Altered functional connectivity of fusiform gyrus in subjects with amnestic mild cognitive impairment: a resting-state fMRI study. Frontiers in Human Neuroscience, 9, 471.Google Scholar
- De Jong, L., Van der Hiele, K., Veer, I., Houwing, J., Westendorp, R., Bollen, E., De Bruin, P., Middelkoop, H., Van Buchem, M., & Van Der Grond, J. (2008). Strongly reduced volumes of putamen and thalamus in Alzheimer’s disease: an MRI study. Brain, 131, 3277–3285.CrossRefPubMedPubMedCentralGoogle Scholar
- de Leon, M. J., Convit, A., Wolf, O. T., Tarshish, C. Y., DeSanti, S., Rusinek, H., Tsui, W., Kandil, E., Scherer, A. J., Roche, A., Imossi, A., Thorn, E., Bobinski, M., Caraos, C., Lesbre, P., Schlyer, D., Poirier, J., Reisberg, B., & Fowler, J. (2001). Prediction of cognitive decline in normal elderly subjects with 2-[(18)F]fluoro-2-deoxy-D-glucose/poitron-emission tomography (FDG/PET). Proceedings of the National Academy of Sciences of the United States of America, 98, 10966–10971.CrossRefPubMedPubMedCentralGoogle Scholar
- Dunn, C. J., Duffy, S. L., Hickie, I. B., Lagopoulos, J., Lewis, S. J., Naismith, S. L., & Shine, J. M. (2014). Deficits in episodic memory retrieval reveal impaired default mode network connectivity in amnestic mild cognitive impairment. NeuroImage: Clinical, 4, 473–480.Google Scholar
- Emre, M. (2003). What causes mental dysfunction in Parkinson’s disease? Movement disorders, 18, 63–71.Google Scholar
- Fair, D. A., Cohen, A. L., Dosenbach, N. U., Church, J. A., Miezin, F. M., Barch, D. M., Raichle, M. E., Petersen, S. E., & Schlaggar, B. L. (2008). The maturing architecture of the brain’s default network. Proceedings of the National Academy of Sciences of the United States of America, 105, 4028–4032.CrossRefPubMedPubMedCentralGoogle Scholar
- Gusnard, D. A., Akbudak, E., Shulman, G. L., & Raichle, M. E. (2001). Medial prefrontal cortex and self-referential mental activity: relation to a default mode of brain function. Proceedings of the National Academy of Sciences of the United States of America, 98, 4259–4264.CrossRefPubMedPubMedCentralGoogle Scholar
- Mazoyer, B., Zago, L., Mellet, E., Bricogne, S., Etard, O., Houde, O., Crivello, F., Joliot, M., Petit, L., & Tzourio-Mazoyer, N. (2001). Cortical networks for working memory and executive functions sustain the conscious resting state in man. Brain Research Bulletin, 54, 287–298.CrossRefPubMedGoogle Scholar
- Satterthwaite, T. D., Wolf, D. H., Loughead, J., Ruparel, K., Elliott, M. A., Hakonarson, H., Gur, R. C., & Gur, R. E. (2012). Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth. NeuroImage, 60, 623–632.CrossRefPubMedPubMedCentralGoogle Scholar
- Shulman, G. L., Corbetta, M., Buckner, R. L., Fiez, J. A., Miezin, F. M., Raichle, M. E., & Petersen, S. E. (1997a). Common blood flow changes across visual tasks: I. Increases in Subcortical Structures and Cerebellum but not in Nonvisual Cortex. Journal of Cognitive Neuroscience, 9, 624–647.CrossRefPubMedGoogle Scholar
- Truchot, L., Costes, N., Zimmer, L., Laurent, B., Le Bars, D., Thomas-Anterion, C., Mercier, B., Hermier, M., Vighetto, A., & Krolak-Salmon, P. (2008). A distinct [18 F] MPPF PET profile in amnestic mild cognitive impairment compared to mild Alzheimer’s disease. NeuroImage, 40, 1251–1256.CrossRefPubMedGoogle Scholar
- Wang, P., Zhou, B., Yao, H., Zhan, Y., Zhang, Z., Cui, Y., Xu, K., Ma, J., Wang, L., & An, N. (2015). Aberrant intra-and inter-network connectivity architectures in Alzheimer’s disease and mild cognitive impairment. Scientific Reports, 5, 14824.Google Scholar
- Zarei, M., Patenaude, B., Damoiseaux, J., Morgese, C., Smith, S., Matthews, P. M., Barkhof, F., Rombouts, S., Sanz-Arigita, E., & Jenkinson, M. (2010). Combining shape and connectivity analysis: an MRI study of thalamic degeneration in Alzheimer’s disease. NeuroImage, 49, 1–8.CrossRefPubMedGoogle Scholar