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Altered Effective Connectivity of the Default Mode Network in Resting-State Amnestic Type Mild Cognitive Impairment

Published online by Cambridge University Press:  21 February 2013

Hao Yan ,
Yumei Zhang ,
Hongyan Chen ,
Yonghui Wang  and
Yijun Liu
Hao Yan
Affiliation:
School of Psychology, Shaanxi Normal University, Xi'an, China Department of Linguistics, Xidian University, Xi'an, China
Yumei Zhang
Affiliation:
Neurology department Beijing Tiantan Hospital, Capital Medical University, Beijing, China
Hongyan Chen
Affiliation:
Radiology department Beijing Tiantan Hospital, Capital Medical University, Beijing, China
Yonghui Wang*
Affiliation:
School of Psychology, Shaanxi Normal University, Xi'an, China
Yijun Liu
Affiliation:
Departments of Psychiatry and Neuroscience, McKnight Brain Institute, University of Florida, Gainesville, Florida
*
Correspondence and reprint requests to: Yonghui Wang, School of Psychology, Shaanxi Normal University, Xi'an, 710062, China. E-mail: wyonghui@snnu.edu.cn
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Abstract

Amnestic mild cognitive impairment (aMCI) is the transitional, heterogeneous continuum from normal elderly to Alzheimer's disease (AD). Previous studies have shown that brain functional activity in the default mode network (DMN) is impaired in aMCI patients with saliently cognitive and memory decline. However, the effective connectivity among the spatially isolated, but functionally related areas within the DMN in aMCI patients remains largely unknown. The present study examined dysfunctional connectivity of the DMN by combining an independent component analysis (ICA) approach with multivariate Granger causality analysis (mGCA) in 18 aMCI patients and 18 age-matched cognitively normal elderly. Results from mGCA showed decreased effective connectivity occurred among the middle temporal gyrus (MTG), hippocampus (HC) and fusiform gyrus (FG), as well as between the precuneus/posterior cingulate cortex (PreCN/PCC) and HC in patients with aMCI. Such an impaired connectivity was also correlated with patients’ cognitive performance of the auditory verbal learning. Moreover, enhanced effective connectivity within frontal cortex emerged, which may maintain memory functions after attenuated connections within DMN activity. These findings may elucidate the dysfunctional processes in brain networks of aMCI patients, highlighting the importance of connectivity changes in the pathophysiology of aMCI. (JINS, 2013, 19, 1–10)

Keywords

Amnestic mild cognitive impairmentDefault mode networkEffective connectivityIndependent component analysisMultivariate Granger causality analysisResting fMRI
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 19 , Issue 4 , April 2013 , pp. 400 - 409
Copyright
Copyright © The International Neuropsychological Society 2013

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Footnotes

Hao Yan and Yumei Zhang contributed equally to this work.

References

Anderson, N.D., Iidaka, T., Cabeza, R., Kapur, S., McIntosh, A.R., Craik, F.I. (2000). The effects of divided attention on encoding- and retrieval-related brain activity: A PET study of younger and older adults. Journal of Cogntive Neuroscience, 12, 775–792.CrossRefGoogle ScholarPubMed
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, 34, 537–541.CrossRefGoogle ScholarPubMed
Blennow, K., de Leon, M.J., Zetterberg, H. (2006). Alzheimer's disease. Lancet, 368, 387–403.CrossRefGoogle ScholarPubMed
Blinowska, K.J., Kus, R., Kaminski, M. (2004). Granger causality and information flow in multivariate processes. Physical Review E, 70, 50902–50906.CrossRefGoogle ScholarPubMed
Bookheimer, S.Y., Strojwas, M.H., Cohen, M.S., Saunders, A.M., Pericak-Vance, M.A., Mazziotta, J.C., Small, G.W. (2000). Patterns of brain activation in people at risk for Alzheimer's disease. The New England Journal of Medicine, 343, 450–456.CrossRefGoogle ScholarPubMed
Braak, H., Braak, E. (1991). Neuropathological stageing of Alzheimer-related changes. Acta Neuropathologica, 82, 239–259.CrossRefGoogle ScholarPubMed
Buchhave, P., Stomrud, E., Warkentin, S., Blennow, K., Minthon, L. (2008). Cube copying test in combination with rCBF or CSF A beta 42 predicts development of Alzheimer's disease. Dementia and Geriatric Cognitive Disorders, 25, 544–552.CrossRefGoogle ScholarPubMed
Buckner, R.L. (2004). Memory and executive function in aging and AD: Multiple factors that cause decline and reserve factors that compensate. Neuron, 44, 195–208.CrossRefGoogle Scholar
Cabeza, R., Anderson, N.D., Locantore, J.K., McIntosh, A.R. (2002). Aging gracefully: Compensatory brain activity in high-performing older adults. Neuroimage, 17, 1394–1402.CrossRefGoogle ScholarPubMed
Cordes, D., Haughton, V.M., Arfanakis, K., Carew, J.D., Turski, P.A., Moritz, C.H., Meyerand, M.E. (2001). Frequencies contributing to functional connectivity in the cerebral cortex in “resting-state” data. AJNR American Journal of Neuroradiology, 22, 1326–1333.Google ScholarPubMed
De Luca, M., Beckmann, C.F., De Stefano, N., Matthews, P.M., Smith, S.M. (2006). fMRI resting state networks define distinct modes of long-distance interactions in the human brain. Neuroimage, 29, 1359–1367.CrossRefGoogle ScholarPubMed
Demirci, O., Stevens, M.C., Andreasen, N.C., Michael, A., Liu, J., White, T., Calhoun, V.D. (2009). Investigation of relationships between fMRI brain networks in the spectral domain using ICA and Granger causality reveals distinct differences between schizophrenia patients and healthy controls. Neuroimage, 46, 419–431.CrossRefGoogle ScholarPubMed
Deshpande, G., LaConte, S., James, G.A., Peltier, S., Hu, X. (2009). Multivariate Granger causality analysis of fMRI data. Human Brain Mapping, 30, 1361–1373.CrossRefGoogle ScholarPubMed
Dhamala, M., Rangarajan, G., Ding, M. (2008). Analyzing information flow in brain networks with nonparametric Granger causality. Neuroimage, 41, 354–362.CrossRefGoogle ScholarPubMed
Ding, M., Chen, Y., Bressler, S.L. (2006). Granger causality: Basic theory and application to neuroscience. In B. Schelter, M. Winterhalder, & J. Timmer (Eds.), Handbook of time series analysis. Weinheim: Wiley-VCH.Google Scholar
Fox, M., Snyder, A., Vincent, J., Corbetta, M., Van Essen, D., Raichle, M. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences of the United States of America, 102, 9673–9678.CrossRefGoogle ScholarPubMed
Gould, R.L., Arroyo, B., Brown, R.G., Owen, A.M., Bullmore, E.T., Howard, R.J. (2006). Brain mechanisms of successful compensation during learning in Alzheimer disease. Neurology, 67, 1011–1017.CrossRefGoogle ScholarPubMed
Grady, C.L., Bernstein, L.J., Beig, S., Siegenthaler, A.L. (2002). The effects of encoding task on age-related differences in the functional neuroanatomy of face memory. Psychology and Aging, 17, 7–23.CrossRefGoogle ScholarPubMed
Granger, C.W.J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37, 424–438.CrossRefGoogle Scholar
Greicius, M.D., Krasnow, B., Reiss, A.L., Menon, V. (2003). Functional connectivity in the resting brain: A network analysis of the default mode hypothesis. Proceedings of the National Academy of Sciences of the United States of America, 100, 253–258.CrossRefGoogle Scholar
Greicius, M.D., Srivastava, G., Reiss, A.L., Menon, V. (2004). Default-mode network activity distinguishes Alzheimer's disease from healthy aging: Evidence from functional MRI. Proceedings of the National Academy of Sciences of the United States of America, 101, 4637–4642.CrossRefGoogle ScholarPubMed
Hamalainen, A., Pihlajamaki, M., Tanila, H., Hanninen, T., Niskanen, E., Tervo, S., Soininen, H. (2007). Increased fMRI responses during encoding in mild cognitive impairment. Neurobiology of Aging, 28, 1889–1903.CrossRefGoogle ScholarPubMed
Harrison, B.J., Pujol, J., López-Solà, M., Hernández-Ribas, R., Deus, J., Ortiz, H., Cardoner, N. (2008). Consistency and functional specialization in the default mode brain network. Proceedings of the National Academy of Sciences of the United States of America, 105, 9781–9786.CrossRefGoogle ScholarPubMed
He, Y., Wang, L., Zang, Y., Tian, L., Zhang, X., Li, K., Jiang, T. (2007). Regional coherence changes in the early stages of Alzheimer's disease: A combined structural and resting-state functional MRI study. Neuroimage, 35, 488–500.CrossRefGoogle ScholarPubMed
Jiao, Q., Lu, G., Zhang, Z., Zhong, Y., Wang, Z., Guo, Y., Liu, Y. (2011). Granger causal influence predicts BOLD activity levels in the default mode network. Human Brain Mapping, 32, 154–161.CrossRefGoogle ScholarPubMed
Kaminski, M., Ding, M.Z., Truccolo, W., Bressler, S. (2001). Evaluating causal relations in neural systems: Granger causality, directed transfer function and statistical assessment of significance. Biological Cybernetics, 85, 145–157.Google ScholarPubMed
Korzeniewska, A., Manczak, M., Kaminski, M., Blinowska, K.J., Kasicki, S. (2003). Determination of information flow direction between brain structures by a modified directed transfer function method (dDTF). Journal of Neuroscience Methods, 125, 195–207.CrossRefGoogle ScholarPubMed
Kus, R., Kaminski, M., Blinowska, K.J. (2004). Determination of EEG activity propagation: Pair-wise versus multichannel estimate. IEEE Transaction Biomedical Engineering, 51, 1501–1510.CrossRefGoogle ScholarPubMed
Liao, W., Mantini, D., Zhang, Z., Pan, Z., Ding, J., Gong, Q., Chen, H. (2009). Evaluating the effective connectivity of resting state networks using conditional Granger causality. Biological Cybernetics, 102, 57–69.CrossRefGoogle ScholarPubMed
Logan, J.M., Sanders, A.L., Snyder, A.Z., Morris, J.C., Buckner, R.L. (2002). Under-recruitment and nonselective recruitment: Dissociable neural mechanisms associated with aging. Neuron, 33, 827–840.CrossRefGoogle ScholarPubMed
Mantini, D., Perrucci, M.G., Del Gratta, C., Romani, G.L., Corbetta, M. (2007). Electrophysiological signatures of resting state networks in the human brain. Proceedings of the National Academy of Sciences of the United States of America, 104, 13170–13175.CrossRefGoogle ScholarPubMed
McCarthy, G., Puce, A., Gore, J.C., Allison, T. (1997). Face-specific processing in the human fusiform gyrus. Journal of Cognitive Neuroscience, 9, 605–610.CrossRefGoogle ScholarPubMed
Minoshima, S., Giordani, B., Berent, S., Frey, K.A., Foster, N.L., Kuhl, D.E. (1997). Metabolic reduction in the posterior cingulate cortex in very early Alzheimer's disease. Annals of Neurology, 42, 85–94.CrossRefGoogle ScholarPubMed
Pariente, J., Cole, S., Henson, R., Clare, L., Kennedy, A., Rossor, M., Frackowiak, R.S. (2005). Alzheimer's patients engage an alternative network during a memory task. Annals of Neurology, 58, 870–879.CrossRefGoogle ScholarPubMed
Petersen, R.C., Doody, R., Kurz, A., Mohs, R.C., Morris, J.C., Rabins, P.V., Winblad, B. (2001). Current concepts in mild cognitive impairment. Archives of Neurology, 58, 1985–1992.CrossRefGoogle ScholarPubMed
Petersen, R.C., Smith, G.E., Waring, S.C., Ivnik, R.J., Tangalos, E.G., Kokmen, E. (1999). Mild cognitive impairment: Clinical characterization and outcome. Archives of Neurology, 56, 303–308.CrossRefGoogle ScholarPubMed
Preston, A.R., Wagner, A.D. (2007). The medial temporal lobe and memory. Neurobiology of Learning and Memory, 2, 305–337.CrossRefGoogle Scholar
Price, C.J., Friston, K.J. (1997). Cognitive conjunction: A new approach to brain activation experiments. Neuroimage, 5, 261–270.CrossRefGoogle ScholarPubMed
Raichle, M.E., MacLeod, A.M., Snyder, A.Z., Powers, W.J., Gusnard, D.A., Shulman, G.L. (2001). A default mode of brain function. Proceedings of the National Academy of Sciences of the United States of America, 98, 676–682.CrossRefGoogle ScholarPubMed
Rombouts, S.A., Barkhof, F., Goekoop, R., Stam, C.J., Scheltens, P. (2005). Altered resting state networks in mild cognitive impairment and mild Alzheimer's disease: An fMRI study. Human Brain Mapping, 26, 231–239.CrossRefGoogle ScholarPubMed
Scholvinck, M.L., Maier, A., Ye, F.Q., Duyn, J.H., Leopold, D.A. (2010). Neural basis of global resting-state fMRI activity. Proceedings of the National Academy of Sciences of the United States of America, 107, 10238–10243.CrossRefGoogle ScholarPubMed
Seth, A.K. (2010). A MATLAB toolbox for Granger causal connectivity analysis. Journal of Neuroscience Methods, 186, 262–273.CrossRefGoogle ScholarPubMed
Shulman, G.L., Fiez, J.A., Corbetta, M.A.L., Miezin, F.M., Raichle, M.E., Petersen, S.E. (1997). Common blood flow changes across visual tasks: II. Decreases in cerebral cortex. J. Cognitive Neuroscience, 9, 648–663.CrossRefGoogle ScholarPubMed
Shulman, K.I. (2000). Clock-drawing: Is it the ideal cognitive screening test? International Journal of Geriatric Psychiatry, 15, 548–561.3.0.CO;2-U>CrossRefGoogle ScholarPubMed
Sorg, C., Riedl, V., Muhlau, M., Calhoun, V.D., Eichele, T., Laer, L., Wohlschlager, A.M. (2007). Selective changes of resting-state networks in individuals at risk for Alzheimer's disease. Proceedings of the National Academy of Sciences of the United States of America, 104, 18760–18765.CrossRefGoogle ScholarPubMed
Theiler, J., Eubank, A., Galdrikian, B., Farmer, D. (1992). Testing for nonlinearity in time series: The method of surrogate data. Physica D, 58, 77–94.CrossRefGoogle Scholar
Vakil, E., Blachstein, H. (1997). Rey AVLT: Developmental norms for adults and the sensitivity of different memory measures to age. Clinical Neuropsychologist, 11, 356–369.CrossRefGoogle Scholar
Van Dijk, K.R.A., Hedden, T., Venkataraman, A., Evans, K.C., Lazar, S.W., Buckner, R.L. (2010). Intrinsic functional connectivity as a tool for human connectomics: Theory, properties, and optimization. Journal of Neurophysiology, 103, 297–321.CrossRefGoogle ScholarPubMed
Wang, L., Zang, Y., He, Y., Liang, M., Zhang, X., Tian, L., Li, K. (2006). Changes in hippocampal connectivity in the early stages of Alzheimer's disease: Evidence from resting state fMRI. Neuroimage, 31, 496–504.CrossRefGoogle ScholarPubMed