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Functional Connectivity Variations in Mild Cognitive Impairment: Associations with Cognitive Function

Published online by Cambridge University Press:  18 October 2011

S. Duke Han ,
Konstantinos Arfanakis ,
Debra A. Fleischman ,
Sue E. Leurgans ,
Elizabeth R. Tuminello ,
Emily C. Edmonds  and
David A. Bennett
S. Duke Han*
Affiliation:
Department of Behavioral Sciences, Rush University Medical Center, Chicago, Illinois
Konstantinos Arfanakis
Affiliation:
Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, Illinois Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois Department of Radiology, Rush University Medical Center, Chicago, Illinois
Debra A. Fleischman
Affiliation:
Department of Behavioral Sciences, Rush University Medical Center, Chicago, Illinois Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois
Sue E. Leurgans
Affiliation:
Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois
Elizabeth R. Tuminello
Affiliation:
Department of Psychology, Loyola University Chicago, Chicago, Illinois
Emily C. Edmonds
Affiliation:
Department of Behavioral Sciences, Rush University Medical Center, Chicago, Illinois
David A. Bennett
Affiliation:
Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois
*
Correspondence and reprint requests to: S. Duke Han, Department of Behavioral Sciences, 1645 W. Jackson Blvd. Ste. 400, Chicago, IL 60612. E-mail: duke_han@rush.edu
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Abstract

Participants with mild cognitive impairment (MCI) have a higher likelihood of developing Alzheimer's disease (AD) compared to those without MCI, and functional magnetic resonance neuroimaging (fMRI) used with MCI participants may prove to be an important tool in identifying early biomarkers for AD. We tested the hypothesis that functional connectivity differences exist between older adults with and without MCI using resting-state fMRI. Data were collected on over 200 participants of the Rush Memory and Aging Project, a community-based, clinical-pathological cohort study of aging. From the cohort, 40 participants were identified as having MCI, and were compared to 40 demographically matched participants without cognitive impairment. MCI participants showed lesser functional connectivity between the posterior cingulate cortex and right and left orbital frontal, right middle frontal, left putamen, right caudate, left superior temporal, and right posterior cingulate regions; and greater connectivity with right inferior frontal, left fusiform, left rectal, and left precentral regions. Furthermore, in an alternate sample of 113, connectivity values in regions of difference correlated with episodic memory and processing speed. Results suggest functional connectivity values in regions of difference are associated with cognitive function and may reflect the presence of AD pathology and increased risk of developing clinical AD. (JINS, 2012, 18, 39–48)

Keywords

Mild cognitive impairment (MCI)Resting-state fMRIFunctional connectivityPosterior cingulate cortexMemoryBasal gangliaStriatum
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 18 , Issue 1 , January 2012 , pp. 39 - 48
Copyright
Copyright © The International Neuropsychological Society 2011

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References

Allen, G., Barnard, H., McColl, R., Hester, A.L., Fields, J.A., Weiner, M.F., Cullum, M. (2007). Reduced hippocampal functional connectivity in Alzheimer's disease. Archives of Neurology, 64(10), 1482–1487.Google Scholar
Alzheimer's Association. (2009). 2009 Alzheimer's disease facts and figures. Alzheimer's and Dementia, 5(3), 234–270.Google Scholar
Bai, F., Watson, D.R., Hui, Y., Shi, Y., Yuan, Y., Zhang, Z. (2009). Abnormal resting-state functional connectivity of posterior cingulate cortex in amnestic type mild cognitive impairment. Brain Research, 1302, 167–174.CrossRefGoogle ScholarPubMed
Bennett, D.A., Schneider, J.A., Aggarwal, N.T., Arvanitakis, Z., Shah, R.C., Kelly, J.F., Wilson, R.S. (2006). Decision rules guiding the clinical diagnosis of Alzheimer's disease in two community-based cohort compared to standard practice in a clinic-based cohort study. Neuroepidemiology, 27, 169–176.CrossRefGoogle Scholar
Bennett, D.A., Schneider, J.A., Buchman, A.S., Mendes de Leon, C., Bienias, J.L., Wilson, R.S. (2005). The Rush Memory and Aging Project: Study design and baseline characteristics of the study cohort. Neuroepidemiology, 25(4), 163–175.CrossRefGoogle ScholarPubMed
Bennett, D.A., Wilson, R.S., Schneider, J.A., Evans, D.A., Beckett, L.A., Aggarwal, N.T., Bach, J. (2002). Natural history of mild cognitive impairment in older persons. Neurology, 59, 198–205.CrossRefGoogle ScholarPubMed
Boyle, P.A., Wilson, R.S., Aggarwal, N.T., Tang, Y., Bennett, D.A. (2005). Mild cognitive impairment: Risk of Alzheimer disease and rate of cognitive decline. Neurology, 67, 441–445.Google Scholar
Bozzali, M., Parker, G.J., Serra, L., Embleton, K., Gili, T., Perri, R., Cercignani, M. (2011). Anatomical connectivity mapping: A new tool to assess brain disconnection in Alzheimer's disease. Neuroimage, 54, 2045–2051.CrossRefGoogle ScholarPubMed
Braak, H., Braak, E. (1990). Alzheimer's disease: Striatal amyloid deposits and neurofibrillary changes. Journal of Neuropathology and Experimental Neurology, 49, 215–224.Google Scholar
Buckner, R.L., Sepulcre, J., Talukdar, T., Krienen, F.M., Liu, H., Hedden, T., Johnson, K.A. (2009). Cortical hubs revealed by intrinsic functional connectivity: Mapping, assessment of stability, and relation to Alzheimer's disease. The Journal of Neuroscience, 29(6), 1860–1873.CrossRefGoogle ScholarPubMed
Buckner, R.L., Synder, A.Z., Shannon, B.J., LaRossa, G., Sachs, R., Fotenos, A.F., Mintun, M.A. (2005). Molecular, structural, and functional characterization of Alzheimer's disease: Evidence for a relationship between default activity, amyloid, and memory. The Journal of Neuroscience, 25(34), 7709–7717.CrossRefGoogle ScholarPubMed
Buckner, R.L., Vincent, J.L. (2007). Unrest at rest: Default activity and spontaneous network correlations. Neuroimage, 37, 1091–1096.Google Scholar
Cabeza, R. (2002). Hemispheric asymmetry reduction in older adults: The HAROLD model. Psychology and Aging, 17(1), 85–100.Google Scholar
Damoiseaux, J.S., Rombouts, S.A., Barkhof, F., Scheltens, P., Stam, C.J., Smith, S.M., Beckmann, C.F. (2006). Consistent resting-state networks across healthy subjects. Proceedings of the National Academy of Sciences of the United States of America, 103(37), 13848–13853.CrossRefGoogle ScholarPubMed
De Jong, L.W., van der Hiele, K., Veer, I.M., Houwig, J.J., Westendorp, R.G., Bollen, E.L., van der Grond, J. (2008). Srongly reduced volumes of putamen and thalamus in Alzheimer's disease: An MRI study. Brain, 131, 3277–3285.CrossRefGoogle Scholar
Fleisher, A.S., Sherzai, A., Talyor, C., Langbaum, J.B., Chen, K., Buxton, R.B. (2009). Resting- state BOLD networks versus task-associated functional MRI for distinguishing Alzheimer's disease risk groups. Neuroimage, 47(4), 1678–1690.CrossRefGoogle ScholarPubMed
Fleischman, D.A., Wilson, R.S., Bienias, J.L., Bennett, D.A. (2005). Parkinsonian signs and cognitive function in old age. Journal of the International Neuropsychological Society, 11, 591–597.Google Scholar
Friston, K.J., Passingham, R.E., Hutt, J.G., Heather, J.D., Sawle, G.V., Frackowiak, R.S.J. (1995). Spatial registration and normalization of images. Human Brain Mapping, 3(3), 165–189.Google Scholar
Gili, T., Cercignani, M., Serra, L., Perri, R., Giove, F., Maraviglia, B., Bozzali, M. (2011). Regional brain atrophy and functional disconnection across Alzheimer's disease evolution. Journal of Neurology, Neurosurgery, and Psychiatry, 82(1), 58–66.CrossRefGoogle ScholarPubMed
Glover, G.H., Thomason, M.E. (2004). Improved combination of spiral-in/out images for BOLD fMRI. Magnetic Resonance in Medicine, 51, 863–868.CrossRefGoogle ScholarPubMed
Graham, J.E., Rockwood, K., Beattie, B.L., Eastwood, R., Gauthier, S., Tuokko, H., McDowell, I. (1997). Prevalence and severity of cognitive impairment with and without dementia in an elderly population. Lancet, 49, 1793–1796.CrossRefGoogle Scholar
Greicius, M.D., Kiviniemi, V., Tervonen, O., Vainionpaa, V., Alahuhta, S., Reiss, A.L., Menon, V. (2008). Persistent default mode network connectivity during light sedation. Human Brain Mapping, 29, 839–847.CrossRefGoogle ScholarPubMed
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(1), 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(13), 4637–4642.CrossRefGoogle ScholarPubMed
Gusnard, D.A., Raichle, M.E. (2001). Searching for a baseline: Functional imaging and the resting human brain. Nature Reviews. Neuroscience, 2, 685–694.Google Scholar
Habeck, C., Fostern, N.L., Pernecsky, R., Kurz, A., Alexopoulos, P., Koeppe, R.A., Stern, Y. (2008). Multivariate and univariate neuroimaging biomarkers of Alzheimer's disease. Neuroimage, 40(4), 1503–1515.Google Scholar
Han, S.D., Houston, W.S., Jak, A.J., Eyler, L.T., Nagel, B.J., Fleisher, A.S., Bondi, M.W. (2007). Verbal paired-associate learning by APOE genotype in nondemented adults: fMRI evidence of a right hemispheric compensatory response. Neurobiology of Aging, 28(2), 238–247.CrossRefGoogle ScholarPubMed
Harrison, B.J., Pujol, J., Lopez-Sola, M., Hernandez-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(28), 9781–9786.CrossRefGoogle ScholarPubMed
Hedden, T., Van Dijk, K.R., Becker, J.A., Mehta, A., Sperling, R.A., Johnson, K.A., Buckner, R.A. (2009). Disruption of functional connectivity in clinically normal older adults harboring amyloid burden. The Journal of Neuroscience, 29(40), 12686–12694.CrossRefGoogle ScholarPubMed
Hebert, L.E., Scherr, P.A., Bienias, J.L., Bennett, D.A., Evans, D.A. (2003). Alzheimer disease in the U.S. population: Prevalence estimates using the 2000 census. Archives of Neurology, 60(8), 1119–1122.Google Scholar
Klunk, W.E., Engler, H., Nordberg, A., Wang, Y., Blomqvist, G., Holt, D.P., Långström, B. (2004). Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound-B. Annals of Neurology, 55(3), 306–319.CrossRefGoogle ScholarPubMed
Koch, W., Teipel, S., Buerger, K., Bokde, A.L., Hampel, H., Coates, U., Meindl, T. (2010). Effects of aging on default mode network activity in resting state fMRI: Does the method of analysis matter? Neuroimage, 51(1), 280–287.CrossRefGoogle ScholarPubMed
Koivunen, J., Scheinin, N., Virta, J.R., Aalto, S., Vahlberg, T., Nagren, K., Rinne, J.O. (2011). Amyloid PET imaging in patients with mild cognitive impairment: A 2-year follow-up study. Neurology, 76(12), 1085–1090.CrossRefGoogle ScholarPubMed
McKhann, G.M., Knopman, D.S., Chertkow, H., Hyman, B.T., Jack, C.R., Kawas, C.H., Phelps, C.H. (2011), The diagnosis of dementia due to Alzheimer's disease: Recommendations from the National Institute on Aging and the Alzheimer's Association workgroup. Alzheimer's and Dementia, 7, 263–269.CrossRefGoogle Scholar
Raiche, 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(2), 676–682.CrossRefGoogle Scholar
Rombouts, S.A., Barkhof, F., Goekoop, R., Stam, C.J., Sheltens, 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
Segonne, F., Dale, A.M., Busa, E., Glessner, M., Salat, D., Hahn, H.K., Fischl, B. (2004). A hybrid approach to the skull stripping problem in MRI. Neuroimage, 22(3), 1060–1075.CrossRefGoogle Scholar
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
Sperling, R.A., Aisen, P.S., Beckett, L.A., Bennett, D.A., Craft, S., Fagan, A.M., Phelps, C.H. (2011). Toward defining the preclinical stages of Alzheimer's disease: Recommendations from the National Institute on Aging and the Alzheimer's Association workgroup. Alzheimer's & Dementia, 7(3), 280–292.CrossRefGoogle Scholar
Sperling, R.A., LaViolette, P.S., O'Keefe, K., O'Brien, J., Rentz, D., Pihlajamaki, M., Johnson, K.A. (2009). Amyloid deposition is associated with impaired default network function in older persons without dementia. Neuron, 63, 178–188.CrossRefGoogle ScholarPubMed
Wang, L., Laviolette, P., O'Keefe, K., Putcha, D., Bakkour, A., Van Dijk, K.R., Sperling, R.A. (2010). Intrinsic connectivity between the hippocampus and posteromedical cortex predicts memory performance in cognitively intact older individuals. Neuroimaging, 51(2), 910–917.CrossRefGoogle Scholar
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.Google Scholar
Wilson, R.S., Barnes, L.L., Bennett, D.A. (2003). Assessment of lifetime participation in cognitively stimulating activities. Journal of Clinical and Experimental Neuropsycholology, 25, 634–642.Google Scholar
Zhang, H.-Y., Wang, S.-J., Xing, J., Liu, B., Ma, Z.-L., Yang, M., Teng, G.-J. (2009). Detection of PCC functional connectivity characteristics in resting-state fMRI in mild Alzheimer's disease. Behavioural Brain Research, 197, 103–108.Google Scholar
Zhou, Y., Dougherty, J.H., Hubner, K.F., Bai, B., Cannon, R.L., Hutson, R.K. (2008). Abnormal connectivity in the posterior cingulated and hippocampus in early Alzheimer's disease and mild cognitive impairment. Alzheimer's and Dementia, 4, 265–270.Google Scholar