Skip to main content

Advertisement

SpringerLink
Log in

Voxel and surface-based topography of memory and executive deficits in mild cognitive impairment and Alzheimer’s disease

  • ADNI: Friday Harbor 2011 Workshop SPECIAL ISSUE
  • Published:
Brain Imaging and Behavior Aims and scope Submit manuscript

Abstract

Mild cognitive impairment (MCI) and Alzheimer’s disease (AD) are associated with a progressive loss of cognitive abilities. In the present report, we assessed the relationship of memory and executive function with brain structure in a sample of 810 Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants, including 188 AD, 396 MCI, and 226 healthy older adults (HC). Composite scores of memory (ADNI-Mem) and executive function (ADNI-Exec) were generated by applying modern psychometric theory to item-level data from ADNI’s neuropsychological battery. We performed voxel-based morphometry (VBM) and surface-based association (SurfStat) analyses to evaluate relationships of ADNI-Mem and ADNI-Exec with grey matter (GM) density and cortical thickness across the whole brain in the combined sample and within diagnostic groups. We observed strong associations between ADNI-Mem and medial and lateral temporal lobe atrophy. Lower ADNI-Exec scores were associated with advanced GM and cortical atrophy across broadly distributed regions, most impressively in the bilateral parietal and temporal lobes. We also evaluated ADNI-Exec adjusted for ADNI-Mem, and found associations with GM density and cortical thickness primarily in the bilateral parietal, temporal, and frontal lobes. Within-group analyses suggest these associations are strongest in patients with MCI and AD. The present study provides insight into the spatially unbiased associations between brain atrophy and memory and executive function, and underscores the importance of structural brain changes in early cognitive decline.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Albert, M. S., DeKosky, S. T., Dickson, D., Dubois, B., Feldman, H. H., Fox, N. C., et al. (2011). The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & Dementia, 7(3), 270–279.

    Article  Google Scholar 

  • Amici, S., Ogar, J., Brambati, S. M., Miller, B. L., Neuhaus, J., Dronkers, N. L., et al. (2007). Performance in specific language tasks correlates with regional volume changes in progressive aphasia. Cognitive and Behavioral Neurology, 20(4), 203–211.

    Article  PubMed  Google Scholar 

  • Apostolova, L. G., Lu, P., Rogers, S., Dutton, R. A., Hayashi, K. M., Toga, A. W., et al. (2008). 3D mapping of language networks in clinical and pre-clinical Alzheimer’s disease. Brain and Language, 104(1), 33–41.

    Article  PubMed  Google Scholar 

  • Apostolova, L. G., Morra, J. H., Green, A. E., Hwang, K. S., Avedissian, C., Woo, E., et al. (2010). Automated 3D mapping of baseline and 12-month associations between three verbal memory measures and hippocampal atrophy in 490 ADNI subjects. NeuroImage, 51(1), 488–499.

    Article  PubMed  Google Scholar 

  • Armstrong, R. A. (2009). The molecular biology of senile plaques and neurofibrillary tangles in Alzheimer’s disease. Folia Neuropathologica, 47(4), 289–299.

    PubMed  CAS  Google Scholar 

  • Ashburner, J., & Friston, K. J. (2000). Voxel-based morphometry—the methods. NeuroImage, 11(6 Pt 1), 805–821.

    Article  PubMed  CAS  Google Scholar 

  • Barbeau, E. J., Ranjeva, J. P., Didic, M., Confort-Gouny, S., Felician, O., Soulier, E., et al. (2008). Profile of memory impairment and gray matter loss in amnestic mild cognitive impairment. Neuropsychologia, 46(4), 1009–1019.

    Article  PubMed  CAS  Google Scholar 

  • Berlingeri, M., Bottini, G., Basilico, S., Silani, G., Zanardi, G., Sberna, M., et al. (2008). Anatomy of the episodic buffer: a voxel-based morphometry study in patients with dementia. Behavioural Neurology, 19(1–2), 29–34.

    PubMed  CAS  Google Scholar 

  • Braak, H., & Braak, E. (1996). Evolution of the neuropathology of Alzheimer’s disease. Acta Neurologica Scandinavica. Supplementum, 165, 3–12.

    Article  PubMed  CAS  Google Scholar 

  • Braak, H., Braak, E., & Bohl, J. (1993). Staging of Alzheimer-related cortical destruction. European Neurology, 33(6), 403–408.

    Article  PubMed  CAS  Google Scholar 

  • Braak, H., Braak, E., Yilmazer, D., de Vos, R. A., Jansen, E. N., & Bohl, J. (1996). Pattern of brain destruction in Parkinson’s and Alzheimer’s diseases. Journal of Neural Transmission, 103(4), 455–490.

    Article  PubMed  CAS  Google Scholar 

  • Brambati, S. M., Myers, D., Wilson, A., Rankin, K. P., Allison, S. C., Rosen, H. J., et al. (2006). The anatomy of category-specific object naming in neurodegenerative diseases. Journal of Cognitive Neuroscience, 18(10), 1644–1653.

    Article  PubMed  CAS  Google Scholar 

  • Braskie, M. N., Small, G. W., & Bookheimer, S. Y. (2009). Entorhinal cortex structure and functional MRI response during an associative verbal memory task. Human Brain Mapping, 30(12), 3981–3992.

    Article  PubMed  Google Scholar 

  • Cabeza, R. (2008). Role of parietal regions in episodic memory retrieval: the dual attentional processes hypothesis. Neuropsychologia, 46(7), 1813–1827.

    Article  PubMed  Google Scholar 

  • Cabeza, R., & Nyberg, L. (2000). Imaging cognition II: an empirical review of 275 PET and fMRI studies. Journal of Cognitive Neuroscience, 12(1), 1–47.

    Article  PubMed  CAS  Google Scholar 

  • Cabeza, R., Ciaramelli, E., Olson, I. R., & Moscovitch, M. (2008). The parietal cortex and episodic memory: an attentional account. Nature Reviews Neuroscience, 9(8), 613–625.

    Article  PubMed  CAS  Google Scholar 

  • Cahn-Weiner, D. A., Sullivan, E. V., Shear, P. K., Fama, R., Lim, K. O., Yesavage, J. A., et al. (1999). Brain structural and cognitive correlates of clock drawing performance in Alzheimer’s disease. Journal of International Neuropsychological Society, 5(6), 502–509.

    Article  CAS  Google Scholar 

  • Chang, Y. L., Bondi, M. W., Fennema-Notestine, C., McEvoy, L. K., Hagler, D. J., Jr., Jacobson, M. W., et al. (2010). Brain substrates of learning and retention in mild cognitive impairment diagnosis and progression to Alzheimer’s disease. Neuropsychologia, 48(5), 1237–1247.

    Article  PubMed  Google Scholar 

  • Chang, Y. L., Jacobson, M. W., Fennema-Notestine, C., Hagler, D. J., Jr., Jennings, R. G., Dale, A. M., et al. (2010). Level of executive function influences verbal memory in amnestic mild cognitive impairment and predicts prefrontal and posterior cingulate thickness. Cerebral Cortex, 20(6), 1305–1313.

    Article  PubMed  Google Scholar 

  • Chetelat, G., Desgranges, B., de la Sayette, V., Viader, F., Berkouk, K., Landeau, B., et al. (2003). Dissociating atrophy and hypometabolism impact on episodic memory in mild cognitive impairment. Brain, 126(Pt 9), 1955–1967.

    Article  PubMed  Google Scholar 

  • Chetelat, G., Villemagne, V. L., Pike, K. E., Ellis, K. A., Bourgeat, P., Jones, G., et al. (2011). Independent contribution of temporal beta-amyloid deposition to memory decline in the pre-dementia phase of Alzheimer’s disease. Brain, 134(Pt 3), 798–807.

    Article  PubMed  Google Scholar 

  • Chiang, G. C., Insel, P. S., Tosun, D., Schuff, N., Truran-Sacrey, D., Raptentsetsang, S., et al. (2011). Identifying cognitively healthy elderly individuals with subsequent memory decline by using automated MR temporoparietal volumes. Radiology, 259(3), 844–851.

    Article  PubMed  Google Scholar 

  • Chou, Y. Y., Lepore, N., Avedissian, C., Madsen, S. K., Parikshak, N., Hua, X., et al. (2009). Mapping correlations between ventricular expansion and CSF amyloid and tau biomarkers in 240 subjects with Alzheimer’s disease, mild cognitive impairment and elderly controls. NeuroImage, 46(2), 394–410.

    Article  PubMed  Google Scholar 

  • Chou, Y. Y., Lepore, N., Saharan, P., Madsen, S. K., Hua, X., Jack, C. R., et al. (2010). Ventricular maps in 804 ADNI subjects: correlations with CSF biomarkers and clinical decline. Neurobiology of Aging, 31(8), 1386–1400.

    Article  PubMed  Google Scholar 

  • Cockrell, J. R., & Folstein, M. F. (1988). Mini-Mental State Examination (MMSE). Psychopharmacology Bulletin, 24(4), 689–692.

    PubMed  CAS  Google Scholar 

  • Convit, A., de Asis, J., de Leon, M. J., Tarshish, C. Y., De Santi, S., & Rusinek, H. (2000). Atrophy of the medial occipitotemporal, inferior, and middle temporal gyri in non-demented elderly predict decline to Alzheimer’s disease. Neurobiology of Aging, 21(1), 19–26.

    Article  PubMed  CAS  Google Scholar 

  • Costafreda, S. G., Fu, C. H., Lee, L., Everitt, B., Brammer, M. J., & David, A. S. (2006). A systematic review and quantitative appraisal of fMRI studies of verbal fluency: role of the left inferior frontal gyrus. Human Brain Mapping, 27(10), 799–810.

    Article  PubMed  Google Scholar 

  • Crane, P. K., Carle, A., Gibbons L. E., et al. (2012). Development and assessment of a composite score for memory in the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Brain Imaging and Behavior. doi:10.1007/s11682-012-9186-z.

  • Crane, P. K., Narasimhalu, K., Gibbons, L. E., Pedraza, O., Mehta, K. M., Tang, Y., et al. (2008). Composite scores for executive function items: demographic heterogeneity and relationships with quantitative magnetic resonance imaging. Journal of International Neuropsychological Society, 14(5), 746–759.

    Article  Google Scholar 

  • Dale, A., Fischl, B., & Sereno, M. (1999). Cortical surface-based analysis. I. Segmentation and surface reconstruction. NeuroImage, 9(2), 179–194.

    Article  PubMed  CAS  Google Scholar 

  • Deweer, B., Lehericy, S., Pillon, B., Baulac, M., Chiras, J., Marsault, C., et al. (1995). Memory disorders in probable Alzheimer’s disease: the role of hippocampal atrophy as shown with MRI. Journal of Neurology, Neurosurgery, and Psychiatry, 58(5), 590–597.

    Article  PubMed  CAS  Google Scholar 

  • Di Paola, M., Macaluso, E., Carlesimo, G. A., Tomaiuolo, F., Worsley, K. J., Fadda, L., et al. (2007). Episodic memory impairment in patients with Alzheimer’s disease is correlated with entorhinal cortex atrophy. A voxel-based morphometry study. Journal of Neurology, 254(6), 774–781.

    Article  PubMed  Google Scholar 

  • Dickerson, B. C., & Wolk, D. A. (2011). Dysexecutive versus amnesic phenotypes of very mild Alzheimer’s disease are associated with distinct clinical, genetic and cortical thinning characteristics. Journal of Neurology, Neurosurgery, and Psychiatry, 82(1), 45–51.

    Article  PubMed  Google Scholar 

  • Epstein, N. U., Saykin, A. J., Risacher, S. L., Gao, S., & Farlow, M. R. (2010). Differences in medication use in the Alzheimer’s disease neuroimaging initiative: analysis of baseline characteristics. Drugs & Aging, 27(8), 677–686.

    Article  Google Scholar 

  • Evans, M. C., Barnes, J., Nielsen, C., Kim, L. G., Clegg, S. L., Blair, M., et al. (2010). Volume changes in Alzheimer’s disease and mild cognitive impairment: cognitive associations. European Radiology, 20(3), 674–682.

    Article  PubMed  Google Scholar 

  • Fischl, B., & Dale, A. M. (2000). Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proceedings of the National Academy of Sciences of the United States of America, 97(20), 11050–11055.

    Article  PubMed  CAS  Google Scholar 

  • Fischl, B., Sereno, M., & Dale, A. (1999). Cortical surface-based analysis. II: inflation, flattening, and a surface-based coordinate system. NeuroImage, 9(2), 195–207.

    Article  PubMed  CAS  Google Scholar 

  • Fischl, B., Salat, D., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., et al. (2002). Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron, 33(3), 341–355.

    Article  PubMed  CAS  Google Scholar 

  • Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). Mini-mental state. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189–198.

    Article  PubMed  CAS  Google Scholar 

  • Fox, N. C., Warrington, E. K., Freeborough, P. A., Hartikainen, P., Kennedy, A. M., Stevens, J. M., et al. (1996). Presymptomatic hippocampal atrophy in Alzheimer’s disease. A longitudinal MRI study. Brain, 119(Pt 6), 2001–2007.

    Article  PubMed  Google Scholar 

  • Gibbons, L. E., Carle, A. C., Mackin, R. S., Harvey, D., et al. (2012). A composite score for executive functioning, validated in Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants with baseline mild cognitive impairment. Brain Imaging and Behavior. doi:10.1007/s11682-012-9176-1.

  • Good, C. D., Johnsrude, I. S., Ashburner, J., Henson, R. N., Friston, K. J., & Frackowiak, R. S. (2001). A voxel-based morphometric study of ageing in 465 normal adult human brains. NeuroImage, 14(1 Pt 1), 21–36.

    Article  PubMed  CAS  Google Scholar 

  • Goodglass, H., & Kaplan, E. (1983). The assessment of aphasia and related disorders. Philadelphia: Lea & Febiger.

    Google Scholar 

  • Goto, M., Abe, O., Miyati, T., Yoshikawa, T., Hayashi, N., Takao, H., et al. (2011). Entorhinal cortex volume measured with 3 T MRI is positively correlated with the Wechsler Memory Scale-Revised logical/verbal memory score for healthy subjects. Neuroradiology, 53(8), 617–622.

    Article  PubMed  Google Scholar 

  • Grady, C. L., McIntosh, A. R., Beig, S., Keightley, M. L., Burian, H., & Black, S. E. (2003). Evidence from functional neuroimaging of a compensatory prefrontal network in Alzheimer’s disease. Journal of Neuroscience, 23(3), 986–993.

    PubMed  CAS  Google Scholar 

  • Greene, S. J., & Killiany, R. J. (2010). Subregions of the inferior parietal lobule are affected in the progression to Alzheimer’s disease. Neurobiology of Aging, 31(8), 1304–1311.

    Article  PubMed  Google Scholar 

  • Greene, S. J., & Killiany, R. J. (2011). Hippocampal subregions are differentially affected in the progression to alzheimer’s disease. Anatomical Record (Hoboken).

  • Grossman, M., McMillan, C., Moore, P., Ding, L., Glosser, G., Work, M., et al. (2004). What’s in a name: voxel-based morphometric analyses of MRI and naming difficulty in Alzheimer’s disease, frontotemporal dementia and corticobasal degeneration. Brain, 127(Pt 3), 628–649.

    PubMed  Google Scholar 

  • Hackert, V. H., den Heijer, T., Oudkerk, M., Koudstaal, P. J., Hofman, A., & Breteler, M. M. (2002). Hippocampal head size associated with verbal memory performance in nondemented elderly. NeuroImage, 17(3), 1365–1372.

    Article  PubMed  CAS  Google Scholar 

  • Hamalainen, A., Pihlajamaki, M., Tanila, H., Hanninen, T., Niskanen, E., Tervo, S., et al. (2007). Increased fMRI responses during encoding in mild cognitive impairment. Neurobiology of Aging, 28(12), 1889–1903.

    Article  PubMed  Google Scholar 

  • Hardy, J., & Selkoe, D. J. (2002). The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science, 297(5580), 353–356.

    Article  PubMed  CAS  Google Scholar 

  • Hart, J., Jr., Anand, R., Zoccoli, S., Maguire, M., Gamino, J., Tillman, G., et al. (2007). Neural substrates of semantic memory. Journal of International Neuropsychological Society, 13(5), 865–880.

    Article  Google Scholar 

  • Hirono, N., Mori, E., Ishii, K., Imamura, T., Tanimukai, S., Kazui, H., et al. (2001). Neuronal substrates for semantic memory: a positron emission tomography study in Alzheimer’s disease. Dementia and Geriatric Cognitive Disorders, 12(1), 15–21.

    Article  PubMed  CAS  Google Scholar 

  • Holtzman, D. M., Morris, J. C., & Goate, A. M. (2011). Alzheimer’s disease: the challenge of the second century. Science Translational Medicine, 3(77), 77sr71.

    Article  CAS  Google Scholar 

  • Hua, X., Leow, A. D., Parikshak, N., Lee, S., Chiang, M. C., Toga, A. W., et al. (2008). Tensor-based morphometry as a neuroimaging biomarker for Alzheimer’s disease: an MRI study of 676 AD, MCI, and normal subjects. NeuroImage, 43(3), 458–469.

    Article  PubMed  Google Scholar 

  • Huey, E. D., Goveia, E. N., Paviol, S., Pardini, M., Krueger, F., Zamboni, G., et al. (2009). Executive dysfunction in frontotemporal dementia and corticobasal syndrome. Neurology, 72(5), 453–459.

    Article  PubMed  CAS  Google Scholar 

  • Ino, T., Asada, T., Ito, J., Kimura, T., & Fukuyama, H. (2003). Parieto-frontal networks for clock drawing revealed with fMRI. Neurosciences Research, 45(1), 71–77.

    Article  Google Scholar 

  • Jack, C. R., Jr., Lowe, V. J., Weigand, S. D., Wiste, H. J., Senjem, M. L., Knopman, D. S., et al. (2009). Serial PIB and MRI in normal, mild cognitive impairment and Alzheimer’s disease: implications for sequence of pathological events in Alzheimer’s disease. Brain, 132(Pt 5), 1355–1365.

    Article  PubMed  Google Scholar 

  • Jagust, W., Gitcho, A., Sun, F., Kuczynski, B., Mungas, D., & Haan, M. (2006). Brain imaging evidence of preclinical Alzheimer’s disease in normal aging. Annals of Neurology, 59(4), 673–681.

    Article  PubMed  Google Scholar 

  • Juottonen, K., Laakso, M. P., Insausti, R., Lehtovirta, M., Pitkanen, A., Partanen, K., et al. (1998). Volumes of the entorhinal and perirhinal cortices in Alzheimer’s disease. Neurobiology of Aging, 19(1), 15–22.

    Article  PubMed  CAS  Google Scholar 

  • Kato, T., Knopman, D., & Liu, H. (2001). Dissociation of regional activation in mild AD during visual encoding: a functional MRI study. Neurology, 57, 812–816.

    Article  PubMed  CAS  Google Scholar 

  • King, R. D., Brown, B., Hwang, M., Jeon, T., & George, A. T. (2010). Fractal dimension analysis of the cortical ribbon in mild Alzheimer’s disease. NeuroImage, 53(2), 471–479.

    Article  PubMed  Google Scholar 

  • Knopman, D. S., DeKosky, S. T., Cummings, J. L., Chui, H., Corey-Bloom, J., Relkin, N., et al. (2001). Practice parameter: diagnosis of dementia (an evidence-based review). Report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology, 56(9), 1143–1153.

    Article  PubMed  CAS  Google Scholar 

  • Kovacevic, S., Rafii, M. S., & Brewer, J. B. (2009). High-throughput, fully automated volumetry for prediction of MMSE and CDR decline in mild cognitive impairment. Alzheimer Disease and Associated Disorders, 23(2), 139–145.

    Article  PubMed  Google Scholar 

  • Kramer, J. H., Quitania, L., Dean, D., Neuhaus, J., Rosen, H. J., Halabi, C., et al. (2007). Magnetic resonance imaging correlates of set shifting. Journal of International Neuropsychological Society, 13(3), 386–392.

    Article  Google Scholar 

  • Laakso, M. P., Soininen, H., Partanen, K., Helkala, E. L., Hartikainen, P., Vainio, P., et al. (1995). Volumes of hippocampus, amygdala and frontal lobes in the MRI-based diagnosis of early Alzheimer’s disease: correlation with memory functions. Journal of Neural Transmission. Parkinson’s Disease and Dementia Section, 9(1), 73–86.

    Article  PubMed  CAS  Google Scholar 

  • Leow, A. D., Yanovsky, I., Parikshak, N., Hua, X., Lee, S., Toga, A. W., et al. (2009). Alzheimer’s disease neuroimaging initiative: a one-year follow up study using tensor-based morphometry correlating degenerative rates, biomarkers and cognition. NeuroImage, 45(3), 645–655.

    Article  PubMed  Google Scholar 

  • Leube, D. T., Weis, S., Freymann, K., Erb, M., Jessen, F., Heun, R., et al. (2008). Neural correlates of verbal episodic memory in patients with MCI and Alzheimer’s disease—a VBM study. International Journal of Geriatric Psychiatry, 23(11), 1114–1118.

    Article  PubMed  Google Scholar 

  • Lo, R. Y., Hubbard, A. E., Shaw, L. M., Trojanowski, J. Q., Petersen, R. C., Aisen, P. S., et al. (2011). Longitudinal change of biomarkers in cognitive decline. Archives of Neurology, 68(10), 1257–1266.

    Article  PubMed  Google Scholar 

  • Madsen, S. K., Ho, A. J., Hua, X., Saharan, P. S., Toga, A. W., Jack, C. R., Jr., et al. (2010). 3D maps localize caudate nucleus atrophy in 400 Alzheimer’s disease, mild cognitive impairment, and healthy elderly subjects. Neurobiology of Aging, 31(8), 1312–1325.

    Article  PubMed  CAS  Google Scholar 

  • McDonald, C. R., Gharapetian, L., McEvoy, L. K., Fennema-Notestine, C., Hagler, D. J., Jr., Holland, D., et al. (2012). Relationship between regional atrophy rates and cognitive decline in mild cognitive impairment. Neurobiology of Aging, 33(2), 242–253.

    Article  PubMed  Google Scholar 

  • McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984). Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA work group under the auspices of Health and Human Services Task Force on Alzheimer’s Disease. Neurology, 34, 939–944.

    Article  PubMed  CAS  Google Scholar 

  • McKhann, G. M., Knopman, D. S., Chertkow, H., Hyman, B. T., Jack, C. R., Jr., Kawas, C. H., et al. (2011). The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & Dementia, 7(3), 263–269.

    Article  Google Scholar 

  • Mechelli, A. P., Price, C. J., Friston, K. J., & Ashburner, J. (2005). Voxel-based morphometry of the human brain: methods and applications. Current Medical Imaging Reviews, 1(1), 1–9.

    Article  Google Scholar 

  • Minati, L., Edginton, T., Bruzzone, M. G., & Giaccone, G. (2009). Current concepts in Alzheimer’s disease: a multidisciplinary review. American Journal of Alzheimer’s Disease and Other Dementias, 24(2), 95–121.

    Article  PubMed  Google Scholar 

  • Mohs, R. C. (1994). Administration and scoring manual for the Alzheimer’s Disease Assessment Scale, 1994 revised edition.

  • Moll, J., de Oliveira-Souza, R., Moll, F. T., Bramati, I. E., & Andreiuolo, P. A. (2002). The cerebral correlates of set-shifting: an fMRI study of the trail making test. Arquivos de Neuro-Psiquiatria, 60(4), 900–905.

    Article  PubMed  Google Scholar 

  • Monchi, O., Petrides, M., Petre, V., Worsley, K., & Dagher, A. (2001). Wisconsin Card Sorting revisited: distinct neural circuits participating in different stages of the task identified by event-related functional magnetic resonance imaging. Journal of Neuroscience, 21(19), 7733–7741.

    PubMed  CAS  Google Scholar 

  • Mormino, E. C., Kluth, J. T., Madison, C. M., Rabinovici, G. D., Baker, S. L., Miller, B. L., et al. (2009). Episodic memory loss is related to hippocampal-mediated beta-amyloid deposition in elderly subjects. Brain, 132(Pt 5), 1310–1323.

    Article  PubMed  CAS  Google Scholar 

  • Morra, J. H., Tu, Z., Apostolova, L. G., Green, A. E., Avedissian, C., Madsen, S. K., et al. (2009a). Automated 3D mapping of hippocampal atrophy and its clinical correlates in 400 subjects with Alzheimer’s disease, mild cognitive impairment, and elderly controls. Human Brain Mapping, 30(9), 2766–2788.

    Article  PubMed  Google Scholar 

  • Morra, J. H., Tu, Z., Apostolova, L. G., Green, A. E., Avedissian, C., Madsen, S. K., et al. (2009b). Automated mapping of hippocampal atrophy in 1-year repeat MRI data from 490 subjects with Alzheimer’s disease, mild cognitive impairment, and elderly controls. NeuroImage, 45(1 Suppl), S3–S15.

    Article  PubMed  Google Scholar 

  • Morris, J. C. (1993). The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology, 43(11), 2412–2414.

    Article  PubMed  CAS  Google Scholar 

  • Morris, J., Heyman, A., Mohs, R., Hughes, J., van Belle, G., Fillenbaum, G., et al. (1989). The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD). Part I. Clinical and neuropsychological assessment of Alzheimer’s disease. Neurology, 39(9), 1159–1165.

    Article  PubMed  CAS  Google Scholar 

  • Mueller, S. G., Weiner, M. W., Thal, L. J., Petersen, R. C., Jack, C., Jagust, W., et al. (2005a). The Alzheimer’s disease neuroimaging initiative. Neuroimaging Clinics of North America, 15(4), 869–877.

    Article  PubMed  Google Scholar 

  • Mueller, S. G., Weiner, M. W., Thal, L. J., Petersen, R. C., Jack, C. R., Jagust, W., et al. (2005b). Ways toward an early diagnosis in Alzheimer’s disease: the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Alzheimer’s & Dementia, 1(1), 55–66.

    Article  Google Scholar 

  • Murphy, E. A., Holland, D., Donohue, M., McEvoy, L. K., Hagler, D. J., Jr., Dale, A. M., et al. (2010). Six-month atrophy in MTL structures is associated with subsequent memory decline in elderly controls. NeuroImage, 53(4), 1310–1317.

    Article  PubMed  CAS  Google Scholar 

  • Nestor, S. M., Rupsingh, R., Borrie, M., Smith, M., Accomazzi, V., Wells, J. L., et al. (2008). Ventricular enlargement as a possible measure of Alzheimer’s disease progression validated using the Alzheimer’s disease neuroimaging initiative database. Brain, 131(Pt 9), 2443–2454.

    Article  PubMed  Google Scholar 

  • Nettiksimmons, J., Harvey, D., Brewer, J., Carmichael, O., DeCarli, C., Jack, C. R., Jr., et al. (2010). Subtypes based on cerebrospinal fluid and magnetic resonance imaging markers in normal elderly predict cognitive decline. Neurobiology of Aging, 31(8), 1419–1428.

    Article  PubMed  CAS  Google Scholar 

  • Newman, L. M., Trivedi, M. A., Bendlin, B. B., Ries, M. L., & Johnson, S. C. (2007). The relationship between gray matter morphometry and neuropsychological performance in a large sample of cognitively healthy adults. Brain Imaging and Behavior, 1(1–2), 3–10.

    Article  PubMed  Google Scholar 

  • Oh, H., Mormino, E. C., Madison, C., Hayenga, A., Smiljic, A., & Jagust, W. J. (2011). Beta-amyloid affects frontal and posterior brain networks in normal aging. NeuroImage, 54(3), 1887–1895.

    Article  PubMed  CAS  Google Scholar 

  • Pa, J., Boxer, A., Chao, L. L., Gazzaley, A., Freeman, K., Kramer, J., et al. (2009). Clinical-neuroimaging characteristics of dysexecutive mild cognitive impairment. Annals of Neurology, 65(4), 414–423.

    Article  PubMed  Google Scholar 

  • Pa, J., Possin, K. L., Wilson, S. M., Quitania, L. C., Kramer, J. H., Boxer, A. L., et al. (2010). Gray matter correlates of set-shifting among neurodegenerative disease, mild cognitive impairment, and healthy older adults. Journal of International Neuropsychological Society, 16(4), 640–650.

    Article  Google Scholar 

  • Pantel, J., Schonknecht, P., Essig, M., & Schroder, J. (2004). Distribution of cerebral atrophy assessed by magnetic resonance imaging reflects patterns of neuropsychological deficits in Alzheimer’s dementia. Neuroscience Letters, 361(1–3), 17–20.

    Article  PubMed  CAS  Google Scholar 

  • Park, H., & Seo, J. (2011). Application of multidimensional scaling to quantify shape in Alzheimer’s disease and its correlation with Mini Mental State Examination: a feasibility study. Journal of Neuroscience Methods, 194(2), 380–385.

    Article  PubMed  Google Scholar 

  • Petersen, R. C. (2000). Mild cognitive impairment: transition between aging and Alzheimer’s disease. Neurologia, 15(3), 93–101.

    PubMed  CAS  Google Scholar 

  • 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(3), 303–308.

    Article  PubMed  CAS  Google Scholar 

  • Petersen, R. C., Jack, C. R., Jr., Xu, Y. C., Waring, S. C., O’Brien, P. C., Smith, G. E., et al. (2000). Memory and MRI-based hippocampal volumes in aging and AD. Neurology, 54(3), 581–587.

    Article  PubMed  CAS  Google Scholar 

  • Poulin, S. P., Dautoff, R., Morris, J. C., Barrett, L. F., & Dickerson, B. C. (2011). Amygdala atrophy is prominent in early Alzheimer’s disease and relates to symptom severity. Psychiatry Research, 194(1), 7–13.

    Article  PubMed  Google Scholar 

  • Rabin, L. A., Saykin, A. J., West, J. D., Borgos, M. J., Wishart, H. A., Nutter-Upham, K. E., et al. (2009). Judgement in older adults with normal cognition, cognitive complaints, MCI, and mild AD: relation to regional frontal grey matter. Brain Imaging and Behavior, 3(2), 212–219.

    Article  Google Scholar 

  • Reitan, R., & Wolfson, D. (1985). The Halstead-Reitan Neuropsychological Test Battery. Tucson: Neuropsychology Press.

    Google Scholar 

  • Remy, F., Mirrashed, F., Campbell, B., & Richter, W. (2005). Verbal episodic memory impairment in Alzheimer’s disease: a combined structural and functional MRI study. NeuroImage, 25(1), 253–266.

    Article  PubMed  Google Scholar 

  • Rey, A. (1964). L’examen clinique en psychologie. Paris: Presses Universitaires de France.

    Google Scholar 

  • Risacher, S. L., Saykin, A. J., West, J. D., Shen, L., Firpi, H. A., & McDonald, B. C. (2009). Baseline MRI predictors of conversion from MCI to probable AD in the ADNI cohort. Current Alzheimer Research, 6(4), 347–361.

    Article  PubMed  CAS  Google Scholar 

  • Risacher, S. L., Shen, L., West, J. D., Kim, S., McDonald, B. C., Beckett, L. A., et al. (2010). Longitudinal MRI atrophy biomarkers: relationship to conversion in the ADNI cohort. Neurobiology of Aging, 31(8), 1401–1418.

    Article  PubMed  Google Scholar 

  • Risacher, S. L., Wishart, H. A., & Saykin, A. J. (2011). Functional MRI studies of memory in aging, mild cognitive impairment, and Alzheimer’s disease. In S. H. Faro & F. B. Mohamed (Eds.), Functional neuroradiology (2nd ed.). New York: Springer.

    Google Scholar 

  • Rombouts, S. A., Barkhof, F., Veltman, D. J., Machielsen, W. C., Witter, M. P., Bierlaagh, M. A., et al. (2000). Functional MR imaging in Alzheimer’s disease during memory encoding. AJNR. American Journal of Neuroradiology, 21(10), 1869–1875.

    PubMed  CAS  Google Scholar 

  • Rushworth, M. F., Hadland, K. A., Paus, T., & Sipila, P. K. (2002). Role of the human medial frontal cortex in task switching: a combined fMRI and TMS study. Journal of Neurophysiology, 87(5), 2577–2592.

    PubMed  CAS  Google Scholar 

  • Rusinek, H., De Santi, S., Frid, D., Tsui, W. H., Tarshish, C. Y., Convit, A., et al. (2003). Regional brain atrophy rate predicts future cognitive decline: 6-year longitudinal MR imaging study of normal aging. [Research Support, U.S. Gov’t, P.H.S.]. Radiology, 229(3), 691–696.

    Article  PubMed  Google Scholar 

  • Sabuncu, M. R., Desikan, R. S., Sepulcre, J., Yeo, B. T., Liu, H., Schmansky, N. J., et al. (2011). The dynamics of cortical and hippocampal atrophy in Alzheimer disease. Archives of Neurology, 68(8), 1040–1048.

    Article  PubMed  Google Scholar 

  • Saykin, A. J., Flashman, L. A., Frutiger, S. A., Johnson, S. C., Mamourian, A. C., Moritz, C. H., et al. (1999). Neuroanatomic substrates of semantic memory impairment in Alzheimer’s disease: patterns of functional MRI activation. Journal of International Neuropsychological Society, 5(5), 377–392.

    Article  CAS  Google Scholar 

  • Schmidt-Wilcke, T., Poljansky, S., Hierlmeier, S., Hausner, J., & Ibach, B. (2009). Memory performance correlates with gray matter density in the ento-/perirhinal cortex and posterior hippocampus in patients with mild cognitive impairment and healthy controls—a voxel based morphometry study. NeuroImage, 47(4), 1914–1920.

    Article  PubMed  Google Scholar 

  • Shen, K. K., Fripp, J., Meriaudeau, F., Chetelat, G., Salvado, O., & Bourgeat, P. (2011). Detecting global and local hippocampal shape changes in Alzheimer’s disease using statistical shape models. Neuroimage.

  • Shimamura, A. P. (1995). Memory and the prefrontal cortex. Annals of the New York Academy of Sciences, 769, 151–159.

    Article  PubMed  CAS  Google Scholar 

  • Small, S. A., Perera, G. M., DeLaPaz, R., Mayeux, R., & Stern, Y. (1999). Differential regional dysfunction of the hippocampal formation among elderly with memory decline and Alzheimer’s disease. Annals of Neurology, 45(4), 466–472.

    Article  PubMed  CAS  Google Scholar 

  • Smith, C. D., Malcein, M., Meurer, K., Schmitt, F. A., Markesbery, W. R., & Pettigrew, L. C. (1999). MRI temporal lobe volume measures and neuropsychologic function in Alzheimer’s disease. Journal of Neuroimaging, 9(1), 2–9.

    PubMed  CAS  Google Scholar 

  • Smith, A. B., Taylor, E., Brammer, M., & Rubia, K. (2004). Neural correlates of switching set as measured in fast, event-related functional magnetic resonance imaging. Human Brain Mapping, 21(4), 247–256.

    Article  PubMed  Google Scholar 

  • Sperling, R. A., Bates, J. F., Chua, E. F., Cocchiarella, A. J., Rentz, D. M., Rosen, B. R., et al. (2003). FMRI studies of associative encoding in young and elderly controls and mild Alzheimer’s disease. Journal of Neurology, Neurosurgery, and Psychiatry, 74(1), 44–50.

    Article  PubMed  CAS  Google Scholar 

  • Sperling, R. A., Dickerson, B. C., Pihlajamaki, M., Vannini, P., LaViolette, P. S., Vitolo, O. V., et al. (2010). Functional alterations in memory networks in early Alzheimer’s disease. Neuromolecular Medicine, 12(1), 27–43.

    Article  PubMed  CAS  Google Scholar 

  • Spreen, O., & Strauss, E. (1998). A compendium of neuropsychological tests. New York: Oxford University Press.

    Google Scholar 

  • Stonnington, C. M., Chu, C., Kloppel, S., Jack, C. R., Jr., Ashburner, J., & Frackowiak, R. S. (2010). Predicting clinical scores from magnetic resonance scans in Alzheimer’s disease. NeuroImage, 51(4), 1405–1413.

    Article  PubMed  Google Scholar 

  • Taylor, S. F., Welsh, R. C., Wager, T. D., Phan, K. L., Fitzgerald, K. D., & Gehring, W. J. (2004). A functional neuroimaging study of motivation and executive function. NeuroImage, 21(3), 1045–1054.

    Article  PubMed  Google Scholar 

  • Thomann, P. A., Toro, P., Dos Santos, V., Essig, M., & Schroder, J. (2008). Clock drawing performance and brain morphology in mild cognitive impairment and Alzheimer’s disease. Brain and Cognition, 67(1), 88–93.

    Article  PubMed  Google Scholar 

  • Vemuri, P., Wiste, H. J., Weigand, S. D., Shaw, L. M., Trojanowski, J. Q., Weiner, M. W., et al. (2009a). MRI and CSF biomarkers in normal, MCI, and AD subjects: diagnostic discrimination and cognitive correlations. Neurology, 73(4), 287–293.

    Article  PubMed  CAS  Google Scholar 

  • Vemuri, P., Wiste, H. J., Weigand, S. D., Shaw, L. M., Trojanowski, J. Q., Weiner, M. W., et al. (2009b). MRI and CSF biomarkers in normal, MCI, and AD subjects: predicting future clinical change. Neurology, 73(4), 294–301.

    Article  PubMed  CAS  Google Scholar 

  • Vemuri, P., Wiste, H. J., Weigand, S. D., Knopman, D. S., Shaw, L. M., Trojanowski, J. Q., et al. (2010). Effect of apolipoprotein E on biomarkers of amyloid load and neuronal pathology in Alzheimer disease. Annals of Neurology, 67(3), 308–316.

    PubMed  CAS  Google Scholar 

  • Vemuri, P., Wiste, H. J., Weigand, S. D., Knopman, D. S., Trojanowski, J. Q., Shaw, L. M., et al. (2010). Serial MRI and CSF biomarkers in normal aging, MCI, and AD. Neurology, 75(2), 143–151.

    Article  PubMed  Google Scholar 

  • Vemuri, P., Weigand, S. D., Przybelski, S. A., Knopman, D. S., Smith, G. E., Trojanowski, J. Q., et al. (2011). Cognitive reserve and Alzheimer’s disease biomarkers are independent determinants of cognition. Brain, 134(Pt 5), 1479–1492.

    Article  PubMed  Google Scholar 

  • Venneri, A., McGeown, W. J., Hietanen, H. M., Guerrini, C., Ellis, A. W., & Shanks, M. F. (2008). The anatomical bases of semantic retrieval deficits in early Alzheimer’s disease. Neuropsychologia, 46(2), 497–510.

    Article  PubMed  Google Scholar 

  • Wager, T. D., Jonides, J., & Reading, S. (2004). Neuroimaging studies of shifting attention: a meta-analysis. NeuroImage, 22(4), 1679–1693.

    Article  PubMed  Google Scholar 

  • Walhovd, K. B., Fjell, A. M., Brewer, J., McEvoy, L. K., Fennema-Notestine, C., Hagler, D. J., Jr., et al. (2010). Combining MR imaging, positron-emission tomography, and CSF biomarkers in the diagnosis and prognosis of Alzheimer disease. AJNR. American Journal of Neuroradiology, 31(2), 347–354.

    Article  PubMed  CAS  Google Scholar 

  • Walhovd, K. B., Fjell, A. M., Dale, A. M., McEvoy, L. K., Brewer, J., Karow, D. S., et al. (2010). Multi-modal imaging predicts memory performance in normal aging and cognitive decline. Neurobiology of Aging, 31(7), 1107–1121.

    Article  PubMed  CAS  Google Scholar 

  • Wechsler, D. (1981). Wechsler Adult Intelligence Scale-Revised. The Psychological Corporation.

  • Wechsler, D. (1987). Wechsler Memory Scale—revised. New York: Psychological Association.

    Google Scholar 

  • Weiner, M. W., Aisen, P. S., Jack, C. R., Jr., Jagust, W. J., Trojanowski, J. Q., Shaw, L., et al. (2010). The Alzheimer’s disease neuroimaging initiative: progress report and future plans. Alzheimers Dement, 6(3), 202–211 e207.

    Google Scholar 

  • Weiner, M. W., Veitch, D. P., Aisen, P. S., Beckett, L. A., Cairns, N. J., Green, R. C., et al. (2011). The Alzheimer’s Disease Neuroimaging Initiative: a review of papers published since its inception. Alzheimers Dement.

  • Wolk, D. A., & Dickerson, B. C. (2010). Apolipoprotein E (APOE) genotype has dissociable effects on memory and attentional-executive network function in Alzheimer’s disease. Proceedings of the National Academy of Sciences of the United States of America, 107(22), 10256–10261.

    Article  PubMed  CAS  Google Scholar 

  • Wolk, D. A., & Dickerson, B. C. (2011). Fractionating verbal episodic memory in Alzheimer’s disease. NeuroImage, 54(2), 1530–1539.

    Article  PubMed  Google Scholar 

  • Wolz, R., Heckemann, R. A., Aljabar, P., Hajnal, J. V., Hammers, A., Lotjonen, J., et al. (2010). Measurement of hippocampal atrophy using 4D graph-cut segmentation: application to ADNI. NeuroImage, 52(1), 109–118.

    Article  PubMed  Google Scholar 

  • Zakzanis, K. K., Graham, S. J., & Campbell, Z. (2003). A meta-analysis of structural and functional brain imaging in dementia of the Alzheimer’s type: a neuroimaging profile. Neuropsychology Review, 13(1), 1–18.

    Article  PubMed  Google Scholar 

  • Zakzanis, K. K., Mraz, R., & Graham, S. J. (2005). An fMRI study of the Trail Making Test. Neuropsychologia, 43(13), 1878–1886.

    Article  PubMed  Google Scholar 

  • Zhang, N., Song, X., Zhang, Y., Chen, W., D’Arcy, R. C., Darvesh, S., et al. (2011). An MRI brain atrophy and lesion index to assess the progression of structural changes in Alzheimer’s disease, mild cognitive impairment, and normal aging: a follow-up study. Journal of Alzheimer’s Disease, 26(Suppl 3), 359–367.

    PubMed  CAS  Google Scholar 

Download references

Acknowledgments

Data collection and sharing for this project was funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Abbott; Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Amorfix Life Sciences Ltd.; AstraZeneca; Bayer HealthCare; 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.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are 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 California, Los Angeles. This research was also supported by NIH grants P30 AG010129, K01 AG030514, and the Dana Foundation.

Data analysis was begun at the 2011 Conference on Advanced Psychometric Methods in Cognitive Aging Research, with conference grant support from the National Institute on Aging (NIA) R13 AG030995 (Mungas). Additional support for data management and the specific analyses reported here were provided by NIA R01 AG19771 (Saykin), P30 AG10133 (Saykin/Ghetti), R01 AG029672 (Crane), U01 AG024904 and P30 AG10129 (DeCarli), NSF IIS-1117335 (Shen), and P50 AG05136 (Raskind). SL Risacher was supported by a Clinical and Translational Science Institute (CTSI) Pre-doctoral Training Grant (TL1 RR025759).

Author information

Authors and Affiliations

  1. Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA

    Kwangsik Nho, Shannon L. Risacher, Sungeun Kim, Li Shen, John D. West & Andrew J. Saykin

  2. Department of Medicine, University of Washington, Seattle, WA, USA

    Paul K. Crane & Shubhabrata Mukherjee

  3. Department of Neurology and the Center for Neuroscience, School of Medicine, University of California Davis, Davis, CA, USA

    Charles DeCarli

  4. Department of Society, Human Development and Health, Harvard School of Public Health, Boston, MA, USA

    M. Maria Glymour

  5. Cognitive Neuroscience Division of Taub Institute for the Study of Alzheimer’s Disease and Aging Brain, Columbia University College of Physicians and Surgeons, New York, NY, USA

    Christian Habeck

  6. Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA

    Grace J. Lee

  7. Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA

    Elizabeth Mormino

Authors
  1. Kwangsik Nho
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shannon L. Risacher
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Paul K. Crane
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Charles DeCarli
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. M. Maria Glymour
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Christian Habeck
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Sungeun Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Grace J. Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Elizabeth Mormino
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Shubhabrata Mukherjee
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Li Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. John D. West
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Andrew J. Saykin
    View author publications

    You can also search for this author in PubMed Google Scholar

Consortia

Alzheimer’s Disease Neuroimaging Initiative (ADNI)

Corresponding author

Correspondence to Andrew J. Saykin.

Additional information

Kwangsik Nho and Shannon L. Risacher contributed equally to this work.

Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (www.adni.loni.ucla.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.ucla.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nho, K., Risacher, S.L., Crane, P.K. et al. Voxel and surface-based topography of memory and executive deficits in mild cognitive impairment and Alzheimer’s disease. Brain Imaging and Behavior 6, 551–567 (2012). https://doi.org/10.1007/s11682-012-9203-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11682-012-9203-2

Keywords

Search

Navigation