Impact of brain aging and neurodegeneration on cognition: Evidence from mri

Current Opinion in Neurology

Volumn 26, Issue 6, 2013, Pages 640-645

  Draganski, Bogdan ^a,b   Lutti, Antoine ^a   Kherif, Ferath ^a  

^a LAUSANNE UNIVERSITY HOSPITAL   (Switzerland)

^b MAX PLANCK INSTITUTE FOR HUMAN COGNITIVE AND BRAIN SCIENCES   (Germany)

Author keywords

Aging; Alzheimer's disease; Amyloid; Cortical thickness; Functional MRI; Neurodegeneration; Voxel based morphometry

Indexed keywords

AMYLOID BETA PROTEIN; PRESENILIN 1;

AGING; ALZHEIMER DISEASE; BOLD SIGNAL; BRAIN AGING; BRAIN ATROPHY; BRAIN FUNCTION; BRAIN INJURY; BRAIN REGION; BRAIN SIZE; CEREBROSPINAL FLUID; CLASSIFICATION ALGORITHM; COGNITIVE DEFECT; COGNITIVE RESERVE; COMPUTATIONAL ANATOMY; CORTICAL THICKNESS (BRAIN); DIFFUSION WEIGHTED IMAGING; EPISODIC MEMORY; FUNCTIONAL MAGNETIC RESONANCE IMAGING; GENE MUTATION; GRAY MATTER; HUMAN; NERVE DEGENERATION; NEUROANATOMY; NEUROCHEMISTRY; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; PROTEIN BLOOD LEVEL; PROTEIN CEREBROSPINAL FLUID LEVEL; REVIEW; VASCULAR AMYLOIDOSIS; VOXEL BASED MORPHOMETRY; WHITE MATTER; ANATOMY AND HISTOLOGY; BRAIN; COGNITION DISORDERS; COMPLICATION; PATHOLOGY;

AGING; BRAIN; COGNITION DISORDERS; HUMANS; NERVE DEGENERATION;

EID: 84892373531     PISSN: 13507540     EISSN: 14736551     Source Type: Journal    
DOI: 10.1097/WCO.0000000000000029     Document Type: Review

References (44)

1. Ashburner J. Computational anatomy with the SPM software. Magn Reson Imaging 2009; 27:1163-1174.
2. Hutton C, Draganski B, Ashburner J, Weiskopf N. A comparison between voxel-based cortical thickness and voxel-based morphometry in normal aging. Neuroimage 2009; 48:371-380.
3. Dale AM, Fischl B, Sereno MI. Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage 1999; 9:179-194.
4. Fischl B, Sereno MI, Dale AM. Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system. Neuroimage 1999; 9:195-207.
5. Salat DH, Lee SY, van der Kouwe AJ, et al. Age-associated alterations in cortical gray and white matter signal intensity and gray to white matter contrast. Neuroimage 2009; 48:21-28.
6. .Weiskopf N, Suckling J, Williams G, et al. Quantitative multiparameter mapping of R1, PD(*), MT, and R2(*) at 3T: A multicenter validation. Front Neurosci 2013; 7:95.
7. .Lutti A, Dick F, Sereno MI, Weiskopf N. Using high-resolution quantitative mapping of R1 as an index of cortical myelination. Neuroimage 2013. +AFs-Epub ahead of print+AF0-
8. Draganski B, Ashburner J, Hutton C, et al. Regional specificity of MRI contrast parameter changes in normal ageing revealed by voxel-based quantification (VBQ). Neuroimage 2011; 55:1423-1434.
9. Pierpaoli C, Basser PJ. Toward a quantitative assessment of diffusion anisotropy. Magn Reson Med 1996; 36:893-906.
10. Concha L, Livy DJ, Beaulieu C, et al. In vivo diffusion tensor imaging and histopathology of the fimbria-fornix in temporal lobe epilepsy. J Neurosci 2010; 30:996-1002.
11. Douaud G, Jbabdi S, Behrens TE, et al. DTI measures in crossing-fibre areas: Increased diffusion anisotropy reveals early white matter alteration in MCI and mild Alzheimer's disease. Neuroimage 2011; 55:880-890.
12. Logothetis NK, Pauls J, Augath M, et al. Neurophysiological investigation of the basis of the fMRI signal. Nature 2001; 412:150-157.
13. Viswanathan A, Freeman RD. Neurometabolic coupling in cerebral cortex reflects synaptic more than spiking activity. Nat Neurosci 2007; 10:1308- 1312.
14. Friston KJ, Penny W, Phillips C, et al. Classical and Bayesian inference in neuroimaging: Theory. Neuroimage 2002; 16:465-483.
15. .Buckner RL, Krienen FM, Yeo BT. Opportunities and limitations of intrinsic functional connectivity MRI. Nat Neurosci 2013; 16:832-837.
16. Power JD, Barnes KA, Snyder AZ, et al. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 2012; 59:2142-2154.
17. Gauthier CJ, Madjar C, Desjardins-Crepeau L, et al. Age dependence of hemodynamic response characteristics in human functional magnetic resonance imaging. Neurobiol Aging 2013; 34:1469-1485.
18. Cabeza R, Nyberg L, Park D. Cognitive neuroscience of aging: linking cognitive and cerebral aging. Cabeza R, Nyberg L, Park D, editors. New York, New York: Oxford University Press; 2004.
19. Wilson RS, Beckett LA, Barnes LL, et al. Individual differences in rates of change in cognitive abilities of older persons. Psychol Aging 2002; 17:179- 193.
20. Ronnlund M, Nyberg L, Backman L, Nilsson LG. Stability, growth, and decline in adult life span development of declarative memory: Cross-sectional and longitudinal data from a population-based study. Psychol Aging 2005; 20:3-18.
21. Ronnlund M, Karlsson E. The relation between dimensions of attachment and internalizing or externalizing problems during adolescence. J Genet Psychol 2006; 167:47-63.
22. Ronnlund M, Mantyla T, Nilsson LG. The Prospective and Retrospective Memory Questionnaire (PRMQ): factorial structure, relations to global subjective memory ratings, and Swedish norms. Scand J Psychol 2008; 49:11- 18.
23. Ronnlund M, Lovden M, Nilsson LG. Cross-sectional versus longitudinal age gradients of tower of Hanoi performance: The role of practice effects and cohort differences in education. Neuropsychol Dev Cogn B Aging Neuropsychol Cogn 2008; 15:40-67.
24. Stern Y. What is cognitive reserve? Theory and research application of the reserve concept. J Int Neuropsychol Soc 2002; 8:448-460.
25. KalpouzosG, Persson J, Nyberg L. Local brain atrophy accounts for functional activity differences in normal aging. Neurobiol Aging 2012; 33:623-623; e1-13.
26. .Persson J, Pudas S, Lind J, et al. Longitudinal structure function correlates in elderly reveal MTL dysfunction with cognitive decline. Cereb Cortex 2012; 22:2297-2304.
27. .Pudas S, Persson J, Josefsson M, et al. Brain characteristics of individuals resisting age-related cognitive decline over two decades. J Neurosci 2013; 33:8668-8677.
28. Hyman BT, Phelps CH, Beach TG, et al. National Institute on Aging- Alzheimer's Association guidelines for the neuropathologic assessment of Alzheimer's disease. Alzheimers Dement 2012; 8:1-13.
29. Morris JC, Roe CM, Xiong C, et al. APOE predicts amyloid-beta but not tau Alzheimer pathology in cognitively normal aging. Ann Neurol 2010; 67:122-131.
30. Dukart J, Kherif F, Mueller K, et al. Generative FDG-PET and MRI model of aging and disease progression in Alzheimer's disease. PLoS Comput Biol 2013; 9:e1002987.
31. Fjell AM, McEvoy L, Holland D, et al. Brain changes in older adults at very low risk for Alzheimer's disease. J Neurosci 2013; 33:8237-8242.
32. Muller U, Winter P, Graeber MB. A presenilin 1 mutation in the first case of Alzheimer's disease. Lancet Neurol 2013; 12:129-130.
33. Hardy J. The amyloid hypothesis for Alzheimer's disease: A critical reappraisal. J Neurochem 2009; 110:1129-1134.
34. Jack CR Jr, Knopman DS, Jagust WJ, et al. Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade. Lancet Neurol 2010; 9:119-128.
35. Reiman EM, Quiroz YT, Fleisher AS, et al. Brain imaging and fluid biomarker analysis in young adults at genetic risk for autosomal dominant Alzheimer's disease in the presenilin 1 E280A kindred: A case-control study. Lancet Neurol 2012; 11:1048-1056.
36. Knopman DS. Alzheimer disease biomarkers and insights into mild cognitive impairment. Neurology 2013; 80:978-980.
37. Oh H, Madison C, Villeneuve S, et al. Association of gray matter atrophy with age, beta-amyloid, and, cognition in aging. Cereb Cortex 2013. [Epub ahead of print]
38. Hedden T, Mormino EC, Amariglio RE, et al. Cognitive profile of amyloid burden and white matter hyperintensities in cognitively normal older adults. J Neurosci 2012; 32:16233-16242.
39. Hedden T, Van Dijk KR, Shire EH, et al. Failure to modulate attentional control in advanced aging linked to white matter pathology. Cereb Cortex 2012; 22:1038-1051.
40. Wirth M, Madison CM, Rabinovici GD, et al. Alzheimer's disease neurodegenerative biomarkers are associated with decreased cognitive function but not beta-amyloid in cognitively normal older individuals. J Neurosci 2013; 33:5553-5563.
41. Klostermann EC, Braskie MN, Landau SM, et al. Dopamine and frontostriatal networks in cognitive aging. Neurobiol Aging 2012; 33:623; e15-24.
42. Chowdhury R, Guitart-Masip M, Bunzeck N, et al. Dopamine modulates episodic memory persistence in old age. J Neurosci 2012; 32:14193-14204.
43. Chowdhury R, Guitart-Masip M, Lambert C, et al. Dopamine restores reward prediction errors in old age. Nat Neurosci 2013; 16:648653.
44. .Jack CR Jr, Knopman DS, Jagust WJ, et al. Tracking pathophysiological processes in Alzheimer's disease: An updated hypothetical model of dynamic biomarkers. Lancet Neurol 2013; 12:207-216.