The DOI matches its Crossref record; 68 of the 68 references it cites were found in a registry or an index.
The topography of grey matter involvement in early and late onset Alzheimer's disease
Open accessAbstract
Clinical observations have suggested that the neuropsychological profile of early and late onset forms of Alzheimer's disease (EOAD and LOAD) differ in that neocortical functions are more affected in the former and learning in the latter, suggesting that they might be different diseases. The aim of this study is to assess the brain structural basis of these observations, and test whether neocortical areas are more heavily affected in EOAD and medial temporal areas in LOAD. Fifteen patients with EOAD and 15 with LOAD (onset before and after age 65; Mini Mental State Examination 19.8, SD 4.0 and 20.7, SD 4.2) were assessed with a neuropsychological battery and high-resolution MRI together with 1:1 age- and sex-matched controls. Cortical atrophy was assessed with cortical pattern matching, and hippocampal atrophy with region-of-interest-based analysis. EOAD patients performed more poorly than LOAD on visuospatial, frontal-executive and learning tests. EOAD patients had the largest atrophy in the occipital [25% grey matter (GM) loss in the left and 24% in the right hemisphere] and parietal lobes (23% loss on both sides), while LOAD patients were remarkably atrophic in the hippocampus (21 and 22% loss). Hippocampal GM loss of EOAD (9 and 16% to the left and right) and occipital (12 and 14%) and parietal (13 and 12%) loss of LOAD patients were less marked. In EOAD, GM loss of 25% or more was mapped to large neocortical areas and affected all lobes, with relative sparing of primary sensory, motor, and visual cortex, and anterior cingulate and orbital cortex. In LOAD, GM loss was diffusely milder (below 15%); losses of 15-20% were confined to temporoparietal and retrosplenial cortex, and reached 25% in restricted areas of the medial temporal lobe and right superior temporal gyrus. These findings indicate that EOAD and LOAD differ in their typical topographic patterns of brain atrophy, suggesting different predisposing or aetiological factors.
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Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975) · Journal of Psychiatric Research · doi:10.1016/0022-3956(75)90026-6 · Cited by 88,282
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984) · Neurology · doi:10.1212/wnl.34.7.939 · Cited by 27,915
Validity of the Trail Making Test as an Indicator of Organic Brain Damage
Reitan, R. M. (1958) · Perceptual and Motor Skills · doi:10.2466/pms.1958.8.3.271 · Cited by 7,928
A New Clinical Scale for the Staging of Dementia
Hughes, C. P., Berg, L., Danziger, W., Coben, L. A., & Martin, R. L. (1982) · British Journal of Psychiatry · doi:10.1192/bjp.140.6.566 · Cited by 7,056
Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space
Collins, D. L., Neelin, P., Peters, T. M., & Evans, A. C. (1994) · Journal of Computer Assisted Tomography · doi:10.1097/00004728-199403000-00005 · Cited by 3,431 · cited 1×
“Processing includes correction for magnetic field non-uniformities, intensity normalization and brain-to-brain linear registration to a standard template in the stereotaxic space (ICBM152) based on the Talairach atlas (Collins et al., 1994).”
MethodContributions of anterior cingulate cortex to behaviour
Devinsky, O., Morrell, M. J., & Vogt, B. A. (1995) · Brain · doi:10.1093/brain/118.1.279 · Cited by 3,377
Restriction isotyping of human apolipoprotein E by gene amplification and cleavage with HhaI.
Hixson, J., & Vernier, D. (1990) · Journal of Lipid Research · doi:10.1016/s0022-2275(20)43176-1 · Cited by 2,933
THE TOKEN TEST: A SENSITIVE TEST TO DETECT RECEPTIVE DISTURBANCES IN APHASICS
DE RENZI, E., & VIGNOLO, L. A. (1962) · Brain · doi:10.1093/brain/85.4.665 · Cited by 1,862
A New Rating Scale for Age-Related White Matter Changes Applicable to MRI and CT
Wahlund, L. O., Barkhof, F., Fazekas, F., Bronge, L., Augustin, M., Sjögren, M., Wallin, A., Ader, H., Leys, D., Pantoni, L., et al. (2001) · Stroke · doi:10.1161/01.str.32.6.1318 · Cited by 1,797
Vogt, B. A., Finch, D. M., & Olson, C. R. (1992) · Cerebral Cortex · doi:10.1093/cercor/2.6.435-a · Cited by 1,315
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Dubois, B., Feldman, H. H., Jacova, C., Hampel, H., Molinuevo, J. L., Blennow, K., DeKosky, S. T., Gauthier, S., Selkoe, D., Bateman, R., et al. (2014) · The Lancet Neurology · doi:10.1016/s1474-4422(14)70090-0 · Cited by 3,321
Self-citationAmyloid-β–induced neuronal dysfunction in Alzheimer's disease: from synapses toward neural networks
Palop, J. J., & Mucke, L. (2010) · Nature Neuroscience · doi:10.1038/nn.2583 · Cited by 1,651
Automatic classification of MR scans in Alzheimer’s disease.
Kloppel, S., Stonnington, C. M., Chu, C., Draganski, B., Scahill, R. I., Rohrer, J. D., Fox, N. C., Jack, C. R., Ashburner, J., & Frackowiak, R. S. J. (2008) · Brain · doi:10.1093/brain/awm319 · Cited by 1,170
Fox, K. C. R., Nijeboer, S., Dixon, M. L., Floman, J. L., Ellamil, M., Rumak, S. P., Sedlmeier, P., & Christoff, K. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.03.016 · Cited by 804
Brain atrophy in Alzheimer’s Disease and aging
Pini, L., Pievani, M., Bocchetta, M., Altomare, D., Bosco, P., Cavedo, E., Galluzzi, S., Marizzoni, M., & Frisoni, G. B. (2016) · Ageing Research Reviews · doi:10.1016/j.arr.2016.01.002 · Cited by 836
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Metadata
- Authors
- Frisoni, G. B., Pievani, M., Testa, C., Sabattoli, F., Bresciani, L., Bonetti, M., Beltramello, A., Hayashi, K. M., Toga, A. W., & Thompson, P. M.
- Venue
- Brain
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-02-09
- Volume
- 130
- Issue
- 3
- Pages
- 720-730
- ISSN
- 0006-8950 (ISSN-L)
- 1460-2156
- OpenAlex
- W2106217904
- Cited by
- 435
- References
- 68
- FWCI
- 12.38
- Type
- journal article
- Language
- en
- Open access
- green
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