The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
Amygdala atrophy is prominent in early Alzheimer's disease and relates to symptom severity
Open accessAbstract
Despite numerous studies on the role of medial temporal lobe structures in Alzheimer's disease (AD), the magnitude and clinical significance of amygdala atrophy has been relatively sparsely investigated. In this study we compared the level of amygdala atrophy to that of the hippocampus in very mild and mild AD subjects in two large samples (Sample 1 n=90; Sample 2 n=174). Using a series of linear regression analyses, we investigated whether amygdala atrophy is related to global cognitive functioning (Clinical Dementia Rating Sum of Boxes: CDR-SB; Mini Mental State Examination: MMSE) and neuropsychiatric status. Results indicated that amygdala atrophy was comparable to hippocampal atrophy in both samples. MMSE and CDR-SB were strongly related to amygdala atrophy, with amygdala atrophy predicting MMSE scores as well as hippocampal atrophy, but predicting CDR-SB scores less robustly. Amygdala atrophy was related to aberrant motor behavior, with potential relationships to anxiety and irritability. These results suggest that the magnitude of amygdala atrophy is comparable to that of the hippocampus in the earliest clinical stages of AD, and is related to global illness severity. There also appear to be specific relationships between the level of amygdala atrophy and neuropsychiatric symptoms that deserve further investigation.
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Neurofibrillary tangles but not senile plaques parallel duration and severity of Alzheimer's disease
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Self-citationThinning of the Cerebral Cortex in Aging
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Self-citationAnxiety and affective style: role of prefrontal cortex and amygdala
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Cited by
Behavioral and psychological symptoms of dementia
Cerejeira, J., Lagarto, L., & Mukaetova-Ladinska, E. B. (2012) · Frontiers in Neurology · doi:10.3389/fneur.2012.00073 · Cited by 1,425
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
LaMontagne, P. J., Benzinger, T. L., Morris, J. C., Keefe, S., Hornbeck, R., Xiong, C., Grant, E., Hassenstab, J., Moulder, K., Vlassenko, A. G., et al. (2019) · medRxiv · doi:10.1101/2019.12.13.19014902 · Cited by 779
“…development of neuroimaging tools, such as brain atlases 3,4 , tissue segmentation algorithms 5 , and de-identification tools 6 , used to create models of healthy aging 7,8 and AD timecourse 7–11 , used to answer hypothesis driven questions 12,13 , and used for educational and training purposes.”
Self-citationSosna, J., Philipp, S., Albay, R., Reyes-Ruiz, J. M., Baglietto-Vargas, D., LaFerla, F. M., & Glabe, C. G. (2018) · Molecular Neurodegeneration · doi:10.1186/s13024-018-0244-x · Cited by 406
Weiner, M. W., Veitch, D. P., Aisen, P. S., Beckett, L. A., Cairns, N. J., Cedarbaum, J., Green, R. C., Harvey, D., Jack, C. R., Jagust, W., et al. (2015) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2014.11.001 · Cited by 348
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Metadata
- Authors
- Poulin, S. P., Dautoff, R., Morris, J. C., Barrett, L. F., & Dickerson, B. C.
- Venue
- Psychiatry Research: Neuroimaging
- Publisher
- Elsevier BV
- Published
- 2011-10
- Volume
- 194
- Issue
- 1
- Pages
- 7-13
- ISSN
- 0925-4927 (ISSN-L)
- OpenAlex
- W2151920318
- Cited by
- 448
- References
- 44
- FWCI
- 8.47
- Type
- journal article
- Language
- en
- Open access
- green
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