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Gray matter atrophy pattern in elderly with subjective memory impairment
Abstract
Background: Individuals with subjective memory impairment (SMI) report worsening of memory without impairment in cognitive tests. Despite normal cognitive performance, they may be at higher risk of cognitive decline compared with individuals without SMI. Methods: We used a discriminative function (a support vector machine) trained on an independent data set of 226 healthy control subjects and 191 patients with probable Alzheimer's disease (AD) dementia to characterize the baseline gray matter patterns of 24 individuals with SMI and 53 control subjects. We tested for associations of these gray matter patterns with SMI presence, cognitive performance at baseline, and cognitive decline at follow‐up. Results: Individuals with SMI showed greater similarity to an AD gray matter pattern compared with control subjects without SMI. In addition, episodic memory decline was associated with an AD gray matter pattern in the SMI group. Conclusions: Our results indicate a link between the gray matter atrophy pattern of patients with AD and the presence of SMI. Furthermore, multivariate pattern recognition approaches seem to be a sensitive method for identifying subtle brain changes that correspond to future memory decline in SMI.
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“The researchers trained a classifier to separate individuals with dementia due to AD from HCs and found that the gray matter atrophy pattern of a subject with SCD was similar to the brain of a patient with dementia due to AD but was significantly different from an HC. The voxels with greatest contributions to the classification were mainly distributed in hippocampal and parahippocampal areas.”
From Neuroimaging advances regarding subjective cognitive decline in preclinical Alzheimer's disease (2020) · cites this paper as [95]
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“Peter and colleagues used similar methods and showed that the extracted index was higher in individuals with SCD than in HCs [95].”
From Neuroimaging advances regarding subjective cognitive decline in preclinical Alzheimer's disease (2020) · cites this paper as [95]
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Metadata
- Authors
- Peter, J., Scheef, L., Abdulkadir, A., Boecker, H., Heneka, M., Wagner, M., Koppara, A., Klöppel, S., Jessen, F., & Initiative, A. D. N.
- Affiliations
- University of Freiburg (DE)
- University Hospital Bonn (DE)
- University of Bonn (DE)
- University Medical Center Freiburg (DE)
- Corresponding author
- Peter, Jessica
- ORCID
- Venue
- Alzheimer's & Dementia
- Publisher
- Wiley
- Published
- 2013-07-17
- Volume
- 10
- Issue
- 1
- Pages
- 99-108
- ISSN
- 1552-5260 (ISSN-L)
- 1552-5279
- OpenAlex
- W2062151508
- Cited by
- 165
- References
- 53
- Citations by year
- 2026: 3 · 2025: 9 · 2024: 14 · 2023: 6 · 2022: 12 · 2021: 19 · 2020: 15 · 2019: 20 · 2018: 15 · 2017: 17 · 2016: 13 · 2015: 12 · 2014: 9 · 2013: 1
- FWCI
- 8.30
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Alzheimer s & Dementia (publishedVersion)
- PubMed (publishedVersion)
- Open Repository and Bibliography (University of Luxembourg) (submittedVersion)
- DZNE Pub (submittedVersion)
- Funders
- Deutsche Forschungsgemeinschaft (KL 2415/2‐1)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Oncology › Cancer-related cognitive impairment studies
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Keywords
- subjective memory impairment, gray matter atrophy
- MeSH terms
- Aged, Atrophy, Brain, Cognition Disorders, Cross-Sectional Studies, Female, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Memory Disorders, Middle Aged, Neuropsychological Tests, ROC Curve, Imaging, Three-Dimensional, Support Vector Machine
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