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Related Concept Videos

Aging01:26

Aging

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Aging is a complex biological phenomenon influenced by various processes that affect cellular and systemic functions. Several prominent theories attempt to explain its mechanisms, highlighting cellular limitations, oxidative damage, and hormonal changes as central factors in aging.
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The cellular clock theory posits that the human lifespan is closely tied to the finite capacity of cells to divide, a phenomenon governed by telomeres, which are protective caps at the ends of...
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The Effect of Aging on Tissues01:19

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Several body functions deteriorate with age. The external signs of aging are easily identifiable. For example, the skin becomes dry, less elastic, and thins out, forming wrinkles. The skin of the face begins to appear looser due to a decrease in the levels of elastic and collagen fibers in the connective tissue. Additionally, melanin production in the hair follicle decreases with age, resulting in gray hair. Moreover, the senses of sight and hearing decline, so glasses and hearing aids may...
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Cognitive Development During Adulthood01:30

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Cognitive development continues throughout adulthood, undergoing significant shifts across early, middle, and late stages. Individual transition occurs from adolescent idealism to pragmatic and adaptable thinking in early adulthood. During this period, individuals learn to integrate personal beliefs with the recognition that other perspectives are equally valid. Exposure to the complexities of modern society, diverse experiences, and higher education contribute to this adaptive thought process,...
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Related Experiment Video

Updated: Feb 17, 2026

3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse
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A spatio-temporal reference model of the aging brain.

W Huizinga1, D H J Poot2, M W Vernooij3

  • 1Biomedical Imaging Group Rotterdam, Depts. of Radiology & Medical Informatics, Erasmus MC, Rotterdam, The Netherlands.

Neuroimage
|December 6, 2017
PubMed
Summary
This summary is machine-generated.

This study developed a novel method to model brain aging using MRI scans, helping distinguish normal aging from Alzheimer's disease. The model quanties accelerated brain aging, aiding in early diagnosis and understanding disease progression.

Keywords:
AgingBrain morphologyNon-rigid groupwise registrationPartial least squares regressionPercentile curvesSpatio-temporal atlas

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Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Gerontology

Background:

  • Brain morphological changes are common in normal aging and neurodegenerative diseases like Alzheimer's (AD).
  • Distinguishing these changes visually from MRI scans is challenging, hindering early diagnosis.
  • A quantitative model of brain aging is needed to aid differential diagnosis.

Purpose of the Study:

  • To develop a spatio-temporal model of brain morphological changes associated with normal aging.
  • To create a reference distribution of brain morphology as a function of age.
  • To enable the assessment of accelerated brain aging at population and individual levels.

Main Methods:

  • Utilized groupwise image registration to analyze morphological variation across different age groups.
  • Employed partial least squares regression to identify age-correlated deformation modes.
  • Fitted smooth percentile curves to age-scores to establish a normative aging trajectory.

Main Results:

  • The framework successfully extracted expected patterns of brain atrophy.
  • Morphology scores were significantly lower in cognitively normal subjects compared to AD patients.
  • Results suggest that accelerated aging contributes to morphological differences observed in AD.

Conclusions:

  • The developed method effectively models spatio-temporal brain aging using MRI data.
  • The model can identify accelerated brain aging, differentiating it from normal aging processes.
  • This approach aids in the diagnosis of neurodegenerative disorders by providing a quantitative measure of brain aging.