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Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach

Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach

Published on: February 14, 2014

Brain aging in the oldest-old.

A von Gunten¹, K Ebbing, A Imhof

¹Service Universitaire de Psychiatrie de l'Age Avancé (SUPAA), Department of Psychiatry of CHUV, University of Lausanne, Route du Mont, 1008 Prilly, Switzerland.

Current Gerontology and Geriatrics Research

|August 14, 2010

Summary

This summary is machine-generated.

Dementia in the oldest-old (nonagenarians and centenarians) differs from younger individuals, with distinct brain pathology patterns. Microvascular factors may predict cognitive decline in this aging population.

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Published on: March 23, 2011

Area of Science:

Neuropathology
Gerontology
Neuroscience

Background:

Nonagenarians and centenarians are a rapidly growing demographic.
Dementia prevalence increases with age, but its definition in the oldest-old is unclear.
The oldest-old may be relatively resistant to typical Alzheimer's disease (AD) brain changes.

Purpose of the Study:

To investigate the neuropathological differences in dementia in the oldest-old compared to younger individuals.
To identify potential determinants of cognitive decline in nonagenarians and centenarians.

Main Methods:

Comparative neuropathological analysis of brain aging markers (neurofibrillary tangles, senile plaques) in oldest-old and younger individuals.
Assessment of lesion distribution, neuronal loss, and microvascular parameters.
Correlation of pathological findings with cognitive status.

Main Results:

The oldest-old show distinct patterns of neurofibrillary tangle (NFT) distribution, with preferential involvement of the hippocampus (CA1 field) and relative sparing of association areas.
NFT progression and amyloid burden are lower in the oldest-old with dementia compared to younger AD cases.
Microvascular parameters, like mean capillary diameter, may be crucial for predicting cognitive decline in the oldest-old.

Conclusions:

Pathological substrates of cognitive deterioration differ significantly between the oldest-old and younger individuals.
Hippocampal NFT distribution and microvascular health are key factors in dementia development in extreme aging.
Further research into longevity-enabling genes may illuminate unique neuropathological adaptations in centenarians.