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The Cognitive Connectome in Healthy Aging.

Eloy Garcia-Cabello1, Lissett Gonzalez-Burgos1,2, Joana B Pereira2,3

  • 1Department of Clinical Psychology, Psychobiology and Methodology, Faculty of Psychology, University of La Laguna, La Laguna, Spain.

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Researchers explored the "cognitive connectome" in aging adults using graph theory. Findings show cognitive networks are stable, with executive functions and processing speed key to age-related changes.

Keywords:
agingcognitioncompensationconnectomedifferentiationgraph theory

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Area of Science:

  • Cognitive Neuroscience
  • Gerontology
  • Network Science

Background:

  • Cognitive aging research traditionally uses univariate and multivariate analyses.
  • Graph theory offers advanced methods to explore complex associations among cognitive variables.
  • The concept of a
  • cognitive connectome
  • has not been extensively studied in relation to aging.

Purpose of the Study:

  • To determine if cognitive functions form a structured network, termed the
  • cognitive connectome
  • .
  • To investigate how this cognitive connectome differs across age groups.

Main Methods:

  • Utilized graph theory to construct cognitive networks from 47 cognitive variables.
  • Analyzed data from 334 cognitively unimpaired individuals across three age groups: early-middle-age (37-50), late-middle-age (51-64), and elderly (65-78).
  • Employed global and nodal graph measures for group comparisons.

Main Results:

  • Identified a cognitive connectome comprising five modules: verbal memory, visual memory-visuospatial abilities, procedural memory, executive-premotor functions, and processing speed.
  • The elderly group exhibited reduced transitivity and average network strength, alongside increased global efficiency.
  • The late-middle-age group displayed decreased global and local efficiency and modularity compared to the early-middle-age group.

Conclusions:

  • A cognitive connectome structure is largely stable in healthy aging.
  • Executive functions and processing speed play crucial roles in age-related cognitive network differences.
  • Applying the connectome concept to cognitive data offers new insights into cognitive aging complexity.