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Metastability in Senescence.

Shruti Naik1, Arpan Banerjee2, Raju S Bapi3

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Trends in Cognitive Sciences
|May 14, 2017
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Summary
This summary is machine-generated.

Healthy aging involves brain changes and stable cognition, but lacks a unified theory. We propose metastability, a framework explaining brain variability, to unify aging research and empirical findings.

Keywords:
healthy agingmetastabilitywhole-brain computational modeling

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Area of Science:

  • Neuroscience
  • Computational Modeling
  • Cognitive Aging

Background:

  • Healthy aging shows brain structural decline alongside preserved cognitive function.
  • Functional brain networks reorganize during aging, with theories debating beneficial or detrimental effects.
  • A cohesive explanation for age-related dynamic brain processes is currently lacking.

Purpose of the Study:

  • To propose a novel hypothesis for understanding the continuous aging process.
  • To bridge the gap between existing neurocognitive theories of aging and empirical evidence.
  • To leverage whole-brain computational modeling for a systematic account of brain variability.

Main Methods:

  • Utilizing recent advancements in whole-brain computational modeling.
  • Applying the theoretical framework of metastability to brain aging.
  • Systematically accounting for brain variability across the lifespan.

Main Results:

  • The study hypothesizes that metastability provides a unified explanation for aging-related brain dynamics.
  • Metastability offers a framework to systematically account for brain variability during aging.
  • This approach aims to reconcile conflicting theories and empirical findings in cognitive aging research.

Conclusions:

  • The metastability hypothesis offers a promising theoretical framework for understanding healthy brain aging.
  • Computational modeling and metastability can unify diverse findings on age-related cognitive and neural changes.
  • This approach provides a systematic account of brain variability throughout the lifespan.