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Updated: Dec 16, 2025

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
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tDCS effects on brain network properties during physiological aging.

Fabrizio Vecchio1, Francesca Miraglia2, Claudia Rodella3

  • 1Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Pisana, Via Val Cannuta, 247, 00166, Rome, Italy. fabrizio.vecchio@uniroma1.it.

Pflugers Archiv : European Journal of Physiology
|July 6, 2020
PubMed
Summary
This summary is machine-generated.

Transcranial direct current stimulation (tDCS) can alter brain network dynamics in aging. This study used EEG and graph theory to analyze tDCS effects on young and elderly brain networks, revealing polarity-dependent changes.

Keywords:
AgingFunctional connectivityGraph theory-EEGRehabilitationtDCS

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Biomedical Engineering

Background:

  • Physiological aging alters brain neural networks, impacting cognitive functions.
  • Non-invasive brain stimulation, like transcranial direct current stimulation (tDCS), shows potential for modulating cognitive functions in aging.
  • Network properties such as segregation, integration, and Small World (SW) parameters are crucial for understanding brain function in aging and neurodegeneration.

Purpose of the Study:

  • To systematically investigate the effects of tDCS on brain network properties in physiological aging.
  • To explore polarity-dependent changes in age-related network dynamics using graph theory.
  • To analyze tDCS-induced effects on brain network organization in young and elderly individuals.

Main Methods:

  • Cortical activity was recorded using electroencephalography (EEG) from healthy young and elderly subjects.
  • Participants underwent anodal, cathodal, or sham tDCS over the left prefrontal cortex (PFC) in separate sessions.
  • Graph theory analysis, including the Small World (SW) parameter, was applied to EEG data to evaluate brain network organization.

Main Results:

  • tDCS applied to the PFC can modify brain network dynamics.
  • EEG-tDCS coregistration data, analyzed with graph theory, revealed polarity-dependent effects.
  • The study demonstrated changes in brain network organization influenced by tDCS in both young and elderly participants.

Conclusions:

  • tDCS is a viable tool for modulating brain network dynamics in physiological aging.
  • Graph theory analysis of tDCS-EEG data provides insights into age-dependent network changes.
  • Understanding these tDCS-induced effects is crucial for potential interventions in aging and neurodegenerative conditions.