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Related Concept Videos

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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Brain-computer-interface-based intervention increases brain functional segregation in cognitively normal older

Xing Qian1, Kwun Kei Ng1, Si Ning Yeo2

  • 1Centre for Sleep and Cognition and Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.

Age and Ageing
|September 18, 2025
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Summary
This summary is machine-generated.

Brain-computer interface (BCI) cognitive training may enhance brain network organization in older adults. This training promotes brain network segregation, potentially supporting cognitive functions like memory and language.

Keywords:
ageingbrain-computer-interface-based interventionfMRIfunctional connectivitynetworkolder people

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Aging Research

Background:

  • Brain-computer interface (BCI) cognitive training shows potential for enhancing cognition in older adults.
  • Neural mechanisms underlying BCI training benefits are not fully understood.
  • Investigating brain network alterations is crucial for understanding BCI efficacy.

Purpose of the Study:

  • To investigate topological changes in intrinsic brain functional networks after BCI-based cognitive training.
  • To examine the relationship between these network changes and cognitive performance in healthy older adults.
  • To elucidate the neural underpinnings of BCI training in aging.

Main Methods:

  • Resting-state functional magnetic resonance imaging (fMRI) was used to capture brain activity.
  • Graph theoretical analysis was applied to assess brain network topology.
  • A comparison was made between an intervention (INT) group and a waitlist (WL) control group.

Main Results:

  • The INT group showed increased functional brain network segregation and modularity.
  • Reduced nodal participation coefficients were observed, particularly in control and subcortical networks.
  • While no significant behavioral improvements were found, specific network changes correlated with cognitive improvements (language, memory).

Conclusions:

  • BCI-based cognitive training may help maintain brain network organization in aging adults.
  • Enhanced functional network segregation appears to be a key mechanism.
  • These network changes offer insights into how BCI training supports cognitive function in older adults.