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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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Developing digital biomarker for predicting cognitive response to multi-domain intervention.

Ji Hyeun Park1, Hyun Sook Kim2, Seong Hye Choi3

  • 1Medical division, Rowan, Cheonan, South Korea.

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A new digital biomarker, Reaction Time-Accuracy Correlation (RTACC), shows promise in identifying individuals with mild cognitive impairment who may benefit from multi-domain interventions for cognitive health.

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Area of Science:

  • Digital biomarkers in cognitive health
  • Neuroscience of aging
  • Computational psychiatry

Background:

  • Computerized cognitive training generates performance metrics usable as digital biomarkers.
  • Mild cognitive impairment (MCI) presents challenges for early detection and intervention.
  • Multi-domain interventions aim to improve cognitive function and well-being in individuals with MCI.

Purpose of the Study:

  • To investigate the utility of a novel in-game digital biomarker, Reaction Time-Accuracy Correlation (RTACC), in participants with MCI.
  • To assess the association of RTACC with cognitive outcomes and biomarker changes following a multi-domain intervention.
  • To determine if RTACC can help identify individuals who respond well to intervention.

Main Methods:

  • Utilized data from 130 participants with MCI in the SUPERBRAIN-MEET randomized controlled trial.
  • Calculated RTACC from task-level reaction time and accuracy data.
  • Employed linear and logistic regression analyses to examine RTACC's relationship with cognitive scores (RBANS) and brain-derived neurotrophic factor (BDNF) levels.
  • Evaluated RTACC's ability to predict good responders when combined with clinical information.

Main Results:

  • RTACC significantly correlated with improvements in Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) scores over 24 weeks (p=0.002).
  • RTACC demonstrated a marginal association with changes in brain-derived neurotrophic factor (BDNF) levels (p=0.057).
  • RTACC, alongside clinical data, achieved an area under the ROC curve of 0.73 for identifying good responders.

Conclusions:

  • The novel digital biomarker RTACC shows potential for monitoring cognitive changes in individuals with MCI.
  • RTACC may serve as a valuable tool to identify individuals likely to benefit from multi-domain interventions.
  • Further research can explore RTACC's application in diverse populations and intervention settings.