Mild cognitive impairment prediction and cognitive score regression in the elderly using EEG topological data analysis and machine learning with awareness assessed in affective reminiscent paradigm.

Journal: Frontiers in aging neuroscience
Published Date: Jan 4, 2024

Abstract

INTRODUCTION: The main objective of this study is to evaluate working memory and determine EEG biomarkers that can assist in the field of health neuroscience. Our ultimate goal is to utilize this approach to predict the early signs of mild cognitive impairment (MCI) in healthy elderly individuals, which could potentially lead to dementia. The advancements in health neuroscience research have revealed that affective reminiscence stimulation is an effective method for developing EEG-based neuro-biomarkers that can detect the signs of MCI.

Authors

  • Tomasz M Rutkowski
    RIKEN Center for Advanced Intelligence Project, Tokyo, Japan.
  • Tomasz Komendziński
    Department of Cognitive Science, Institute of Information and Communication Research, Nicolaus Copernicus University, Toruń, Poland.
  • Mihoko Otake-Matsuura
    RIKEN Center for Advanced Intelligence Project, Tokyo, Japan.

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