Research Paper Advance Articles pp 24101—24116
Predicting the outcome of non-pharmacological treatment for patients with dementia-related mild cognitive impairment
- 1 Precision Medicine Centre, Hokuto Hospital, Obihiro 080-0833, Hokkaido, Japan
- 2 MEG Centre, Kumagaya General Hospital, Kumagaya 360-8567, Saitama, Japan
- 3 Biomedical Engineering Group, Higher Technical School of Telecommunications Engineering, University of Valladolid, Valladolid 47011, Castilla y León, Spain
- 4 Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Valladolid 47011, Castilla y León, Spain
- 5 Instituto de Investigación en Matemáticas (IMUVA), University of Valladolid, Valladolid 47011, Castilla y León, Spain
- 6 The Dementia Center, Institute of Brain and Vessels Mihara Memorial Hospital, Isehara 372-0006, Gunma, Japan
- 7 Isesaki Clinic, Gunma, Isehara 372-0056, Gunma, Japan
Received: September 5, 2020 Accepted: November 8, 2020 Published: December 7, 2020https://doi.org/10.18632/aging.202270
How to Cite
Copyright: © 2020 Shigihara et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Dementia is a progressive cognitive syndrome, with few effective pharmacological treatments that can slow its progress. Hence, non-pharmacological treatments (NPTs) play an important role in improving patient symptoms and quality of life. Designing the optimal personalised NPT strategy relies on objectively and quantitatively predicting the treatment outcome. Magnetoencephalography (MEG) findings can reflect the cognitive status of patients with dementia, and thus potentially predict NPT outcome. In the present study, 16 participants with cognitive impairment underwent NPT for several months. Their cognitive performance was evaluated based on the Mini-Mental State Examination and the Alzheimer's Disease Assessment Scale - Cognitive at the beginning and end of the NPT period, while resting-state brain activity was evaluated using MEG during the NPT period. Our results showed that the spectral properties of MEG signals predicted the changes in cognitive performance scores. High frequency oscillatory intensity at the right superior frontal gyrus medial segment, opercular part of the inferior frontal gyrus, triangular part of the inferior frontal gyrus, post central gyrus, and angular gyrus predicted the changes in cognitive performance scores. Thus, resting-state brain activity may be a powerful tool in designing personalised NPT.