作者
Sebastian Moguilner, Adolfo M García, Yonatan Sanz Perl, Enzo Tagliazucchi, Olivier Piguet, Fiona Kumfor, Pablo Reyes, Diana Matallana, Lucas Sedeño, Agustín Ibáñez
发表日期
2021/1/15
期刊
Neuroimage
卷号
225
页码范围
117522
出版商
Academic Press
简介
From molecular mechanisms to global brain networks, atypical fluctuations are the hallmark of neurodegeneration. Yet, traditional fMRI research on resting-state networks (RSNs) has favored static and average connectivity methods, which by overlooking the fluctuation dynamics triggered by neurodegeneration, have yielded inconsistent results. The present multicenter study introduces a data-driven machine learning pipeline based on dynamic connectivity fluctuation analysis (DCFA) on RS-fMRI data from 300 participants belonging to three groups: behavioral variant frontotemporal dementia (bvFTD) patients, Alzheimer's disease (AD) patients, and healthy controls. We considered non-linear oscillatory patterns across combined and individual resting-state networks (RSNs), namely: the salience network (SN), mostly affected in bvFTD; the default mode network (DMN), mostly affected in AD; the executive network …
学术搜索中的文章
S Moguilner, AM García, YS Perl, E Tagliazucchi… - Neuroimage, 2021