[HTML][HTML] Methods for cleaning the BOLD fMRI signal

C Caballero-Gaudes, RC Reynolds - Neuroimage, 2017 - Elsevier
Blood oxygen-level-dependent functional magnetic resonance imaging (BOLD fMRI) has
rapidly become a popular technique for the investigation of brain function in healthy …

A review of resting-state fMRI and its use to examine psychiatric disorders

E Canario, D Chen, B Biswal - Psychoradiology, 2021 - academic.oup.com
Resting-state fMRI (rs-fMRI) has emerged as an alternative method to study brain function in
human and animal models. In humans, it has been widely used to study psychiatric …

[HTML][HTML] Resting-state connectivity in neurodegenerative disorders: Is there potential for an imaging biomarker?

C Hohenfeld, CJ Werner, K Reetz - NeuroImage: Clinical, 2018 - Elsevier
Biomarkers in whichever modality are tremendously important in diagnosing of disease,
tracking disease progression and clinical trials. This applies in particular for disorders with a …

Mining imaging and clinical data with machine learning approaches for the diagnosis and early detection of Parkinson's disease

J Zhang - npj Parkinson's Disease, 2022 - nature.com
Parkinson's disease (PD) is a common, progressive, and currently incurable
neurodegenerative movement disorder. The diagnosis of PD is challenging, especially in …

A comprehensive analysis of resting state fMRI measures to classify individual patients with Alzheimer's disease

F de Vos, M Koini, TM Schouten, S Seiler… - Neuroimage, 2018 - Elsevier
Alzheimer's disease (AD) patients show altered patterns of functional connectivity (FC) on
resting state functional magnetic resonance imaging (RSfMRI) scans. It is yet unclear which …

Resting-state networks in the course of aging—differential insights from studies across the lifespan vs. amongst the old

C Jockwitz, S Caspers - Pflügers Archiv-European Journal of Physiology, 2021 - Springer
Resting-state functional connectivity (RSFC) has widely been used to examine
reorganization of functional brain networks during normal aging. The extraction of …

Intraclass correlation: Improved modeling approaches and applications for neuroimaging

G Chen, PA Taylor, SP Haller, K Kircanski… - Human brain …, 2018 - Wiley Online Library
Intraclass correlation (ICC) is a reliability metric that gauges similarity when, for example,
entities are measured under similar, or even the same, well‐controlled conditions, which in …

Is the statistic value all we should care about in neuroimaging?

G Chen, PA Taylor, RW Cox - NeuroImage, 2017 - Elsevier
Here we address an important issue that has been embedded within the neuroimaging
community for a long time: the absence of effect estimates in results reporting in the …

Brain connectivity based graph convolutional networks and its application to infant age prediction

Y Li, X Zhang, J Nie, G Zhang, R Fang… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Infancy is a critical period for the human brain development, and brain age is one of the
indices for the brain development status associated with neuroimaging data. The difference …

Discriminating cognitive status in Parkinson's disease through functional connectomics and machine learning

A Abós, HC Baggio, B Segura, AI García-Díaz… - Scientific reports, 2017 - nature.com
There is growing interest in the potential of neuroimaging to help develop non-invasive
biomarkers in neurodegenerative diseases. In this study, connection-wise patterns of …