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@proceedings{2401057,
author = {Gajdoš, Martin and Mitterová, Kristína and Lamoš, Martin and Rektorová, Irena},
booktitle = {OHBM 2022 Annual Meeting, Glasgow},
keywords = {fMRI; Parkinson’s disease; independent component analysis; sliding window analysis},
language = {eng},
title = {Dynamics of fMRI connectivity associated with attention in patients with Parkinson’s disease},
url = {https://www.humanbrainmapping.org/i4a/pages/index.cfm?pageid=4118},
year = {2022}
}
TY - CONF
ID - 2401057
AU - Gajdoš, Martin - Mitterová, Kristína - Lamoš, Martin - Rektorová, Irena
PY - 2022
TI - Dynamics of fMRI connectivity associated with attention in patients with Parkinson’s disease
KW - fMRI
KW - Parkinson’s disease
KW - independent component analysis
KW - sliding window analysis
UR - https://www.humanbrainmapping.org/i4a/pages/index.cfm?pageid=4118
N2 - Dynamic fMRI connectivity extends information reported with static fMRI connectivity. In this work, we focused on relation between changes in brain states and behavioral characteristics in patients with Parkinson’s disease (PD). Our dataset consists of 31 patients with PD (age 63.1 ± 10.2, 7 women) and 40 HC (age 66.0 ± 7.7 let, 29 women). We used independent component analysis (ICA) in toolbox GIFT for identification of large scale brain networks. We performed sliding window analysis on timeseries of mentioned ICA components. We observed statistically significant differences in dynamic parameters, probably relevant to preparation attentional activity of top-down type.
ER -
GAJDOŠ, Martin, Kristína MITTEROVÁ, Martin LAMOŠ and Irena REKTOROVÁ. Dynamics of fMRI connectivity associated with attention in patients with Parkinson’s disease. In \textit{OHBM 2022 Annual Meeting, Glasgow}. 2022.
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