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Title

Detecting Perfusion Pattern based on the Background Low-frequency Fluctuation in Resting-State Functional MRI Data and its Influence on Resting-State Networks: An Iterative Post-processing Approach

Authors
Qian, Tianyi
Published in Brain Connectivity. 2017, vol. 7, no. 10, p. 627-634
Abstract RS-fMRI is based on the assumption that the vascular response and the blood oxygenation level dependent (BOLD) response are homogenous across the entire brain. However, this a priori hypothesis is not consistent with the well-known variability of cerebral vascular territories. In order to explore whether the RS networks are influenced by varied vascular speed in different vascular territories, we assessed the time-shift maps that give an estimate of the local timing of the vascular response and check whether local differences in this timing have an impact on the estimates of RS networks.
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PMID: 29117709
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Article (Author postprint) (4 MB) - public document Free access
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Research group Groupe Giannakopoulos Panteleimon (psychiatrie générale) (201)
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QIAN, Tianyi et al. Detecting Perfusion Pattern based on the Background Low-frequency Fluctuation in Resting-State Functional MRI Data and its Influence on Resting-State Networks: An Iterative Post-processing Approach. In: Brain Connectivity, 2017, vol. 7, n° 10, p. 627-634. https://archive-ouverte.unige.ch/unige:100223

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Deposited on : 2017-12-13

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