2018
DOI: 10.1016/j.neuron.2018.03.035
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Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation

Abstract: The organization of human brain networks can be measured by capturing correlated brain activity with fMRI. There is considerable interest in understanding how brain networks vary across individuals or neuropsychiatric populations or are altered during the performance of specific behaviors. However, the plausibility and validity of such measurements is dependent on the extent to which functional networks are stable over time or are state dependent. We analyzed data from nine high-quality, highly sampled individ… Show more

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Cited by 727 publications
(837 citation statements)
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References 86 publications
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“…It was more sensitive than the ICA, which showed no changes in whole‐brain resting‐state networks. This lack of differences in ICA is consistent with a recent investigation conducted by Gratton et al () focused on the variability of functional brain networks. The authors found that functional networks are ruled by common organization patterns, like genetics and structural connections, as well as, stable individual features, like long‐term histories of coactivation.…”
Section: Discussionsupporting
confidence: 92%
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“…It was more sensitive than the ICA, which showed no changes in whole‐brain resting‐state networks. This lack of differences in ICA is consistent with a recent investigation conducted by Gratton et al () focused on the variability of functional brain networks. The authors found that functional networks are ruled by common organization patterns, like genetics and structural connections, as well as, stable individual features, like long‐term histories of coactivation.…”
Section: Discussionsupporting
confidence: 92%
“…In our study, the preexisting connectivity patterns of rPPC and rDLPFC were rapidly modified by a specific but individual experience, the training, and these modifications were observable especially at rest. It is thought that daily variability has a minor contribution to functional networks (Gratton et al, ), but the evidence found here and in previous works (e.g., Lewis et al, ) support that experience‐based variability has an effect on functional brain connectivity, which might be due to the specificity and the intensity of the training session. In agreement with Gratton et al (), these changes are specific and different for each individual; moreover, their effects are likely to affect higher order processing and control areas (i.e., frontoparietal areas).…”
Section: Discussionsupporting
confidence: 67%
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“…As in previous work, functional brain networks were considered to be dominated by stable group and individual factors (Gratton et al, 2018;Xie et al, 2018). In this section, we utilize a data-driven SDL model to estimate group factors from functional connectomes.…”
Section: Methodsmentioning
confidence: 99%
“…Inspired by the work proposed by Gratton et al (2018), we believe that each functional connectivity is comprised of group and individual factors. Group components are expected to be more expressed by some subjects.…”
Section: Increased Individual Identifiability By Removing Group Facmentioning
confidence: 99%