Resting-state functional connectivity in normal brain aging.

By L. K. Ferreira, G. Busatto. Neuroscience and Biobehavioral Reviews, 2013

596 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/4e4d0e9fe4deab1787cf2a03e2474e0eb40dae45

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In Cognitive Neuroscience

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Fréchet regression for random objects with Euclidean predictors (2016, methodology): “Of particular interest regarding functional connectivity in the resting state is the so-called default-mode network (DMN), including the study of agerelated effects (Ferreira and Busatto 2013).”
Statistical harmonization corrects site effects in functional connectivity measurements from multi-site fMRI data (2018, methodology): “…negative correlation between age and functional connectivity within the default mode network (DMN; Damoiseaux et al., 2008; Damoiseaux, 2017; Ferreira & Busatto, 2013; Grady et al., 2010; Koch et al., 2010; Tomasi & Volkow, 2012), as well as preserve previously reported negative…”
Effects of aging on functional and structural brain connectivity☆ (2017, result): “Overall, the most consistent finding across all these studies is that older adults have lower functional connectivity between regions of the default mode network compared to younger adults, see (Dennis and Thompson, 2014; Ferreira and Busatto, 2013) for previous reviews on this topic.”
Functional data analysis for density functions by transformation to a Hilbert space (2016, background): “In recent years, the problem of identifying functional connectivity between brain voxels or regions has received a great deal of attention, especially for resting state fMRI (Allen et al., 2012; Ferreira and Busatto, 2013; Sheline and Raichle, 2013).”
Age-Related Characteristics of Resting-State Electroencephalographic Signals and the Corresponding Analytic Approaches: A Review (2024, background): “Various brain connectivities based on the corresponding mathematical principles have been proposed to identify the significant evidence of functional (unidirectional) or effective (bidirectional) connectivity in the brain using graph-theory-based network analysis [26,27].”