Functional brain networks are dominated by stable group and individual factors, not cognitive or daily variation

By Caterina Gratton, Timothy O. Laumann, A. Nielsen, Deanna J. Greene, Evan M. Gordon, Adrian W. Gilmore, Steven M. Nelson, Rebecca S. Coalson, Abraham Z. Snyder, Bradley L. Schlaggar and 2 more. Neuron, 2018

798 citations recorded by the source corpus.

Summary The organization of human brain networks can be measured by capturing correlated brain activity with functional magnetic resonance imaging (fMRI). There is considerable interest in understanding how brain networks vary across individuals, 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 9 high-quality highly-sampled individuals to parse the magnitude and anatomical distribution of network variability across subjects, sessions, and tasks. Critically, we find that functional networks are dominated by common organizational principles and stable individual features, with substantially more modest contributions from task-state and day-to-day variability. Sources of variation were differentially distributed across the brain and differentially linked to intrinsic and task-evoked sources. We conclude that functional networks are suited to measuring stable individual characteristics, suggesting utility in personalized medicine.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/19c690c3e38038c35c20de464f60867c787aac2d

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Citations in the corpus

Linking Structure and Function in Macroscale Brain Networks. (2020, neutral): “FC may primarily capture stable functional configurations, potentially limiting inferences about time-dependent functional interactions [135] (but see [136]).”
Reproducible brain-wide association studies require thousands of individuals (2022, positive): “For this manuscript we chose to pre-process the resting state and task BOLD data identically to exclude pre-processing choices from the list of potential contributors to poor reproducibility (Gratton et al. , 2018, Neuron).”
Questions and controversies in the study of time-varying functional connectivity in resting fMRI (2020, positive): “9 (Calhoun et al., 2008; Cole et al., 2014; Geerligs et al., 2015; Gratton et al., 2018), and that patterns of static FC are relatively stable across different tasks, with similarity estimates ranging from r = 0.”
Neurodevelopment of the association cortices: Patterns, mechanisms, and implications for psychopathology (2021, neutral): “…including cortical structure (Fischl and Dale, 2000; Hill et al., 2010a; Mueller et al., 2013; Reardon et al., 2018), connectivity architecture (Gratton et al., 2018; Mueller et al., 2013; Xu et al., 2019), the topographical organization of functional systems (Cui et al., 2020; Kong et al.,…”
Considerations for conducting developmental neuroimaging research on mental health topics (2025, unknown): “With large quantities of high quality data per person, these individual features have been shown to be stable within a given individual over time, thereby capturing the individual variability typically obscured with standard group averaging approaches [88, 119, 127, 134, 135].”