Can brain state be manipulated to emphasize individual differences in functional connectivity?

By Emily S. Finn, Dustin Scheinost, D. Finn, X. Shen, X. Papademetris, T. Constable. NeuroImage, 2017

351 citations recorded by the source corpus.

&NA; While neuroimaging studies typically collapse data from many subjects, brain functional organization varies between individuals, and characterizing this variability is crucial for relating brain activity to behavioral phenotypes. Rest has become the default state for probing individual differences, chiefly because it is easy to acquire and a supposed neutral backdrop. However, the assumption that rest is the optimal condition for individual differences research is largely untested. In fact, other brain states may afford a better ratio of within‐ to between‐subject variability, facilitating biomarker discovery. Depending on the trait or behavior under study, certain tasks may bring out meaningful idiosyncrasies across subjects, essentially enhancing the individual signal in networks of interest beyond what can be measured at rest. Here, we review theoretical considerations and existing work on how brain state influences individual differences in functional connectivity, present some preliminary analyses of within‐ and between‐subject variability across conditions using data from the Human Connectome Project, and outline questions for future study. HighlightsRest is the default for studying individual differences in functional connectivity.But certain tasks may improve the ratio of within‐ to between‐subject variability.We review work on how scan condition influences individual differences.Preliminary results using HCP data show individual differences change with task.Using certain tasks over rest may improve sensitivity of imaging‐based biomarkers.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/37760e5eda2b1effd51c5debc90616557c4f5a23

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In Cognitive Neuroscience

Citations in the corpus

Questions and controversies in the study of time-varying functional connectivity in resting fMRI (2020, neutral): “…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 = 0.5 to r = 0.9 (Cole et al., 2014; Finn et al., 2017; Geerligs et al., 2015; Gratton et al., 2018; Krienen, Yeo, & Buckner, 2014).”
Functional brain networks are dominated by stable group and individual factors, not cognitive or daily variation (2018, background): “While the magnitude of task by individual interactions differed by task, as predicted by Finn et al. (2017), inter-task differences were minor compared to the overall size of the individual-specific task effect and at least partly dependent on data quantity/quality (Figure S2); future work will be…”
Ten simple rules for predictive modeling of individual differences in neuroimaging (2019, background): “…shown previously that by having individuals complete tasks in the scanner, participant-specific connectivity features are more readily observable (Finn et al., 2017; Vanderwal et al., 2017) and lead to better model performance when predicting fluid intelligence (Greene et al., 2018) and measures…”