2022
DOI: 10.1002/hbm.26112
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Differences in functional connectivity distribution after transcranial direct‐current stimulation: A connectivity density point of view

Abstract: In this manuscript, we consider the problem of relating functional connectivity measurements viewed as statistical distributions to outcomes. We demonstrate the utility of using the distribution of connectivity on a study of resting‐state functional magnetic resonance imaging association with an intervention. The method uses the estimated density of connectivity between nodes of interest as a functional covariate. Moreover, we demonstrate the utility of the procedure in an instance where connectivity is natura… Show more

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Cited by 7 publications
(2 citation statements)
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“…Additionally, delta power findings in the present study were in line with previous findings of ketamine increasing slow wave activity in the first NREM episode [ 8 ]. Other areas of brain research have also supported the use of FDA, including studies using anatomic magnetic resonance imaging (MRI) and functional MRI measures [ 45 , 46 ]. Because our application of FDA in a study of drug effects on sleep EEG is novel, additional work is needed to replicate these findings in other datasets and treatments to determine whether the potential effects are ketamine-specific or represent a signature of antidepressant response to treatment.…”
Section: Discussionmentioning
confidence: 99%
“…Additionally, delta power findings in the present study were in line with previous findings of ketamine increasing slow wave activity in the first NREM episode [ 8 ]. Other areas of brain research have also supported the use of FDA, including studies using anatomic magnetic resonance imaging (MRI) and functional MRI measures [ 45 , 46 ]. Because our application of FDA in a study of drug effects on sleep EEG is novel, additional work is needed to replicate these findings in other datasets and treatments to determine whether the potential effects are ketamine-specific or represent a signature of antidepressant response to treatment.…”
Section: Discussionmentioning
confidence: 99%
“…Since edge-at-a-time approaches distinguish each individual edge in the connectivity matrix, they can be described as making a full use of the associated location information for each edge (that is, which pair of brain regions the edge corresponds to). In contrast, in recent work, Tang et al (2023) treat all withinsubject edges as exchangeable. Their approach ignores the location information for each edge and instead characterizes subjects by the distribution (or histogram) of their edges.…”
Section: Introductionmentioning
confidence: 95%