Functional connectome fingerprinting accuracy in youths and adults is similar when examined on the same day and 1.5‐years apart

Jalbrzikowski, Maria; Liu, Fuchen; Foran, William; Klei, Lambertus; Calabro, Finnegan J.; Roeder, Kathryn; Devlin, Bernie; Luna, Beatríz

doi:10.1002/hbm.25118

Cited by 40 publications

(40 citation statements)

References 59 publications

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“…BOLD fMRI and RSFC ( 96 , 97 ) have been proposed as tools for neuroimaging biomarkers. RSFC as measured by fMRI is stable across development ( 232 , 233 ) and reproducible ( 234 ) at a group level. RSFC in adolescent depression has been shown to differentiate (at a group-, not at the individual-level) symptom severity ( 235 ), symptom domains ( 213 , 236 , 237 ), onset ( 238 ), and course of disease ( 239 , 240 ).…”

Section: Limitations Of the Existing Literature And Proposed Resolutionsmentioning

confidence: 93%

Repetitive Transcranial Magnetic Stimulation for Adolescent Major Depressive Disorder: A Focus on Neurodevelopment

et al. 2021

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Adolescent depression is a potentially lethal condition and a leading cause of disability for this age group. There is an urgent need for novel efficacious treatments since half of adolescents with depression fail to respond to current therapies and up to 70% of those who respond will relapse within 5 years. Repetitive transcranial magnetic stimulation (rTMS) has emerged as a promising treatment for major depressive disorder (MDD) in adults who do not respond to pharmacological or behavioral interventions. In contrast, rTMS has not demonstrated the same degree of efficacy in adolescent MDD. We argue that this is due, in part, to conceptual and methodological shortcomings in the existing literature. In our review, we first provide a neurodevelopmentally focused overview of adolescent depression. We then summarize the rTMS literature in adult and adolescent MDD focusing on both the putative mechanisms of action and neurodevelopmental factors that may influence efficacy in adolescents. We then identify limitations in the existing adolescent MDD rTMS literature and propose specific parameters and approaches that may be used to optimize efficacy in this uniquely vulnerable age group. Specifically, we suggest ways in which future studies reduce clinical and neural heterogeneity, optimize neuronavigation by drawing from functional brain imaging, apply current knowledge of rTMS parameters and neurodevelopment, and employ an experimental therapeutics platform to identify neural targets and biomarkers for response. We conclude that rTMS is worthy of further investigation. Furthermore, we suggest that following these recommendations in future studies will offer a more rigorous test of rTMS as an effective treatment for adolescent depression.

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Section: Limitations Of the Existing Literature And Proposed Resolutionsmentioning

confidence: 93%

Repetitive Transcranial Magnetic Stimulation for Adolescent Major Depressive Disorder: A Focus on Neurodevelopment

et al. 2021

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“…Evidence suggests that the different levels of inter- and intrasubject variability in functional networks contribute to their distinctiveness, such that high intersubject ( Gratton et al, 2018 ; Mueller et al, 2013 ) and low intrasubject ( Laumann et al, 2015 ; Poldrack et al, 2015 ) variability in higher order associative networks are often related to their high discriminability ( Finn et al, 2015 ; Jalbrzikowski et al, 2020 ; Kaufmann et al, 2017 ; Miranda-Dominguez et al, 2018 , 2014 ; Mueller et al, 2013 ) and the opposite pattern to the low discriminability of primary sensory and motor networks ( Gratton et al, 2018 ; Laumann et al, 2015 ; Mueller et al, 2013 ; Poldrack et al, 2015 ). We confirmed that higher order associative networks were the most discriminatory, while visual networks were the least discriminatory, although they showed similar levels of intrasubject variability.…”

Section: Discussionmentioning

confidence: 99%

“…Recent and mounting evidence suggests that FC profiles are stable at different timescales ( Gratton et al, 2018 ; Jalbrzikowski et al, 2020 ; Miranda-Dominguez et al, 2018 ; Sato, White, & Biazoli, 2017 ). This characteristic posits the FC not only as an individual marker because of the comparably low intrasubject variability , but also as a powerful discriminatory measure characterized by the high intersubject variability.…”

Section: Introductionmentioning

confidence: 99%

“…Interestingly, functional networks show distinct levels of intersubject variability. Networks comprising higher order associative cortical areas seem to remarkably contribute to the FC distinctiveness ( Finn et al, 2015 ; Jalbrzikowski et al, 2020 ; Kaufmann et al, 2017 ; Miranda-Dominguez et al, 2018 , 2014 ; Mueller et al, 2013 ), which, in turn, might be due to a high intersubject ( Gratton et al, 2018 ; Mueller et al, 2013 ) and low intrasubject variability ( Laumann et al, 2015 ; Poldrack et al, 2015 ). On the other hand, functional connectivity within networks that comprises primary sensory and motor regions showed high intrasubject and low intersubject variability ( Gratton et al, 2018 ; Laumann et al, 2015 ; Mueller et al, 2013 ; Poldrack et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

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Inferring the heritability of large-scale functional networks with a multivariate ACE modeling approach

Ribeiro

Santos

Sato

et al. 2021

Network Neuroscience

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Recent evidence suggests that the human functional connectome is stable at different time scales and unique. These characteristics posit the functional connectome not only as an individual marker but also as a powerful discriminatory measure characterized by high intersubject variability. Among distinct sources of intersubject variability, the long-term sources include functional patterns that emerge from genetic factors. Here, we sought to investigate the contribution of additive genetic factors to the variability of functional networks by determining the heritability of the connectivity strength in a multivariate fashion. First, we reproduced and extended the connectome fingerprinting analysis to the identification of twin pairs. Then, we estimated the heritability of functional networks by a multivariate ACE modeling approach with bootstrapping. Twin pairs were identified above chance level using connectome fingerprinting, with monozygotic twin identification accuracy equal to 57.2% on average for whole-brain connectome. Additionally, we found that a visual (0.37), the medial frontal (0.31) and the motor (0.30) functional networks were the most influenced by additive genetic factors. Our findings suggest that genetic factors not only partially determine intersubject variability of the functional connectome, such that twins can be identified using connectome fingerprinting, but also differentially influence connectivity strength in large-scale functional networks.

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“…Recent and mounting evidence suggests that FC profiles are stable at different time scales (Gratton et al, 2018;Jalbrzikowski et al, 2020;Miranda-Dominguez et al, 2018;Sato, White, & Biazoli, 2017). This characteristic posits the FC not only as an individual marker due to the comparably low intrasubject variability but also as a powerful discriminatory measure characterized by the high intersubject variability.…”

Section: Introductionmentioning

confidence: 97%

Inferring the heritability of large-scale functional networks with a multivariate ACE modeling approach

Ribeiro

Santos

Sato

et al. 2018

Preprint

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Functional connectome fingerprints are partially heritable. Specifically, a higher heritability of high-order associative networks, which are greatly variable between individuals, has been proposed. However, such an interpretation relies on linear assumptions for the heritability inference and does not take into account the influence of the number of nodes on connectome fingerprinting analyses, since associative networks tend to include more brain regions. To overcome these limitations, we considered stable individual factors to estimate the relative genetic influence on whole-brain and eigenvector centrality-based networks of fixed size using the Human Connectome Project twin dataset. Individual identification accuracies were found to be higher in networks including more central nodes (94%) than the ones comprising peripheral nodes (22%). Nonetheless, the inferred additive genetic influence was more prominent in networks comprising peripheral nodes (50%) than hubs' networks (28%). Our results suggest that a brain hub's backbone is individually unique and less heritable than the connectivity profile of a subset of peripheral regions.

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Functional connectome fingerprinting accuracy in youths and adults is similar when examined on the same day and 1.5‐years apart

Cited by 40 publications

References 59 publications

Repetitive Transcranial Magnetic Stimulation for Adolescent Major Depressive Disorder: A Focus on Neurodevelopment

Repetitive Transcranial Magnetic Stimulation for Adolescent Major Depressive Disorder: A Focus on Neurodevelopment

Inferring the heritability of large-scale functional networks with a multivariate ACE modeling approach

Inferring the heritability of large-scale functional networks with a multivariate ACE modeling approach

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