Connectome-based fingerprinting: reproducibility, precision, and behavioral prediction

Ramduny, Jivesh; Kelly, Clare

doi:10.1038/s41386-024-01962-8

Neuropsychopharmacol.

2024

DOI: 10.1038/s41386-024-01962-8

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Connectome-based fingerprinting: reproducibility, precision, and behavioral prediction

Jivesh Ramduny,

Clare Kelly

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2024

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Cited by 2 publications

References 115 publications

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Effects of oral contraceptive pills on brain networks: A replication and extension

Haase,

Liu,

Jordan

et al. 2024

Preprint

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Neuroimaging research has identified significant effects of oral contraceptive pills (OCPs) on brain networks. A wide variety of approaches have been employed, largely in observational samples, with few converging results. This study was designed to replicate and expand this previous work using a randomized, double-blind, placebo-controlled crossover trial to investigate effects of OCPs on brain networks. Using functional MRI, we focused on brain regions identified in prior studies. Our analyses did not strictly replicate previously reported effects of OCPs on functional connectivity. Exploratory analyses suggest that traditional seed-based approaches may miss broader, network-level effects of OCPs on brain circuits. We applied data-driven, multivariate techniques to assess these network-level changes, A deeper understanding of neural effects of OCPs can be important in helping patients make informed decisions regarding contraception, mitigating unwanted side effects, and also in understanding the potentially confounding effects of OCPs in other neuroimaging investigations.

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Effects of oral contraceptive pills on brain networks: A replication and extension

Haase,

Liu,

Jordan

et al. 2024

Preprint

View full text Add to dashboard Cite

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Individual uniqueness of connectivity gradients is driven by the complexity of the embedded networks and their dispersion

Serhan,

Darawshy,

Wei

et al. 2024

Preprint

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Connectivity gradients are widely used to characterize meaningful principles of functional brain organization in health and disease. However, the degree of individual uniqueness and shared common principles is not yet fully understood. Here, we leveraged the Hangzhou test-retest dataset, comprising repeated resting-state fMRI scans over the span of one month, to investigate the balance between individual variation and shared patterns of brain organization. We quantified the short- and long-term stability for the first three connectivity gradients and used connectome fingerprinting to establish the associated individual identification rate. We found that all three connectivity gradients are highly correlated over both short and long time intervals, demonstrating connectome fingerprinting utility. Individual uniqueness was dictated by the complexity of the networks such that heteromodal networks had higher connectome fingerprinting rates than unimodal networks. Importantly, the dispersion of the gradient coefficients associated with canonical functional networks was correlated with identification rates, irrespective of the position along the gradients. Beyond individual uniqueness, between subject similarity was high along the first connectivity gradient, which captures the dissociation between unimodal and heteromodal cortices, and the second connectivity gradient, which differentiates sensory cortices. Our results support the usage of connectivity gradients for the purposes of both group comparisons and prediction of individual behaviours. Our work adds to existing knowledge on the shared versus unique organizational principles and offers insights into the importance of network dispersion to the individual uniqueness it carries.

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Connectome-based fingerprinting: reproducibility, precision, and behavioral prediction

Cited by 2 publications

References 115 publications

Effects of oral contraceptive pills on brain networks: A replication and extension

Effects of oral contraceptive pills on brain networks: A replication and extension

Individual uniqueness of connectivity gradients is driven by the complexity of the embedded networks and their dispersion

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