TemplateFlow: FAIR-sharing of multi-scale, multi-species brain models

Ćirić, Rastko; Thompson, William; Lorenz, Romy; Goncalves, Mathias; MacNicol, Eilidh; Markiewicz, Chris; Halchenko, Yaroslav O.; Ghosh, Samik; Gorgolewski, Krzysztof J.; Poldrack, Russell A.; Estéban, Oscar

doi:10.21203/rs.3.rs-264855/v2

Cited by 5 publications

(1 citation statement)

References 60 publications

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“…The RESILIENT templates and associated resources are available under a Creative Commons Attribution 4.0 license from the open science framework (osf.io/U4GTW) and TemplateFlow (Ciric et al, 2021), a versioncontrolled repository that faciliates template integration for processing pipelines.…”

Section: Release Of Prior Information For Rat Brains In Their Adulthoodmentioning

confidence: 99%

Age-Specific Adult Rat Brain MRI Templates and Tissue Probability Maps

MacNicol

Wright

Kim

et al. 2022

Front. Neuroinform.

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Age-specific resources in human MRI mitigate processing biases that arise from structural changes across the lifespan. There are fewer age-specific resources for preclinical imaging, and they only represent developmental periods rather than adulthood. Since rats recapitulate many facets of human aging, it was hypothesized that brain volume and each tissue's relative contribution to total brain volume would change with age in the adult rat. Data from a longitudinal study of rats at 3, 5, 11, and 17 months old were used to test this hypothesis. Tissue volume was estimated from high resolution structural images using a priori information from tissue probability maps. However, existing tissue probability maps generated inaccurate gray matter probabilities in subcortical structures, particularly the thalamus. To address this issue, gray matter, white matter, and CSF tissue probability maps were generated by combining anatomical and signal intensity information. The effects of age on volumetric estimations were then assessed with mixed-effects models. Results showed that herein estimation of gray matter volumes better matched histological evidence, as compared to existing resources. All tissue volumes increased with age, and the tissue proportions relative to total brain volume varied across adulthood. Consequently, a set of rat brain templates and tissue probability maps from across the adult lifespan is released to expand the preclinical MRI community's fundamental resources.

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Section: Release Of Prior Information For Rat Brains In Their Adulthoodmentioning

confidence: 99%

Age-Specific Adult Rat Brain MRI Templates and Tissue Probability Maps

MacNicol

Wright

Kim

et al. 2022

Front. Neuroinform.

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Voxel‐wise intermodal coupling analysis of two or more modalities using local covariance decomposition

Weinstein

Baller

et al. 2022

Human Brain Mapping

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When individual subjects are imaged with multiple modalities, biological information is present not only within each modality, but also between modalities – that is, in how modalities covary at the voxel level. Previous studies have shown that local covariance structures between modalities, or intermodal coupling (IMCo), can be summarized for two modalities, and that two‐modality IMCo reveals otherwise undiscovered patterns in neurodevelopment and certain diseases. However, previous IMCo methods are based on the slopes of local weighted linear regression lines, which are inherently asymmetric and limited to the two‐modality setting. Here, we present a generalization of IMCo estimation which uses local covariance decompositions to define a symmetric, voxel‐wise coupling coefficient that is valid for two or more modalities. We use this method to study coupling between cerebral blood flow, amplitude of low frequency fluctuations, and local connectivity in 803 subjects ages 8 through 22. We demonstrate that coupling is spatially heterogeneous, varies with respect to age and sex in neurodevelopment, and reveals patterns that are not present in individual modalities. As availability of multi‐modal data continues to increase, principal‐component‐based IMCo (pIMCo) offers a powerful approach for summarizing relationships between multiple aspects of brain structure and function. An R package for estimating pIMCo is available at: https://github.com/hufengling/pIMCo.

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