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Riggins, T.

Publications and source records attributed to Riggins, T..

4 recordsLinked to original sources

Fiber-tract development contributes to functional specialization in the human hippocampus

Fiber-tracts exhibit distinct projection patterns along the anterior-posterior axis of the hippocampus, promoting a specialization in function. This specialization becomes increasingly pronounced throughout child development, with important implications for neurocognitive outcomes. Developmental changes in fiber-tract properties, including intra-axonal cross-sectional area and myelin content, may contribute to this anterior-posterior functional specialization. To test this, we developed a diffusion-MRI tractography pipeline to identify hippocampal fiber-tracts in single subjects, then examined whether age-related differences in total intra-axonal cross-sectional area and myelin content (T1w/T2w) could predict functional specialization in a large cross-sectional sample (N=539, aged 5-21 years). With age, we found that the cross-sectional area of short-range medial-temporal tracts, which primarily target the anterior/body of the hippocampus, exhibited rapid growth. Concomitantly, the cross-sectional area of long-range occipito-parietal tracts, which primarily target the posterior hippocampus, exhibited a modest pruning. Increases in myelin content were relatively homogenous across fiber-tracts. In support of our hypothesis, we found that the cross-sectional area of fiber-tracts significantly predicts the surface-area of an fMRI-defined posterior system; a sensitive marker of functional specialization in the hippocampus. Tracts targeting early visual cortex (V2, V3, V4) showed the strongest association, with statistical modeling indicating a mediating effect of early-visual tract development on the relation between age and functional specialization. These findings provide evidence consistent with a mechanism whereby anatomical neurodevelopment contributes to functional specialization in the human hippocampus.

neuroscience↗

Harmonized Protocol for Segmentation of the Hippocampal Tail on High-Resolution in vivo MRI from the Hippocampal Subfields Group (HSG)

The hippocampus is a heterogeneous structure with cytoarchitectonically distinct subfields that exhibit heterogeneous lifespan trajectories and are differentially susceptible to diseases. Advances in high-resolution imaging have accelerated research on these structures, yet variability in segmentation protocols limits cross-study comparability. The Hippocampal Subfields Group (HSG) is an international consortium addressing this challenge by developing a reliable, accessible, and freely available segmentation protocol for high-resolution T2-weighted 3 tesla MRI scans (http://www.hippocampalsubfields.com). Here, we present the harmonized protocol for the posterior portion of the hippocampus (the "tail"), complementing the previously established "body" protocol, and with an anterior "head" protocol under development. The tail protocol provides standardized definitions of the external boundaries for the posterior-most extent of the hippocampus, facilitating consistent segmentation from surrounding tissues. The research community was extensively involved through an online survey that incorporated comprehensive protocol details, feasibility assessments, tutorial videos, and illustrative segmentations. Through this collaborative process, consensus emerged to exclude subfield labeling in the hippocampal tail due to limited visibility of internal landmarks and substantial anatomical variability in this region. All proposed boundary guidelines were deemed clear and agreed upon via a Delphi procedure. The harmonized tail protocol has high intra-(Averaged ICC(2,1) > 0.98; Averaged Dice Similarity Coefficient = 0.92) and inter-rater reliability (Averaged ICC(2,k) > 0.98; Averaged Dice Similarity Coefficient = 0.86) and offers a practical framework for replicable segmentation. By establishing standardized guidelines, this protocol enhances comparability of findings across developmental, aging, and clinical research and is compatible with ongoing technological advances.

neuroscience↗

Harmonized Protocol for Subfield Segmentation in the Hippocampal Body on High-Resolution in vivo MRI from the Hippocampal Subfields Group (HSG)

Hippocampal subfields differentially develop and age, and they vary in vulnerability to neurodegenerative diseases. Innovation in high-resolution imaging has accelerated clinical research on human hippocampal subfields, but substantial differences in segmentation protocols impede comparisons of results across laboratories. The Hippocampal Subfields Group (HSG) is an international organization seeking to address this issue by developing a histologically-valid, reliable, and freely available segmentation protocol for high-resolution T2-weighted 3 tesla MRI (http://www.hippocampalsubfields.com). Here, we report the first portion of the protocol focused on subfields in the hippocampal body; protocols for the head and tail are in development. The body protocol includes definitions of the internal boundaries between subiculum, Cornu Ammonis (CA) 1-3 subfields, and dentate gyrus, in addition to the external boundaries of the hippocampus apart from surrounding white matter and cerebrospinal fluid. The segmentation protocol is based on a novel histological reference data set labeled by multiple expert neuroanatomists. With broad participation of the research community, we voted on the segmentation protocol via online survey, which included detailed protocol information, feasibility testing, demonstration videos, example segmentations, and labeled histology. All boundary definitions were rated as having high clarity and reached consensus agreement by Delphi procedure. The harmonized body protocol yielded high inter- and intra-rater reliability. In the present paper we report the procedures to develop and test the protocol, as well as the detailed procedures for manual segmentation using the harmonized protocol. The harmonized protocol will significantly facilitate cross-study comparisons and provide increased insight into the structure and function of hippocampal subfields across the lifespan and in neurodegenerative diseases.

neuroscience↗

Handling Multiplicity in Neuroimaging through Bayesian Lenses with Hierarchical Modeling

Here we address the current issues of inefficiency and over-penalization in the massively univariate approach followed by the correction for multiple testing, and propose a more efficient model that pools and shares information among brain regions. Using Bayesian multilevel (BML) modeling, we control two types of error that are more relevant than the conventional false positive rate (FPR): incorrect sign (type S) and incorrect magnitude (type M). BML also aims to achieve two goals: 1) improving modeling efficiency by having one integrative model and thereby dissolving the multiple testing issue, and 2) turning the focus of conventional null hypothesis significant testing (NHST) on FPR into quality control by calibrating type S errors while maintaining a reasonable level of inference efficiency The performance and validity of this approach are demonstrated through an application at the region of interest (ROI) level, with all the regions on an equal footing: unlike the current approaches under NHST, small regions are not disadvantaged simply because of their physical size. In addition, compared to the massively univariate approach, BML may simultaneously achieve increased spatial specificity and inference efficiency, and promote results reporting in totality and transparency. The benefits of BML are illustrated in performance and quality checking using an experimental dataset. The methodology also avoids the current practice of sharp and arbitrary thresholding in the p-value funnel to which the multidimensional data are reduced. The BML approach with its auxiliary tools is available as part of the AFNI suite for general use.

neuroscience↗