Hierarchical Development of White Matter Tracts in Youth
Poster No:
1281
Submission Type:
Abstract Submission
Authors:
Audrey Luo1,2, Valerie Sydnor3, Joelle Bagautdinova1, Aaron Alexander-Bloch1, Bart Larsen4, Fang-Cheng Yeh5, Fengling Hu1, Marc Jaskir6, Arielle Keller1, David Roalf7, Golia Shafiei1, Russell Shinohara1, Matthew Cieslak8, Theodore Satterthwaite8
Institutions:
1University of Pennsylvania, Philadelphia, PA, 2Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 3Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, 4University of Minnesota, Minneapolis, MN, 5Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, 6Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA, 7Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 8UPenn, Philadelphia, PA
First Author:
Audrey Luo
University of Pennsylvania|Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania
Philadelphia, PA|Philadelphia, PA
University of Pennsylvania|Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania
Philadelphia, PA|Philadelphia, PA
Co-Author(s):
Marc Jaskir
Center for Neuroengineering and Therapeutics, University of Pennsylvania
Philadelphia, PA
Center for Neuroengineering and Therapeutics, University of Pennsylvania
Philadelphia, PA
David Roalf
Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania
Philadelphia, PA
Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania
Philadelphia, PA
Introduction:
Previous work has shown regional variation in the pattern and timing of white matter (WM) development, but the relationship between WM development and hierarchical brain organization remains sparsely investigated. Recent studies have shown that spatiotemporal developmental patterns of functional connectivity align with the sensorimotor-association (S-A) axis [1,2]. Studying WM development in the context of cortical organization can provide insight into how structural connectivity develops to support cortical activity. We hypothesized that the pattern and timing of developmental changes in WM tracts occur hierarchically along the S-A axis of cortical development.
Methods:
We used diffusion MRI data in youth ages 8-22 from the Human Connectome Project: Development (N=569). All images were preprocessed using QSIPrep 0.16.1 [3]. Next, 50 white matter tracts were mapped using automated fiber tracking from DSI studio [4] as part of a QSIPrep reconstruction workflow. We used mean fractional anisotropy (FA) along each tract to characterize WM. Site effects were harmonized using CovBat, in which age was modeled as a smooth term via a generalized additive model (GAM) [5,6]. To model both linear and non-linear associations between FA and age, we used GAMs with penalized splines while covarying for sex and in-scanner motion. The age of maturation was defined as the earliest age at which the first derivative of the smooth was not significant. To define S-A ranks for each tract, we used a population-based WM tract-to-cortical region connectome mapping [7] based on HCP-MMP atlas regions [8], which identified the population probability that a given tract was connected to each HCP-MMP atlas region. Tract-to-region connections present in at least 5% of the population were retained. We parcellated the S-A axis using the HCP-MMP atlas, yielding regional S-A ranks. Next, a weighted mean S-A rank was computed for each tract by weighing the average S-A ranks of the regions that a tract connected to by the population probability of each tract-to-region connection. We used Spearman's rank correlations to characterize the spatial association between developmental effects and S-A axis ranks. Spin-based spatial permutation tests were used for significance testing [9].
Results:
We visualized each tracts' weighted mean S-A rank and the cortical regions each tract connected to using Yeh's tract-to-region probabilities (Fig. 1). Weighted mean S-A rank tended to correspond to associated tract functions described in literature; for example, the optic radiation ranked lowest whereas arcuate fasciculus ranked high on the S-A axis (Fig. 1A-B). Mid-ranking tracts tended to connect diverse cortical regions spanning across the S-A axis (Fig. 1D). A tract's rank was significantly associated with its age of maturation (Fig. 2A, r = 0.41, pspin<0.001). Sensorimotor tracts tended to mature earlier, including corticospinal tracts and the optic radiations. In contrast, higher order tracts (i.e., those with higher S-A ranks) tended to mature later, such as the frontal aslant tracts and anterior thalamic radiations. The uncinate fasciculus uniquely matured earlier among higher order tracts. Fitted smooths based on model-predicted data were computed in all tracts (Fig. 2B-E). The FA of lowest-order tracts (rank less than 100) tended to have flatter trajectories of developmental change (Fig. 2B and C). In contrast, FA in many higher order tracts (rank greater than 200) continued to increase throughout adolescence (Fig. 2E), though several tracts displayed earlier flattening, including the uncinate fasciculus.
·Figure 1
·Figure 2
Conclusions:
We found WM maturation occurs hierarchically along a major axis of cortical organization. Characterizing patterns of healthy WM development is important for understanding how deviations from normative hierarchical development may confer risk for diverse psychopathology. Replication of these results in additional datasets is necessary to establish generalizability.
Lifespan Development:
Early life, Adolescence, Aging
Normal Brain Development: Fetus to Adolescence 1
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Normal Development
White Matter Anatomy, Fiber Pathways and Connectivity 2
Novel Imaging Acquisition Methods:
Diffusion MRI
Keywords:
Development
MRI
NORMAL HUMAN
Open Data
Open-Source Code
Open-Source Software
Tractography
White Matter
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
1|2Indicates the priority used for review
Provide references using author date format
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