Cortical folding and layering support local-to-global functional properties at 7T
Poster No:
2314
Submission Type:
Abstract Submission
Authors:
Yigu Zhou1, Giulia Baracchini1, Jessica Royer1, Oualid Benkarim1, Raúl Rodriguez-Cruces1, Ke Xie1, Donna Gift Cabalo1, Nathan Spreng1, Boris Bernhardt1
Institutions:
1Montreal Neurological Institute and Hospital, Montreal, QC
First Author:
Co-Author(s):
Introduction:
Brain function is coordinated and can be abstracted as networks whose activity is overlaid onto the cortical mantle with its organized folding patterns and layered microarchitecture. Previous investigations of structure-function coupling in the cortex revealed laminated microstructure and macroscopic geometry as constraints to global functional organization [1,2] while heterogeneity within connected cortical regions, or network "nodes", is crucial for local functional specification [3]. Expanding and integrating these lines of evidence, we probed how cortical folding and layered microarchitecture support functional properties of single-vertex nodes at local, regional, and global levels.
Methods:
Twelve healthy young adults (age 25±4.42; 50% females) with no history of psychiatric or neurological diagnoses underwent 7T MRI. Each participant completed two runs of quantitative T1-weighted scan (qT1, 0.5mm isotropic, 12m35s) followed by multi-echo resting-state fMRI (rs-fMRI; TR=1.69s; TE=10.8, 27.3, 43.8ms; 1.9mm isotropic; 5m39s). Images were preprocessed using micapipe v0.2.2. [4]. We assessed nodal functional properties on mean-centered timeseries via BOLD signal variability (local), regional homogeneity (ReHo; regional), and degree centrality (WDC; global) (Fig 1a). Folding was assessed at varying spatial scales with mean curvature at the finest scale, followed by sulcal depth potential [5] and gyrification index at coarser scales (Fig 1b). Microstructural profiles were obtained using qT1 intensities sampled across cortical depths [6]. We created histograms for qT1 intensities on vertex-wise cortical depth columns and examined the first three statistical moments (m1, m2, m3) (Fig 1c). All measures were computed in native surface and interpolated to fsLR-5k template for comparison. Product-moment correlation was calculated within and between participants (Fig 1) and between measures (Fig 2a) to assess reliability and spatial relationships, respectively. Multiple linear regression models were built to predict nodal function based on morphological and microstructural measures, and cross-validated using a distance-dependent approach [7]. The significance of spatial correlation coefficients and linear model metrics was evaluated using spatial null models [8, 9] and Bonferroni-adjusted.
Results:
Measures of nodal function, morphology and microstructure were reliable within participants across sessions (Fig 1, see caption for stats). Spatial correlation between measures highlighted moderate associations of nodal function with all statistical moments derived from microstructural profiles. Meanwhile, associations of local, regional, and global functional properties with curvature, depth and gyrification were graded, with measures of morphology taken at increasingly wide spatial scales associated to dynamics assessed at the corresponding scales. A strong relationship between curvature and ReHo at the whole-brain level is consistent with coupling between sulcation and ReHo reported by [10] (Fig 2a). Via multiple linear regression and dominance analysis, the relative contributions of morphology to nodal function reflected a local-to-global gradation, with morphology assessed at finer spatial scale contributing more to functional measures at a similar scale. The contributions of microstructure to nodal function were most important for BOLD variability and for ReHo. However, microstructural moments were overtaken by gyrification for predicting WDC. These patterns were replicated across sessions (Fig 2b, c, see caption for stats).
Conclusions:
We leveraged the fine spatial resolution of 7T MRI with multi-echo functional sequences to investigate cortical folding, microstructure, and nodal dynamics concomitantly. The tradeoff between cortical folding and microstructure for predicting nodal dynamics at the vertex, community and network levels found here supports that constraints to local-to-global signal flow are ingrained in both shape and substrate of the cortical mantle.
Modeling and Analysis Methods:
Task-Independent and Resting-State Analysis
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Cortical Anatomy and Brain Mapping 2
Novel Imaging Acquisition Methods:
BOLD fMRI 1
Keywords:
FUNCTIONAL MRI
HIGH FIELD MR
Multivariate
STRUCTURAL MRI
1|2Indicates the priority used for review
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