Structural graph-based morphometry: A multiscale searchlight framework based on sulcal pits

Abstract

Studying the topography of the cortex has proved valuable in order to characterize populations of subjects. In particular, the recent interest towards the deepest parts of the cortical sulci - the so-called sulcal pits - has opened new avenues in that regard. In this paper, we introduce the first fully automatic brain morphometry method based on the study of the spatial organization of sulcal pits - Structural Graph-Based Morphometry (SGBM). Our framework uses attributed graphs to model local patterns of sulcal pits, and further relies on three original contributions. First, a graph kernel is defined to provide a new similarity measure between pit-graphs, with few parameters that can be efficiently estimated from the data. Secondly, we present the first searchlight scheme dedicated to brain morphometry, yielding dense information maps covering the full cortical surface. Finally, a multi-scale inference strategy is designed to jointly analyze the searchlight information maps obtained at different spatial scales. We demonstrate the effectiveness of our framework by studying gender differences and cortical asymmetries: we show that SGBM can both localize informative regions and estimate their spatial scales, while providing results which are consistent with the literature. Thanks to the modular design of our kernel and the vast array of available kernel methods, SGBM can easily be extended to include a more detailed description of the sulcal patterns and solve different statistical problems. Therefore, we suggest that our SGBM framework should be useful for both reaching a better understanding of the normal brain and defining imaging biomarkers in clinical settings.

Exploring folding patterns of infant cerebral cortex based on multi-view curvature features: Methods and applications

“…This indicates that some typical folding patterns may present male or female dominant trends. Some studies on older children and adults showed gender differences in cortical folding (Awate et al, 2010;Li et al, 2014d;Takerkart et al, 2017). For instance, Takerkart et al found the gender differences in the spatial organization of sulcal pits in parts of the frontal cortex (overlapped with IFG) and the cingulate cortex, which are partially consistent with our results.…”

“…Human brain exhibits hemispheric asymmetries in terms of structure and function (Toga and Thompson, 2003). In existing infant studies, cortical hemispheric asymmetries, which appear before term birth and largely preserve during postnatal brain development, have been observed in various cortical measurements, e.g., surface area, sulcal depth, cortical thickness, vertex position, as well as sulcal pits distribution (Hill et al, 2010;Li et al, 2014d;Meng et al, 2014;Li et al, 2015a;Le Guen et al, 2017;Takerkart et al, 2017;Im and Grant, 2018). Herein, we found hemispheric asymmetries present in STG and cingulate cortex by comparing our discovered cortical folding patterns in left and right hemispheres of both infant and adult brains.…”

Mindboggling morphometry of human brains

“…Depth is an important measure characterizing the highly folded surface of the human cerebral cortex. Since much of the surface is buried deep within these folds, an accurate measure of depth is useful for defining and extracting deep features, such as sulci [ 92 , 93 ], sulcal fundus curves [ 94 – 96 ], and sulcal pits [ 26 , 97 – 99 ]. Depth may also serve as an indicator of developmental stage [ 26 ].…”

Sparse description of the cortical surface pediatric development: A sulcal pits study

“…A major interest of sulcal pits is to define a finite set of robust landmarks on the cortical surface allowing local comparison across individuals. They have been often used to describe adult cortical morphometry [1] or atypical sulcal pattern in pathologies [2] but they have been largely neglected to study the typical post-birth cortical folding. The longitudinal study of [3] on the first two years of life highlighted a stable spatial distribution of pits in the few major deepest folds already present at term birth.…”

“…The identification of homologous pits across subjects, either by clustering after registration [5,6] or graph matching [7,1], is made difficult by the large inter-subject variability. Several studies avoid this issue by considering only the deepest folds (e.g.…”