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Neuroimage. 2016 Jul 15;135:163-76. doi: 10.1016/j.neuroimage.2016.04.053. Epub 2016 May 3.

Development of cortical shape in the human brain from 6 to 24months of age via a novel measure of shape complexity.

Author information

1
Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, USA; Department of Psychiatry, University of North Carolina at Chapel Hill, NC, USA. Electronic address: shykim@email.unc.edu.
2
Department of Computer Science, University of North Carolina at Chapel Hill, NC, USA.
3
McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada.
4
Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA.
5
Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, USA.
6
Department of Radiology, University of Washington, Seattle, USA.
7
Department of Neuroradiology, Washington University, St. Louis, USA.
8
Department of Psychiatry, Washington University School of Medicine, St. Louis, USA.
9
Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
10
Tandon School of Engineering, Department of Computer Science and Engineering, NYU, New York, USA.
11
Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, USA; Department of Psychiatry, University of North Carolina at Chapel Hill, NC, USA; Department of Computer Science, University of North Carolina at Chapel Hill, NC, USA.

Abstract

The quantification of local surface morphology in the human cortex is important for examining population differences as well as developmental changes in neurodegenerative or neurodevelopmental disorders. We propose a novel cortical shape measure, referred to as the 'shape complexity index' (SCI), that represents localized shape complexity as the difference between the observed distributions of local surface topology, as quantified by the shape index (SI) measure, to its best fitting simple topological model within a given neighborhood. We apply a relatively small, adaptive geodesic kernel to calculate the SCI. Due to the small size of the kernel, the proposed SCI measure captures fine differences of cortical shape. With this novel cortical feature, we aim to capture comparatively small local surface changes that capture a) the widening versus deepening of sulcal and gyral regions, as well as b) the emergence and development of secondary and tertiary sulci. Current cortical shape measures, such as the gyrification index (GI) or intrinsic curvature measures, investigate the cortical surface at a different scale and are less well suited to capture these particular cortical surface changes. In our experiments, the proposed SCI demonstrates higher complexity in the gyral/sulcal wall regions, lower complexity in wider gyral ridges and lowest complexity in wider sulcal fundus regions. In early postnatal brain development, our experiments show that SCI reveals a pattern of increased cortical shape complexity with age, as well as sexual dimorphisms in the insula, middle cingulate, parieto-occipital sulcal and Broca's regions. Overall, sex differences were greatest at 6months of age and were reduced at 24months, with the difference pattern switching from higher complexity in males at 6months to higher complexity in females at 24months. This is the first study of longitudinal, cortical complexity maturation and sex differences, in the early postnatal period from 6 to 24months of age with fine scale, cortical shape measures. These results provide information that complement previous studies of gyrification index in early brain development.

KEYWORDS:

Age effect; And sexual dimorphism; Earth mover distance; Shape complexity index; Shape index

PMID:
27150231
PMCID:
PMC4915970
DOI:
10.1016/j.neuroimage.2016.04.053
[Indexed for MEDLINE]
Free PMC Article

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