Open AccessCortical Morphology in Autism: Findings from a Cortical Shape-Adaptive Approach to Local Gyrification Indexing
Author(s) -
Alisa R. Zoltowski,
Ilwoo Lyu,
Michelle D. Failla,
Lisa E. Mash,
Kacie Dunham,
Jacob Feldman,
Tiffany Woynaroski,
Mark T. Wallace,
Laura A. Barquero,
Tin Q Nguyen,
Laurie E. Cutting,
Hakmook Kang,
Bennett A. Landman,
Carissa J. Cascio
Publication year - 2021
Publication title -
cerebral cortex
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.694
H-Index - 250
eISSN - 1460-2199
pISSN - 1047-3211
DOI - 10.1093/cercor/bhab151
Subject(s) - gyrification , neurotypical , autism , psychology , neuroscience , brain morphometry , autism spectrum disorder , developmental psychology , cerebral cortex , magnetic resonance imaging , medicine , radiology
It has been challenging to elucidate the differences in brain structure that underlie behavioral features of autism. Prior studies have begun to identify patterns of changes in autism across multiple structural indices, including cortical thickness, local gyrification, and sulcal depth. However, common approaches to local gyrification indexing used in prior studies have been limited by low spatial resolution relative to functional brain topography. In this study, we analyze the aforementioned structural indices, utilizing a new method of local gyrification indexing that quantifies this index adaptively in relation to specific sulci/gyri, improving interpretation with respect to functional organization. Our sample included n = 115 autistic and n = 254 neurotypical participants aged 5-54, and we investigated structural patterns by group, age, and autism-related behaviors. Differing structural patterns by group emerged in many regions, with age moderating group differences particularly in frontal and limbic regions. There were also several regions, particularly in sensory areas, in which one or more of the structural indices of interest either positively or negatively covaried with autism-related behaviors. Given the advantages of this approach, future studies may benefit from its application in hypothesis-driven examinations of specific brain regions and/or longitudinal studies to assess brain development in autism.