| Literature DB >> 30541110 |
Huan Liu1, Shu Zhang2, Xi Jiang3, Tuo Zhang4, Heng Huang1, Fangfei Ge1,2, Lin Zhao1, Xiao Li1, Xintao Hu1, Junwei Han1, Lei Guo1, Tianming Liu2.
Abstract
The human cerebral cortex is highly folded into diverse gyri and sulci. Accumulating evidences suggest that gyri and sulci exhibit anatomical, morphological, and connectional differences. Inspired by these evidences, we performed a series of experiments to explore the frequency-specific differences between gyral and sulcal neural activities from resting-state and task-based functional magnetic resonance imaging (fMRI) data. Specifically, we designed a convolutional neural network (CNN) based classifier, which can differentiate gyral and sulcal fMRI signals with reasonable accuracies. Further investigations of learned CNN models imply that sulcal fMRI signals are more diverse and more high frequency than gyral signals, suggesting that gyri and sulci truly play different functional roles. These differences are significantly associated with axonal fiber wiring and cortical thickness patterns, suggesting that these differences might be deeply rooted in their structural and cellular underpinnings. Further wavelet entropy analyses demonstrated the validity of CNN-based findings. In general, our collective observations support a new concept that the cerebral cortex is bisectionally segregated into 2 functionally different units of gyri and sulci.Entities:
Keywords: cerebral cortex; convolutional neural network; gyri; sulci; wavelet entropy
Year: 2019 PMID: 30541110 PMCID: PMC6735260 DOI: 10.1093/cercor/bhy305
Source DB: PubMed Journal: Cereb Cortex ISSN: 1047-3211 Impact factor: 5.357