School of Automation, Northwestern Polytechnical University, Xi'an, China.
Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, USA.
Cereb Cortex. 2019 Sep 13;29(10):4238-4252. doi: 10.1093/cercor/bhy305.
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.
人类大脑皮层高度折叠成不同的脑回和脑沟。越来越多的证据表明,脑回和脑沟在解剖结构、形态和连接上存在差异。受这些证据的启发,我们进行了一系列实验,从静息态和任务态功能磁共振成像 (fMRI) 数据中探索脑回和脑沟神经活动的频率特异性差异。具体来说,我们设计了一个基于卷积神经网络 (CNN) 的分类器,可以合理准确地区分脑回和脑沟 fMRI 信号。对学习到的 CNN 模型的进一步研究表明,脑沟 fMRI 信号比脑回信号更加多样化和高频,这表明脑回和脑沟确实发挥着不同的功能作用。这些差异与轴突纤维布线和皮质厚度模式显著相关,表明这些差异可能深深植根于它们的结构和细胞基础。进一步的小波熵分析证明了基于 CNN 的发现的有效性。总的来说,我们的综合观察支持了一个新的概念,即大脑皮层被分为两个功能上不同的单位,即脑回和脑沟。