Carnegie Mellon University, Department of Psychology, CAOs Laboratory, USA.
Carnegie Mellon University, Department of Psychology, CAOs Laboratory, USA.
Cortex. 2023 Jun;163:14-25. doi: 10.1016/j.cortex.2023.02.008. Epub 2023 Mar 18.
Temporal characteristics of neural signals are often overlooked in traditional fMRI developmental studies but are critical to studying brain functions in ecologically valid settings. In the present study, we explore the temporal properties of children's neural responses during naturalistic mathematics and grammar tasks. To do so, we introduce a novel measure in developmental fMRI: neural entropy, which indicates temporal complexity of BOLD signals. We show that temporal patterns of neural activity have lower complexity and greater variability in children than in adults in the association cortex but not in the sensory-motor cortex. We also show that neural entropy is associated with both child-adult similarity in functional connectivity and neural synchrony, and that neural entropy increases with the size of functionally connected networks in the association cortex. In addition, neural entropy increases with functional maturity (i.e., child-adult neural synchrony) in content-specific regions. These exploratory findings suggest the hypothesis that neural entropy indexes the increasing breadth and diversity of neural processes available to children for analyzing mathematical information over development.
在传统的 fMRI 发育研究中，神经信号的时间特征经常被忽视，但对于在生态上有效的环境中研究大脑功能至关重要。在本研究中，我们探讨了儿童在自然数学和语法任务期间神经反应的时间特性。为此，我们在发育 fMRI 中引入了一种新的测量方法：神经熵，它表示 BOLD 信号的时间复杂性。我们发现，与成年人相比，儿童的关联皮层的神经活动时间模式的复杂性较低，变异性较大，但感觉运动皮层则并非如此。我们还发现，神经熵与功能连接和神经同步中的儿童与成年人之间的相似性有关，并且与关联皮层中功能连接网络的大小有关。此外，神经熵随功能成熟度（即儿童与成年人的神经同步性）增加，在特定内容的区域中增加。这些探索性发现表明了这样的假设，即神经熵索引了儿童在发展过程中用于分析数学信息的可用神经过程的广度和多样性的增加。
