McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada.
School of Physics, The University of Sydney, Sydney, Australia.
Elife. 2020 Dec 17;9:e62116. doi: 10.7554/eLife.62116.
The intrinsic dynamics of neuronal populations are shaped by both microscale attributes and macroscale connectome architecture. Here we comprehensively characterize the rich temporal patterns of neural activity throughout the human brain. Applying massive temporal feature extraction to regional haemodynamic activity, we systematically estimate over 6000 statistical properties of individual brain regions' time-series across the neocortex. We identify two robust spatial gradients of intrinsic dynamics, one spanning a ventromedial-dorsolateral axis and dominated by measures of signal autocorrelation, and the other spanning a unimodal-transmodal axis and dominated by measures of dynamic range. These gradients reflect spatial patterns of gene expression, intracortical myelin and cortical thickness, as well as structural and functional network embedding. Importantly, these gradients are correlated with patterns of meta-analytic functional activation, differentiating cognitive affective processing and sensory higher-order cognitive processing. Altogether, these findings demonstrate a link between microscale and macroscale architecture, intrinsic dynamics, and cognition.
神经元群体的内在动力学受到微观属性和宏观连接组结构的共同塑造。在这里，我们全面描述了人类大脑中丰富的神经活动时间模式。通过对区域性血液动力学活动进行大规模的时间特征提取，我们系统地估计了整个新皮层中超过 6000 个个体脑区时间序列的统计属性。我们确定了内在动力学的两个稳健的空间梯度，一个跨越腹侧-背侧轴，主要由信号自相关度量来主导，另一个跨越单模态-多模态轴，主要由动态范围度量来主导。这些梯度反映了基因表达、皮质内髓鞘和皮质厚度的空间模式，以及结构和功能网络嵌入的空间模式。重要的是，这些梯度与功能分析激活模式相关，区分了认知情感处理和感觉高级认知处理。总之，这些发现表明微观和宏观结构、内在动力学和认知之间存在联系。
