Decision Neuroscience Laboratory, University of Nebraska-Lincoln, NE 68501, United States.
Center for Brain, Biology, and Behavior, University of Nebraska-Lincoln, NE 68501, United States.
Cereb Cortex. 2023 Sep 26;33(19):10322-10331. doi: 10.1093/cercor/bhad284.
Cognitive neuroscience continues to advance our understanding of the neural foundations of human intelligence, with significant progress elucidating the role of the frontoparietal network in cognitive control mechanisms for flexible, intelligent behavior. Recent evidence in network neuroscience further suggests that this finding may represent the tip of the iceberg and that fluid intelligence may depend on the collective interaction of multiple brain networks. However, the global brain mechanisms underlying fluid intelligence and the nature of multi-network interactions remain to be well established. We therefore conducted a large-scale Connectome-based Predictive Modeling study, administering resting-state fMRI to 159 healthy college students and examining the contributions of seven intrinsic connectivity networks to the prediction of fluid intelligence, as measured by a state-of-the-art cognitive task (the Bochum Matrices Test). Specifically, we aimed to: (i) identify whether fluid intelligence relies on a primary brain network or instead engages multiple brain networks; and (ii) elucidate the nature of brain network interactions by assessing network allegiance (within- versus between-network connections) and network topology (strong versus weak connections) in the prediction of fluid intelligence. Our results demonstrate that whole-brain predictive models account for a large and significant proportion of variance in fluid intelligence (18%) and illustrate that the contribution of individual networks is relatively modest by comparison. In addition, we provide novel evidence that the global architecture of fluid intelligence prioritizes between-network connections and flexibility through weak ties. Our findings support a network neuroscience approach to understanding the collective role of brain networks in fluid intelligence and elucidate the system-wide network mechanisms from which flexible, adaptive behavior is constructed.
认知神经科学继续深入研究人类智力的神经基础，阐明了额顶网络在认知控制机制中的作用，为灵活智能行为提供了重要的认识。网络神经科学的最新证据进一步表明，这一发现可能只是冰山一角，流体智力可能依赖于多个脑网络的集体相互作用。然而，流体智力的全球脑机制和多网络相互作用的性质仍有待充分确立。因此，我们进行了一项大规模的基于连接组的预测建模研究，对 159 名健康大学生进行了静息态 fMRI 检测，并考察了七个内在连接网络对流体智力预测的贡献，其中流体智力由一项最先进的认知任务（Bochum 矩阵测试）来测量。具体来说，我们旨在：（i）确定流体智力是否依赖于主要的脑网络，还是同时涉及多个脑网络；（ii）通过评估预测流体智力时的网络隶属关系（网络内与网络间的连接）和网络拓扑（强连接与弱连接），阐明脑网络相互作用的性质。研究结果表明，全脑预测模型可以解释流体智力中很大且显著的变异性（18%），并且与比较而言，单个网络的贡献相对较小。此外，我们提供了新的证据，表明流体智力的整体结构通过弱连接优先考虑网络间的连接和灵活性。我们的研究结果支持了一种网络神经科学方法，用于理解脑网络在流体智力中的集体作用，并阐明了灵活、适应行为构建的系统范围的网络机制。
