Fluid and flexible minds: Intelligence reflects synchrony in the brain's intrinsic network architecture.
Fluid and flexible minds: Intelligence reflects synchrony in the brain's intrinsic network architecture.
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DOI：
10.1162/netn_a_00010
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Spreng RN
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文献类型：
--
作者：
Ferguson MA;Anderson JS;Spreng RN
人类智力一直被认为是一个由可分离的认知过程组成的复杂系统，然而调查智力的神经基础的研究通常强调离散的大脑区域的贡献，或者最近强调功能连接区域的特定网络的贡献。在这里，我们采取更广泛的系统视角来研究智能是否是大脑内在网络架构中同步的一种涌现特性。使用静息状态fMRI和认知数据的大样本（n = 830），我们报告了分布式大脑网络内部和之间的功能相互作用的同动性可靠地预测了流体和灵活的智力功能。通过采用全脑系统级方法，我们能够通过描述大脑内在网络结构的特征来可靠地预测人类智力的个体差异。这些发现为最终开发神经标记物来预测与神经发育、正常衰老和脑部疾病相关的智力功能变化带来了希望。在我们的研究中，我们旨在了解智力功能的个体差异如何反映在人类大脑的内在网络结构中。我们应用了被称为光谱分解的统计方法，以确定自发性大脑活动同步模式中的个体差异，这些模式可靠地预测了人类智力的核心方面。在多个离散神经网络中，休息时大脑活动的同步性与流体智力呈正相关。相反，大脑网络结构中的全局同步可靠地（相反地）预测了智力功能的核心方面——精神灵活性。这里描述的多网络系统方法代表了早期研究的方法论和概念延伸，这些研究将智力的差异与特定大脑区域、网络或它们之间的相互作用的变化联系起来。我们的研究结果表明，从网络神经科学的角度可以最完整地理解复杂的、综合的认知功能的神经基础。
Human intelligence has been conceptualized as a complex system of dissociable cognitive processes, yet studies investigating the neural basis of intelligence have typically emphasized the contributions of discrete brain regions or, more recently, of specific networks of functionally connected regions. Here we take a broader, systems perspective in order to investigate whether intelligence is an emergent property of synchrony within the brain’s intrinsic network architecture. Using a large sample of resting-state fMRI and cognitive data (n = 830), we report that the synchrony of functional interactions within and across distributed brain networks reliably predicts fluid and flexible intellectual functioning. By adopting a whole-brain, systems-level approach, we were able to reliably predict individual differences in human intelligence by characterizing features of the brain’s intrinsic network architecture. These findings hold promise for the eventual development of neural markers to predict changes in intellectual function that are associated with neurodevelopment, normal aging, and brain disease. In our study, we aimed to understand how individual differences in intellectual functioning are reflected in the intrinsic network architecture of the human brain. We applied statistical methods, known as spectral decompositions, in order to identify individual differences in the synchronous patterns of spontaneous brain activity that reliably predict core aspects of human intelligence. The synchrony of brain activity at rest across multiple discrete neural networks demonstrated positive relationships with fluid intelligence. In contrast, global synchrony within the brain’s network architecture reliably, and inversely, predicted mental flexibility, a core facet of intellectual functioning. The multinetwork systems approach described here represents a methodological and conceptual extension of earlier efforts that related differences in intellectual ability to variations in specific brain regions, networks, or their interactions. Our findings suggest that the neural basis of complex, integrative cognitive functions can be most completely understood from the perspective of network neuroscience.