Ramchandran Kanchna, Zeien Eugene, Andreasen Nancy C
University of Iowa, Department of Psychiatry, Carver College of Medicine, 200 Hawkins Drive, Iowa City, IA 52242, United States.
University of Iowa, Department of Psychiatry, Carver College of Medicine, 200 Hawkins Drive, Iowa City, IA 52242, United States.
Trends Neurosci Educ. 2019 Jun;15:48-61. doi: 10.1016/j.tine.2019.02.006. Epub 2019 Mar 19.
Whether superior intelligence is associated with global lower resource consumption in the brain remains unresolved. In order to tap fluid intelligence "Gf" cortical networks, 50 neurologically healthy adults were functionally neuro-imaged while solving a modified version of the Raven Advanced Progressive Matrices. "Gf" predicted increased activation of key components of the dorsal attention network (DAN); and age predicted extent of simultaneous deactivation in key components of the default mode network (DMN) during problem-solving. However, there was no significant difference in mean levels of whole brain activation even when cognitively taxed. This suggests that the brain may dynamically switch resource consumption between these anti-correlated DAN and DMN networks, concentrating processing power in regions critical to enhanced cognitive performance. We term this mechanism of activation increase and decrease of these anti-correlated DAN/DMN systems, modulated by "Gf" and age, as "distributed neural efficiency". This may achieve local cost-efficiency trade-offs, while maintaining global energy homeostasis.
智力超群是否与大脑整体资源消耗较低相关，这一问题仍未得到解决。为了探究流体智力（“Gf”）与皮质网络的关系，50名神经健康的成年人在解决改良版瑞文高级渐进矩阵测验时接受了功能性神经成像。“Gf”预示着背侧注意网络（DAN）关键组件的激活增加；年龄预示着在解决问题过程中默认模式网络（DMN）关键组件同时失活的程度。然而，即使在认知负荷下，全脑激活的平均水平也没有显著差异。这表明大脑可能会在这些反相关的DAN和DMN网络之间动态切换资源消耗，将处理能力集中在对提高认知表现至关重要的区域。我们将这种由“Gf”和年龄调节的反相关DAN/DMN系统激活增加和减少的机制称为“分布式神经效率”。这可能在实现局部成本效益权衡的同时，维持整体能量稳态。
