Santarnecchi Emiliano, Khanna Arjun R, Musaeus Christian S, Benwell Christopher S Y, Davila Paula, Farzan Faranak, Matham Santosh, Pascual-Leone Alvaro, Shafi Mouhsin M
Berenson-Allen Center for Non-Invasive Brain Stimulation, Division of Cognitive Neurology, Beth Israel Medical Center, Harvard Medical School, 330 Brookline Ave, West/Baker 5, Boston, MA, 02215, USA.
Siena-Brain Investigation & Neuromodulation Lab (SiBIN), Department of Medicine, Surgery and Neuroscience, Neurology and Clinical Neurophysiology Section, University of Siena, Siena, Italy.
Brain Topogr. 2017 Jul;30(4):502-520. doi: 10.1007/s10548-017-0565-z. Epub 2017 May 10.
The neurobiological correlates of human fluid intelligence (Gf) remain elusive. Here, we demonstrate that spatiotemporal dynamics of EEG activity correlate with baseline measures of Gf and with its modulation by cognitive training. EEG dynamics were assessed in 74 healthy participants by examination of fast-changing, recurring, topographically-defined electric patterns termed "microstates", which characterize the electrophysiological activity of distributed cortical networks. We find that the frequency of appearance of specific brain topographies, spatially associated with visual (microstate B) and executive control (microstate C) networks, respectively, is inversely related to Gf scores. Moreover, changes in Gf scores with cognitive training are inversely correlated with changes in microstate properties, indicating that the changes in brain network dynamics are behaviorally relevant. Finally, we find that cognitive training that increases Gf scores results in a posterior shift in the topography of microstate C. These results highlight the role of fast-changing brain electrical states in individual variability in Gf and in the response to cognitive training.
人类流体智力(Gf)的神经生物学关联仍不明确。在此,我们证明脑电图活动的时空动态与Gf的基线测量值及其受认知训练的调节相关。通过检查被称为“微状态”的快速变化、反复出现、具有地形学定义的电模式来评估74名健康参与者的脑电图动态,这些微状态表征了分布式皮质网络的电生理活动。我们发现,分别与视觉(微状态B)和执行控制(微状态C)网络在空间上相关的特定脑地形图的出现频率与Gf分数呈负相关。此外,Gf分数随认知训练的变化与微状态属性的变化呈负相关,表明脑网络动态的变化具有行为相关性。最后,我们发现提高Gf分数的认知训练会导致微状态C的地形图向后移位。这些结果突出了快速变化的脑电状态在Gf个体差异及对认知训练反应中的作用。