台大心理系

The brain needs to activate multiple networks in a temporally coordinated manner in order to perform cognitive tasks, and it needs to do so at different temporal scales, from the slowest cyrcadian cycles to fast subsecond rhythms. I propose a novel probabilistic framework to investigate brain functional reorganisation, capable to reliably access the dynamics contained in the signal even at the fastest time scales. Using this approach we investigate several aspects of the intrinsic dynamics of the human brain. First, we found that the brain spontaneously transitions between different networks in a predictable manner and follows a hierarchical organization that is remarkably simple. Importantly, this organisation is specific to individuals, is heritable and significantly relates to behavior, in the form of intelligence and different subject psychological traits. Second, we investigate the spectral properties of the default mode network using MEG, which is revealed to be composed of two components, anterior and posterior, with very distinct temporal and spectral properties. These two separated components exhibit strong coherence with the posterior cingulate cortex, yet in very different frequency regimes. The operation of these large-scale cortical networks in very different frequency bands may reflect the different intrinsic timescales that they specialise in, consistent with evidence from spike count autocorrelograms from single neurons.