Researchers from the Laboratory of Brain Imaging, at the Institute of Neuroscience (ION), Shanghai Institutes for Biological Sciences, CAS, revealed dynamic changes of brain connectomics for inherent functional flexibility, in which dissociable changes of frontal and parietal cortices occurred across the human life span, using a Shannon entropy-based method.
Humans are unrivaled in their capacity to adaptively implement a wide variety of goal-directed tasks. Recent research has demonstrated that the human capability for adaptive task control is intimately related to the flexible operation of frontoparietal network. However, it remains unclear whether this flexibly functional reconfiguration is intrinsic and occurs in the absence of an overt task. To this aim, researchers proposed a probabilistic framework in which dynamic reconfiguration of intrinsic functional connectivity between brain regions can be represented as a probability distribution (Panel A).
A complexity measurement (i.e., entropy) was then applied to quantify functional flexibility, the heterogeneity of dynamic connectivity between a particular region and others over time. The researchers identified regions showing high flexibility mainly in the higher-order association cortices (e.g., LPFC, lateral parietal cortex, and lateral temporal lobes).
In contrast, primary sensory (e.g., visual and auditory) areas exhibited low flexibility (Panel B). Using multiple regression analysis, the researchers further found that flexibility of the right LPFC improved during maturation and reduced due to normal aging, with the opposite occurring for the left lateral parietal cortex (Panel C).
This study not only provides a new framework to quantify the spatiotemporal characteristics of functional brain connectomics, but also sheds light on the organizational principle behind changes in brain function across the human life span.
This work entitled "Dissociable Changes of Frontal and Parietal Cortices in Inherent Functional Flexibility across the Human Life Span” was published online in the Journal of Neuroscience on Sept. 28.
This work was completed by Dr. YIN Dazhi, under the supervision of Profs. WANG Zheng and CHENG Wenhong, and funded by the Hundred Talents Program of the CAS, Strategic Priority Research Program (B) of the CAS(XDB02050006), Shanghai Education Committee(HJTY2012-A06), NSFC(81471651,81571300), and Shanghai Institute for Biological Sciences, CAS(2014KIP206).
Figure legend：(A) Illustration of the probabilistic model. Dynamic functional connectivity matrices were firstly obtained for each participant using a sliding window approach. Subsequently, a local thresholding method was used to reserve its k(e.g., k =5 shown here) strongest functional connections (red lines) for a given region at each time window. Then, a probability distribution Pi( j…n)was obtained, reflecting the frequency of each connection with i emerged across the temporal windows. A complexity measure (i.e., entropy Hi) was finally applied to this probability distribution to quantify functional flexibility of region i. (B) Brain map for inherent functional flexibility. The color bar indicates the degree of flexibility. Red colors denote high flexibility and blue colors denote low flexibility. (C) Age-related changes of functional flexibility in the left supramarginal gyrus (SMG) and right middle frontal gyrus (MFG). (Image provided by Dr. WANG Zheng's group)
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