The human brain is highly plastic.Cognitive training is usually used to modify functional connectivity of brain networks.Moreover,the structures of brain networks may determine its dynamic behavior which is related to...The human brain is highly plastic.Cognitive training is usually used to modify functional connectivity of brain networks.Moreover,the structures of brain networks may determine its dynamic behavior which is related to human cognitive abilities.To study the effect of functional connectivity on the brain dynamics,the dynamic model based on functional connections of the brain and the Hindmarsh–Rose model is utilized in this work.The resting-state fMRI data from the experimental group undergoing abacus-based mental calculation(AMC)training and from the control group are used to construct the functional brain networks.The dynamic behavior of brain at the resting and task states for the AMC group and the control group are simulated with the above-mentioned dynamic model.In the resting state,there are the differences of brain activation between the AMC group and the control group,and more brain regions are inspired in the AMC group.A stimulus with sinusoidal signals to brain networks is introduced to simulate the brain dynamics in the task states.The dynamic characteristics are extracted by the excitation rates,the response intensities and the state distributions.The change in the functional connectivity of brain networks with the AMC training would in turn improve the brain response to external stimulus,and make the brain more efficient in processing tasks.展开更多
The organization of the brain follows a topologi-cal hierarchy that changes dynamically during development.However,it remains unknown whether and how cognitive training administered over multiple years during develop-...The organization of the brain follows a topologi-cal hierarchy that changes dynamically during development.However,it remains unknown whether and how cognitive training administered over multiple years during develop-ment can modify this hierarchical topology.By measuring the brain and behavior of school children who had carried out abacus-based mental calculation(AMC)training for five years(starting from 7 years to 12 years old)in pre-training and post-training,we revealed the reshaping effect of long-term AMC intervention during development on the brain hierarchical topology.We observed the development-induced emergence of the default network,AMC training-promoted shifting,and regional changes in cortical gradi-ents.Moreover,the training-induced gradient changes were located in visual and somatomotor areas in association with the visuospatial/motor-imagery strategy.We found that gradient-based features can predict the math ability within groups.Our findings provide novel insights into the dynamic nature of network recruitment impacted by long-term cognitive training during development.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.62276229 and 32071096).
文摘The human brain is highly plastic.Cognitive training is usually used to modify functional connectivity of brain networks.Moreover,the structures of brain networks may determine its dynamic behavior which is related to human cognitive abilities.To study the effect of functional connectivity on the brain dynamics,the dynamic model based on functional connections of the brain and the Hindmarsh–Rose model is utilized in this work.The resting-state fMRI data from the experimental group undergoing abacus-based mental calculation(AMC)training and from the control group are used to construct the functional brain networks.The dynamic behavior of brain at the resting and task states for the AMC group and the control group are simulated with the above-mentioned dynamic model.In the resting state,there are the differences of brain activation between the AMC group and the control group,and more brain regions are inspired in the AMC group.A stimulus with sinusoidal signals to brain networks is introduced to simulate the brain dynamics in the task states.The dynamic characteristics are extracted by the excitation rates,the response intensities and the state distributions.The change in the functional connectivity of brain networks with the AMC training would in turn improve the brain response to external stimulus,and make the brain more efficient in processing tasks.
基金supported by the National Natural Science Foundation of China(32071096 and 31270026)the National Social Science Foundation(17ZDA323)+3 种基金the STI 2030-Major Projects(2021ZD0200500)the Hong Kong Baptist University Research Committee Interdisciplinary Research Matching Scheme 2018/19(IRMS/18-19/SCI01)the Recruitment Program of Global Experts of Zhejiang Provincethe Start-up Funds for Leading Talents at Beijing Normal University and the National Basic Science Data Center“Chinese Data-sharing Warehouse for In-vivo Imaging Brain”(NBSDC-DB-15).
文摘The organization of the brain follows a topologi-cal hierarchy that changes dynamically during development.However,it remains unknown whether and how cognitive training administered over multiple years during develop-ment can modify this hierarchical topology.By measuring the brain and behavior of school children who had carried out abacus-based mental calculation(AMC)training for five years(starting from 7 years to 12 years old)in pre-training and post-training,we revealed the reshaping effect of long-term AMC intervention during development on the brain hierarchical topology.We observed the development-induced emergence of the default network,AMC training-promoted shifting,and regional changes in cortical gradi-ents.Moreover,the training-induced gradient changes were located in visual and somatomotor areas in association with the visuospatial/motor-imagery strategy.We found that gradient-based features can predict the math ability within groups.Our findings provide novel insights into the dynamic nature of network recruitment impacted by long-term cognitive training during development.