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
Abacus-based mental calculation(AMC)training may improve mathematics-related abilities and transfer to other cognitive domains.Thus,it was hypothesized that inductive reasoning abilities can be improved by AMC trainin...Abacus-based mental calculation(AMC)training may improve mathematics-related abilities and transfer to other cognitive domains.Thus,it was hypothesized that inductive reasoning abilities can be improved by AMC training given the overlapping cognitive processes and neural correlates between AMC and inductive reasoning.The aim of the current study was to examine the underlying neurobiological mechanisms of this possible adaption by resting-state functional magnetic resonance imaging(rs-fMRI).Sixty-three children were randomly assigned to either the AMC-trained or the nontrained group.The AMC-trained group was required to perform abacus training for 2 hours per week for 5 years whereas the nontrained group was not required to perform any abacus training.Each participant’s rs-fMRI data were collected after abacus training,and regional homogeneity(ReHo)analysis was performed to determine the neural activity differences between groups.The participants’posttraining mathematical ability,intelligence quotients,and inductive reasoning ability were recorded and evaluated.The results revealed that AMC-trained children exhibited a significantly higher mathematical ability and inductive reasoning performance and higher ReHo in the rostrolateral prefrontal cortex(RLPFC)compared to the nontrained group.In particular,the increased ReHo in the RLPFC was found to be positively correlated with improved inductive reasoning performance.Our findings suggest that rs-fMRI may reflect the modulation of training in task-related networks.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.
基金supported partly by National Natural Science Foundation of China Grants 62076169 and 31270026National Social Science Foundation Grant 17ZDA323+2 种基金Beijing Nova Program Grant 2016000021223TD07National Key Research and Development Project of China Grants 2020YFC2007300 and 2020YFC2007302the Academy for Multidisciplinary Studies,Capital Normal University,and the Beijing Brain Initiative of Beijing Municipal Science&Technology Commission.
文摘Abacus-based mental calculation(AMC)training may improve mathematics-related abilities and transfer to other cognitive domains.Thus,it was hypothesized that inductive reasoning abilities can be improved by AMC training given the overlapping cognitive processes and neural correlates between AMC and inductive reasoning.The aim of the current study was to examine the underlying neurobiological mechanisms of this possible adaption by resting-state functional magnetic resonance imaging(rs-fMRI).Sixty-three children were randomly assigned to either the AMC-trained or the nontrained group.The AMC-trained group was required to perform abacus training for 2 hours per week for 5 years whereas the nontrained group was not required to perform any abacus training.Each participant’s rs-fMRI data were collected after abacus training,and regional homogeneity(ReHo)analysis was performed to determine the neural activity differences between groups.The participants’posttraining mathematical ability,intelligence quotients,and inductive reasoning ability were recorded and evaluated.The results revealed that AMC-trained children exhibited a significantly higher mathematical ability and inductive reasoning performance and higher ReHo in the rostrolateral prefrontal cortex(RLPFC)compared to the nontrained group.In particular,the increased ReHo in the RLPFC was found to be positively correlated with improved inductive reasoning performance.Our findings suggest that rs-fMRI may reflect the modulation of training in task-related networks.
