Effect of cognitive training on brain dynamics

• Published in: Chinese physics B Vol. 33; no. 2; pp. 28704 - 609
• Main Authors: Lv, Guiyang, Xu, Tianyong, Chen, Feiyan, Zhu, Ping, Wang, Miao, He, Guoguang
• Format: Journal Article
• Language: English
• Published: Chinese Physical Society and IOP Publishing Ltd 01.02.2024
• Subjects: abacus-based mental calculation; brian dynamics; cognitive training; functional brain networks; brian dynamics; abacus-based mental calculation; functional brain networks; cognitive training
• ISSN: 1674-1056; 2058-3834
• DOI: 10.1088/1674-1056/ad09c8

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.