Lv Guiyang, Xu Tianyong, Li Jinhang, Zhu Ping, Chen Feiyan, Yang Dongping, He Guoguang
School of Physics, Zhejiang University, Hangzhou, 310027, China; Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics and Information Engineering, Taizhou University, Taizhou, 318000, China.
School of Physics, Zhejiang University, Hangzhou, 310027, China.
Neuroimage. 2025 Mar;308:121055. doi: 10.1016/j.neuroimage.2025.121055. Epub 2025 Jan 30.
It has been widely observed that cognitive training can enhance the working memory capacity (WMC) of participants, yet the underlying mechanisms remain unexplained. Previous research has confirmed that abacus-based mental calculation (AMC) training can enhance the WMC of subjects and suggested its possible association with changes in functional connectivity. With fMRI data, we construct whole brain resting state connectivity of subjects who underwent long-term AMC training and other subjects from a control group. Their working memory capacity is simulated based on their whole brain resting state connectivity and reservoir computing. It is found that the AMC group has higher WMC than the control group, and especially the WMC involved in the frontoparietal network (FPN), visual network (VIS) and sensorimotor network (SMN) associated with the AMC training is even higher in the AMC group. However, the advantage of the AMC group disappears if the connection strengths between brain regions are neglected. The effects on WMC from the connection strength differences between the AMC and control groups are evaluated. The results show that the WMC of the control group is enhanced and achieved consistency with or even better than that the AMC group if the connection strength of the control group are weakened. And the advantage of FPN, VIS and SMN is reproduced too. In conclusion, our work reveals a correlation between reduction in functional connection strength and enhancements in the WMC of subjects undergoing cognitive training.
人们普遍观察到，认知训练可以提高参与者的工作记忆能力（WMC），但其潜在机制仍未得到解释。先前的研究证实，基于算盘的心算（AMC）训练可以提高受试者的WMC，并表明其可能与功能连接的变化有关。利用功能磁共振成像（fMRI）数据，我们构建了接受长期AMC训练的受试者以及对照组其他受试者的全脑静息状态连接性。基于他们的全脑静息状态连接性和储层计算来模拟他们的工作记忆能力。研究发现，AMC组的WMC高于对照组，尤其是与AMC训练相关的额顶网络（FPN）、视觉网络（VIS）和感觉运动网络（SMN）所涉及的WMC在AMC组中更高。然而，如果忽略脑区之间的连接强度，AMC组的优势就会消失。评估了AMC组和对照组之间连接强度差异对WMC的影响。结果表明，如果削弱对照组的连接强度，对照组的WMC会增强，并达到与AMC组一致甚至更好的水平。并且FPN、VIS和SMN的优势也会重现。总之，我们的工作揭示了功能连接强度降低与接受认知训练的受试者WMC增强之间的相关性。
