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Recently, Fang Fang’s research group from the School of Psychology and Cognitive Sciences of Peking University has published research papers in Brain Stimulation , a top journal in the field of neuromodulation , and found that transcranial electrical stimulation technology can effectively improve the performance of visual perception learning
Plasticity has been one of the hot research topics in neuroscience
Visual perceptual learning refers to the phenomenon that the visual function is greatly improved under the action of repeated practice and other visual experience, which can be reflected in behavioral indicators such as the increase of the correct rate of judgment, the shortening of the reaction time and the reduction of the threshold value
At the same time, the fashionable non-invasive neuromodulation technology can rapidly change the neural activity of the brain, and has been widely used in the fields of basic neurology, rehabilitation therapy and cognitive enhancement due to its high safety, simple operation and low cost.
In order to determine the intrinsic neural oscillation frequencies that govern visual perceptual learning, Fang Fang’s group applied tACS of different frequencies to the visual cortex during the process of performing the discrimination task (as shown in Figure 2), which induced changes in the brain’s intrinsic neural oscillatory activity.
Figure 1.
Figure 2.
Figure 3.
In order to explore the regulatory role of altered cortical excitability on visual perceptual learning during the early consolidation phase after training, in another study, the research group used a texture discrimination task widely used in visual perceptual learning consolidation research as an experimental task
Figure 4.
Figure 5.
These studies will help to understand the neural mechanisms of the occurrence and consolidation of visual perceptual learning, and also provide new strategies for visual function enhancement in special application scenarios, such as clinical rehabilitation, military operations, and sports training
This series of research was supported by the National Natural Science Foundation of China Key Project (31930053) and Beijing Zhiyuan Artificial Intelligence Research Institute
Paper information:
He, Q.
Yang, XY#, He, Q.