Wang Hongmei, Yao Renhuan, Zhang Xiaoyan, Chen Chao, Wu Jia, Dong Minghao, Jin Chenwang
Department of Radiology, First Affiliated Hospital of Xi'an, Jiaotong University, Xi'an, China.
Department of Medical Imaging, Inner Mongolia People's Hospital, Hohhot, China.
Front Neurosci. 2023 May 17;17:1152619. doi: 10.3389/fnins.2023.1152619. eCollection 2023.
Visual expertise reflects accumulated experience in reviewing domain-specific images and has been shown to modulate brain function in task-specific functional magnetic resonance imaging studies. However, little is known about how visual experience modulates resting-state brain network dynamics. To explore this, we recruited 22 radiology interns and 22 matched healthy controls and used resting-state functional magnetic resonance imaging (rs-fMRI) and the degree centrality (DC) method to investigate changes in brain network dynamics. Our results revealed significant differences in DC between the RI and control group in brain regions associated with visual processing, decision making, memory, attention control, and working memory. Using a recursive feature elimination-support vector machine algorithm, we achieved a classification accuracy of 88.64%. Our findings suggest that visual experience modulates resting-state brain network dynamics in radiologists and provide new insights into the neural mechanisms of visual expertise.
视觉专业技能反映了在审查特定领域图像方面积累的经验，并且在特定任务的功能磁共振成像研究中已被证明可以调节大脑功能。然而，关于视觉经验如何调节静息状态下的脑网络动力学，我们知之甚少。为了探究这一点，我们招募了22名放射科实习生和22名匹配的健康对照者，并使用静息状态功能磁共振成像（rs-fMRI）和度中心性（DC）方法来研究脑网络动力学的变化。我们的结果显示，放射科实习生组和对照组在与视觉处理、决策、记忆、注意力控制和工作记忆相关的脑区的度中心性存在显著差异。使用递归特征消除-支持向量机算法，我们实现了88.64%的分类准确率。我们的研究结果表明，视觉经验会调节放射科医生静息状态下的脑网络动力学，并为视觉专业技能的神经机制提供了新的见解。
