Çelik Samet, Doğan Rümeysa Büşra, Parlatan Cennet Sena, Güntekin Bahar
Graduate School of Health Sciences, Program of Neuroscience Ph.D, Istanbul Medipol University, Istanbul, Turkey.
Health Application, and Research Center, Zonguldak Bulent Ecevit University, Zonguldak, Turkey.
Cogn Neurodyn. 2021 Aug;15(4):609-620. doi: 10.1007/s11571-020-09660-z. Epub 2021 Jan 8.
The body recognition process includes complex visual processing, the sensation, perception, and distinction stages of the stimulus. This study examined this process by using the time-frequency analysis of EEG signals and analyzed the obtained data by using the event-related oscillations method. This study aimed to examine the oscillatory brain responses and distinguish one's own body from other's body. In the present study, 17 young adults were included and the EEGs were recorded with 32 electrodes placed in different locations. Event-related power spectrum and phase-locking analyzes were performed. ITC and ERSP data were analyzed using 2 (condition) × 11 (location) × 2 (hemisphere) ANOVA Design. As we observed a prolonged response in the theta band in the grand averages, we included the time variable in the overall model. As a result, we found that the phase-locking and the event-related power spectrum of the theta response in recognizing one's own body were higher when compared to the phase-locking and the event-related power spectrum of the theta response in recognizing others' body ( < 0.05). When the time variable was included, the early theta response was more phase-locked and had a higher power spectrum compared to the late theta response ( < 0.05). As a result of the power spectrum analysis, the condition × hemisphere interaction effect in the beta band was higher in the left hemisphere regarding increased responses in recognizing one's own body ( < 0.05). As a result of ITC, the main effect of the condition was higher in the recognition of the stimulus of one's own body ( < 0.05). Finally, the theta oscillator response stood out in distinguishing one's own body from other's body. Similarly, the power spectrum in the beta response was higher in the left hemisphere, and this finding is consistent with the literature.
身体识别过程包括复杂的视觉处理以及刺激的感觉、知觉和区分阶段。本研究通过对脑电图信号进行时频分析来研究这一过程,并使用事件相关振荡方法分析所获得的数据。本研究旨在检测大脑的振荡反应,并将自己的身体与他人的身体区分开来。在本研究中,纳入了17名年轻成年人,并使用放置在不同位置的32个电极记录脑电图。进行了事件相关功率谱和锁相分析。使用2(条件)×11(位置)×2(半球)方差分析设计对ITC和ERSP数据进行分析。由于我们在总体平均值中观察到θ波段的反应延长,因此我们在总体模型中纳入了时间变量。结果发现,与识别他人身体时θ反应的锁相和事件相关功率谱相比,识别自己身体时θ反应的锁相和事件相关功率谱更高(<0.05)。当纳入时间变量时,早期θ反应比晚期θ反应更锁相且具有更高的功率谱(<0.05)。功率谱分析的结果显示,在β波段,关于识别自己身体时反应增加,左半球的条件×半球交互作用效应更高(<0.05)。ITC的结果显示,条件的主效应在识别自己身体的刺激时更高(<0.05)。最后,θ振荡反应在区分自己的身体与他人的身体方面表现突出。同样,β反应中的功率谱在左半球更高,这一发现与文献一致。