论文部分内容阅读
目的研究双眼竞争的客观检测方法,并分析梭状回与视觉皮质的相关性。方法 6名受试者进行双眼竞争试验,受试者一只眼呈现8.57 Hz闪烁的平静表情面孔图片,另一只眼分别呈现12、15 Hz闪烁的恐惧表情面孔图片,并记录脑电图(electroencephalogram,EEG)信号。两个不同频率闪烁的刺激诱发稳态视觉诱发电位(steady state visual evoked potential,SSVEP),通过短时傅里叶变换(short time Fourier transformation,STFT)的时频分析方法,解析面孔刺激中双眼竞争的持续时间和交替频率,比较两侧梭状回面孔识别区(fusiform face area,FFA)与视觉皮质的相关系数。结果双眼竞争下左眼观看平静表情面孔的时长平均(411.6±73.8)ms,右眼观看恐惧表情面孔的时长平均(547.6±126.7)ms,不同组合下交替频率没有差异,左侧FFA与右侧相比,对恐惧表情面孔的加工更敏感,两侧FFA对恐惧表情面孔的加工没有频率差异。结论 SSVEP能作为双眼竞争中优势态感知的频率标记,成功对双眼竞争下视觉感知进行客观评价,双眼竞争和SSVEP结合的方法可用于视觉感知神经机制的研究。
Objective To study the objective detection method of binocular competition and to analyze the correlation between fusiform gyrus and visual cortex. Methods Six subjects were tested for binocular competition. One eye of the test subject showed a flickering 8.57 Hz facial expression, and the other showed a 12,15 Hz flicker of the facial expression of fear. EEG electroencephalogram, EEG) signal. Two flickering stimuli at different frequencies induced steady-state visual evoked potential (SSVEP) and analyzed the binocular rivalry in face stimulation by time-frequency analysis of short time Fourier transformation (STFT) Duration and frequency of alternation, and compared the correlation coefficients between fusiform face area (FFA) and visual cortex on both sides. Results The eyes of the left eye watched the facial expressions of the calm eyes for an average of (411.6 ± 73.8) ms while the eyes of the right eyes watched the faces of the fearsome faces for an average of (547.6 ± 126.7) ms. There was no difference in the alternation frequencies between the two groups. Compared to the more sensitive to the processing of fear facial expressions, the frequency of the FFA on both sides of the processing of fear facial expression there is no frequency difference. Conclusion SSVEP can be used as a frequency marker of dominant state perception in binocular competition, and objective assessment of visual perception under binocular competition is successful. The combination of binocular competition and SSVEP can be used to study the neural mechanism of visual perception.