Zhang Xinni, Dai Mengshi, Cheng Feiyan, Yun Lijun, Chen Zaiqing
School of Information Science and Technology, Yunnan Normal University, Kunming 650500, China;
Engineering Research Center of Computer Vision and Intelligent Control Technology, Department of Education of Yunnan Province, Kunming 650500, China;
J Eye Mov Res. 2025 Apr 5;18(2):10. doi: 10.3390/jemr18020010. eCollection 2025 Apr.
Color fusion and rivalry are two key information integration mechanisms in binocular vision, representing the visual system's processing patterns for consistent and conflicting inputs, respectively. This study hypothesizes that there are quantifiable differences in eye movement indicators under states of binocular color fusion and rivalry, which can be verified through multi-paradigm eye movement experiments. The experiment recruited eighteen subjects with normal vision (nine males and nine females), employing the Gaze Stability paradigm, Straight Curve Eye Hopping paradigm, and Smoothed Eye Movement Tracking paradigm for eye movement tracking. Each paradigm included a binocular color rivalry experimental group (R-G) and two binocular color fusion control groups (R-R, G-G). Data analysis indicates significant differences in indicators such as Average Saccade Amplitude, Median Saccade Amplitude, and SD of Saccade Amplitude between binocular color fusion and rivalry states. For instance, through Z-Score normalization and cross-paradigm merged analysis, specific ranges of these indicators were identified to distinguish between the two states. When the Average Saccade Amplitude falls within the range of -0.905--0.693, it indicates a state of binocular color rivalry; when the range is 0.608-1.294, it reflects a state of binocular color fusion. Subsequently, ROC curve analysis confirmed the effectiveness of the experimental paradigms in analyzing the mechanisms of binocular color fusion and rivalry, with AUC values of 0.990, 0.741, and 0.967, respectively. These results reveal the potential of eye movement behaviors as biomarkers for the dynamic processing of visual conflicts. This finding provides empirical support for understanding the neural computational models of binocular vision and lays a methodological foundation for developing visual impairment assessment tools based on eye movement features.
颜色融合和竞争是双眼视觉中的两种关键信息整合机制，分别代表视觉系统对一致和冲突输入的处理模式。本研究假设，在双眼颜色融合和竞争状态下，眼动指标存在可量化的差异，这可以通过多范式眼动实验来验证。该实验招募了18名视力正常的受试者（9名男性和9名女性），采用凝视稳定性范式、直线曲线眼跳范式和平滑眼动跟踪范式进行眼动跟踪。每个范式都包括一个双眼颜色竞争实验组（R-G）和两个双眼颜色融合对照组（R-R、G-G）。数据分析表明，双眼颜色融合和竞争状态之间在平均扫视幅度、中值扫视幅度和扫视幅度标准差等指标上存在显著差异。例如，通过Z分数归一化和跨范式合并分析，确定了这些指标的特定范围以区分这两种状态。当平均扫视幅度落在-0.905--0.693范围内时，表明处于双眼颜色竞争状态；当范围为0.608-1.294时，则反映双眼颜色融合状态。随后，ROC曲线分析证实了实验范式在分析双眼颜色融合和竞争机制方面的有效性，AUC值分别为0.990、0.741和0.967。这些结果揭示了眼动行为作为视觉冲突动态处理生物标志物的潜力。这一发现为理解双眼视觉的神经计算模型提供了实证支持，并为基于眼动特征开发视觉障碍评估工具奠定了方法基础。
