Visual Neuroscience Group, School of Psychology, University of Nottingham, Nottingham, United Kingdom.
School of Optometry & Vision Science, Faculty of Life Sciences, University of Bradford, Bradford, United Kingdom.
Invest Ophthalmol Vis Sci. 2018 Nov 1;59(13):5408-5416. doi: 10.1167/iovs.18-24674.
Even during steady fixation, people make small eye movements such as microsaccades, whose rate is altered by presentation of salient stimuli. Our goal was to develop a practical method for objectively and robustly estimating contrast sensitivity from microsaccade rates in a diverse population.
Participants, recruited to cover a range of contrast sensitivities, were visually normal (n = 19), amblyopic (n = 10), or had cataract (n = 9). Monocular contrast sensitivity was estimated behaviorally while binocular eye movements were recorded during interleaved passive trials. A probabilistic inference approach was used to establish the likelihood of observed microsaccade rates given the presence or absence of a salient stimulus. Contrast sensitivity was estimated from a function fitted to the scaled log-likelihood ratio of the observed microsaccades in the presence or absence of a salient stimulus across a range of contrasts.
Microsaccade rate signature shapes were heterogeneous; nevertheless, estimates of contrast sensitivity could be obtained in all participants. Microsaccade-estimated contrast sensitivity was unbiased compared to behavioral estimates (1.2% mean), with which they were strongly correlated (Spearman's ρ 0.74, P < 0.001, median absolute difference 7.6%). Measurement precision of microsaccade-based contrast sensitivity estimates was worse than that of behavioral estimates, requiring more than 20 times as many presentations to equate precision.
Microsaccade rate signatures are heterogeneous in shape when measured across populations with a broad range of contrast sensitivities. Contrast sensitivity can be robustly estimated from rate signatures by probabilistic inference, but more stimulus presentations are currently required to achieve similarly precise estimates to behavioral techniques.
即使在稳定注视时，人们也会进行微小的眼球运动，如微扫视，其频率会因显著刺激的呈现而改变。我们的目标是开发一种实用的方法，从不同人群的微扫视率中客观、稳健地估计对比敏感度。
参与者的招募范围涵盖了各种对比敏感度，包括视力正常者（n=19）、弱视者（n=10）和白内障患者（n=9）。在进行间歇性被动试验时，同时记录双眼运动，以行为方式估计单眼对比敏感度。使用概率推理方法，根据显著刺激的存在或缺失，确定观察到的微扫视率的可能性。通过拟合观察到的微扫视在存在或不存在显著刺激时的对数似然比的函数，从观察到的微扫视中估计对比敏感度。
微扫视率特征形状存在异质性；然而，能够在所有参与者中获得对比敏感度的估计值。微扫视估计的对比敏感度与行为估计相比是无偏的（平均 1.2%），两者具有很强的相关性（Spearman's ρ 0.74，P<0.001，中位数绝对差 7.6%）。基于微扫视的对比敏感度估计的测量精度比行为估计差，需要超过 20 倍的呈现次数才能达到相同的精度。
当在具有广泛对比敏感度范围的人群中进行测量时，微扫视率特征的形状存在异质性。可以通过概率推理从率特征中稳健地估计对比敏感度，但目前需要更多的刺激呈现次数才能达到与行为技术相当的精确估计。
