Learning optimal eye movements to unusual faces.
Learning optimal eye movements to unusual faces.
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DOI：
10.1016/j.visres.2013.11.005
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发表时间：
2014-06
期刊：
影响因子：
1.8
通讯作者：
Eckstein, Miguel P.
中科院分区：
文献类型：
--
作者：
Peterson, Matthew F.;Eckstein, Miguel P.
眼球运动将中央凹的高分辨率和计算能力引导到视觉场景的相关区域，对于高效、成功地完成许多视觉任务至关重要。人类如何通过感知环境的经验来改变眼球运动，及其在学习新任务中的功能作用尚未得到充分研究。在这里，我们使用了面部识别任务，其中仅通过嘴部区分样本来评估眼动调节是否、如何以及何时可以介导学习。通过将不受约束的眼球运动试验与强制注视试验交织在一起，我们试图将眼球运动和隐蔽机制对性能改进的贡献分开。在没有指导的情况下，大多数观察者大大提高了准确性，并学会了将他们最初的眼球运动引向最佳注视点。观察者的默认面部识别眼动行为与新的最佳注视点的接近程度以及观察者的外围处理能力可以预测性能增益和眼动学习。在随后的条件下进行练习后，观察者被引导注视面部的不同位置，包括相关的嘴部区域，所有观察者都学会了将眼球移动到最佳注视点。在这种完全学习的状态下，增强固定策略占总效率提高的 43%，而隐蔽机制占剩余的 57%。研究结果表明，眼动计划对感知学习起着至关重要的作用，并阐明了可以预测观察者何时以及如何能够通过不寻常的范例学习新任务的因素。
Eye movements, which guide the fovea’s high resolution and computational power to relevant areas of the visual scene, are integral to efficient, successful completion of many visual tasks. How humans modify their eye movements through experience with their perceptual environments, and its functional role in learning new tasks, has not been fully investigated. Here, we used a face identification task where only the mouth discriminated exemplars to assess if, how, and when eye movement modulation may mediate learning. By interleaving trials of unconstrained eye movements with trials of forced fixation, we attempted to separate the contributions of eye movements and covert mechanisms to performance improvements. Without instruction, a majority of observers substantially increased accuracy and learned to direct their initial eye movements towards the optimal fixation point. The proximity of an observer’s default face identification eye movement behavior to the new optimal fixation point and the observer’s peripheral processing ability were predictive of performance gains and eye movement learning. After practice in a subsequent condition in which observers were directed to fixate different locations along the face, including the relevant mouth region, all observers learned to make eye movements to the optimal fixation point. In this fully learned state, augmented fixation strategy accounted for 43% of total efficiency improvements while covert mechanisms accounted for the remaining 57%. The findings suggest a critical role for eye movement planning to perceptual learning, and elucidate factors that can predict when and how well an observer can learn a new task with unusual exemplars.
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