Land Michael F, Furneaux Sophie M, Gilchrist Iain D
School of Biological Sciences, University of Sussex, Brighton BN1 9QG, UK.
Neurocase. 2002;8(1-2):80-7. doi: 10.1093/neucas/8.1.80.
We investigated the visual strategy of a subject without eye movements (AI), comparing her with normal subjects on the 'real-life' task of making a cup of tea. Differences in overall performance were surprisingly few. She took no more time than the controls to complete the tea-making task and the division of the task into object-related actions was essentially similar. However, the way AI took in visual information was very different from the normal subjects who used a typical 'saccade and fixate' strategy when moving between and scrutinizing objects. AI made saccades with the head, which were on average 1.5 times larger than the eye-head saccades of the controls and lasted four times as long, meaning that AI would have had impaired vision for more of the time than the controls. She also made only approximately one-third as many saccades as normals during the same task. However, she had another strategy, 'slow drift', in which she allowed her eyes to move smoothly across the scene at speeds of up to 30 degrees /s. Such movements were never seen in the controls, and we assume that AI used them to offset the cost in time of the slow head saccades, even though they had their own cost in terms of reduced resolution. We demonstrate that these differences have a minimal effect on the timings of events during an object-related action. We discuss supervisory checking operations within actions, and consider what information is needed for appropriate gaze control during object-related actions.
我们研究了一名无眼球运动受试者（人工智能）的视觉策略，并将她在“现实生活”中泡茶任务上的表现与正常受试者进行比较。整体表现上的差异出奇地少。她完成泡茶任务所花的时间并不比对照组多，并且将任务划分为与物体相关的动作基本上是相似的。然而，人工智能获取视觉信息的方式与正常受试者非常不同，正常受试者在观察和审视物体时采用典型的“扫视和注视”策略。人工智能通过头部进行扫视，其平均幅度比对照组的眼-头扫视幅度大1.5倍，持续时间长四倍，这意味着人工智能视力受损的时间比对照组更多。在同一任务中，她进行的扫视次数也只有正常人的约三分之一。然而，她还有另一种策略，即“缓慢漂移”，她让眼睛以高达30度/秒的速度在场景中平稳移动。对照组中从未见过这种运动，我们认为人工智能使用它们来抵消缓慢的头部扫视在时间上的代价，尽管它们在分辨率降低方面也有自身的代价。我们证明，这些差异对与物体相关动作中事件的时间安排影响极小。我们讨论了动作中的监督检查操作，并考虑在与物体相关动作中进行适当的注视控制需要哪些信息。
