Camalier C R, Gotler A, Murthy A, Thompson K G, Logan G D, Palmeri T J, Schall J D
Department of Psychology, Wilson Hall, Center for Integrative and Cognitive Neuroscience, Vanderbilt Vision Research Center, Vanderbilt University, 111 21st Avenue South, Nashville, TN 37203, USA.
Vision Res. 2007 Jul;47(16):2187-211. doi: 10.1016/j.visres.2007.04.021. Epub 2007 Jul 2.
We investigated how saccade target selection by humans and macaque monkeys reacts to unexpected changes of the image. This was explored using double step and search step tasks in which a target, presented alone or as a singleton in a visual search array, steps to a different location on infrequent, random trials. We report that human and macaque monkey performance are qualitatively indistinguishable. Performance is stochastic with the probability of producing a compensated saccade to the final target location decreasing with the delay of the step. Compensated saccades to the final target location are produced with latencies relative to the step that are comparable to or less than the average latency of saccades on trials with no target step. Noncompensated errors to the initial target location are produced with latencies less than the average latency of saccades on trials with no target step. Noncompensated saccades to the initial target location are followed by corrective saccades to the final target location following an intersaccade interval that decreases with the interval between the target step and the initiation of the noncompensated saccade. We show that this pattern of results cannot be accounted for by a race between two stochastically independent processes producing the saccade to the initial target location and another process producing the saccade to the final target location. However, performance can be accounted for by a race between three stochastically independent processes--a GO process producing the saccade to the initial target location, a STOP process interrupting that GO process, and another GO process producing the saccade to the final target location. Furthermore, if the STOP process and second GO process start at the same time, then the model can account for the incidence and latency of mid-flight corrections and rapid corrective saccades. This model provides a computational account of saccade production when the image changes unexpectedly.
我们研究了人类和猕猴的扫视目标选择如何对图像的意外变化做出反应。这是通过双步和搜索步任务进行探究的,在这些任务中,单独呈现或作为视觉搜索阵列中的单独元素的目标,在不频繁的随机试验中会移动到不同的位置。我们报告称,人类和猕猴的表现从质的方面来看难以区分。表现具有随机性,产生向最终目标位置的补偿性扫视的概率会随着步移的延迟而降低。相对于步移而言,向最终目标位置的补偿性扫视的潜伏期与无目标步移试验中扫视的平均潜伏期相当或更短。向初始目标位置的非补偿性错误产生的潜伏期比无目标步移试验中扫视的平均潜伏期要短。向初始目标位置的非补偿性扫视之后会跟着向最终目标位置的校正性扫视,校间扫视间隔会随着目标步移与非补偿性扫视启动之间的间隔而缩短。我们表明,这种结果模式无法用产生向初始目标位置的扫视的两个随机独立过程与产生向最终目标位置的扫视的另一个过程之间的竞争来解释。然而,表现可以用三个随机独立过程之间的竞争来解释——一个产生向初始目标位置的扫视的启动过程、一个中断该启动过程的停止过程,以及另一个产生向最终目标位置的扫视的启动过程。此外,如果停止过程和第二个启动过程同时开始,那么该模型就能解释飞行中校正和快速校正性扫视的发生率和潜伏期。该模型为图像意外变化时扫视产生提供了一种计算解释。