Van Pelt Stan, Medendorp W Pieter
Nijmegen Institute for Cognition and Information, Radboud University Nijmegen, Nijmegen, The Netherlands.
J Neurophysiol. 2008 May;99(5):2281-90. doi: 10.1152/jn.01281.2007. Epub 2008 Mar 19.
We tested between two coding mechanisms that the brain may use to retain distance information about a target for a reaching movement across vergence eye movements. If the brain was to encode a retinal disparity representation (retinal model), i.e., target depth relative to the plane of fixation, each vergence eye movement would require an active update of this representation to preserve depth constancy. Alternatively, if the brain was to store an egocentric distance representation of the target by integrating retinal disparity and vergence signals at the moment of target presentation, this representation should remain stable across subsequent vergence shifts (nonretinal model). We tested between these schemes by measuring errors of human reaching movements (n = 14 subjects) to remembered targets, briefly presented before a vergence eye movement. For comparison, we also tested their directional accuracy across version eye movements. With intervening vergence shifts, the memory-guided reaches showed an error pattern that was based on the new eye position and on the depth of the remembered target relative to that position. This suggests that target depth is recomputed after the gaze shift, supporting the retinal model. Our results also confirm earlier literature showing retinal updating of target direction. Furthermore, regression analyses revealed updating gains close to one for both target depth and direction, suggesting that the errors arise after the updating stage during the subsequent reference frame transformations that are involved in reaching.
我们测试了大脑在跨越聚散眼球运动进行伸手够物动作时,可能用于保留目标距离信息的两种编码机制。如果大脑要编码视网膜视差表征(视网膜模型),即目标相对于注视平面的深度,每次聚散眼球运动都需要对该表征进行主动更新,以保持深度恒常性。或者,如果大脑要在目标呈现时通过整合视网膜视差和聚散信号来存储目标的自我中心距离表征,那么在随后的聚散变化过程中,该表征应保持稳定(非视网膜模型)。我们通过测量人类(n = 14名受试者)对记忆目标的伸手动作误差来测试这两种方案,这些目标在聚散眼球运动之前短暂呈现。为了进行比较,我们还测试了它们在版本眼球运动中的方向准确性。在有聚散变化介入的情况下,记忆引导的伸手动作显示出一种基于新眼位以及记忆目标相对于该位置的深度的误差模式。这表明在注视转移后会重新计算目标深度,支持视网膜模型。我们的结果还证实了早期文献中关于目标方向的视网膜更新。此外,回归分析显示目标深度和方向的更新增益都接近1,这表明误差出现在伸手动作中涉及的后续参考系转换的更新阶段之后。