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在跟踪不可预测运动目标的视觉过程中,扫视和平稳追踪眼动协调的神经动力学。

Neural dynamics of saccadic and smooth pursuit eye movement coordination during visual tracking of unpredictably moving targets.

机构信息

Center for Adaptive Systems, Department of Cognitive and Neural Systems, Boston University, 677 Beacon Street, Boston, MA 02215, USA.

出版信息

Neural Netw. 2012 Mar;27:1-20. doi: 10.1016/j.neunet.2011.10.011. Epub 2011 Oct 28.

Abstract

How does the brain coordinate saccadic and smooth pursuit eye movements to track objects that move in unpredictable directions and speeds? Saccadic eye movements rapidly foveate peripheral visual or auditory targets, and smooth pursuit eye movements keep the fovea pointed toward an attended moving target. Analyses of tracking data in monkeys and humans reveal systematic deviations from predictions of the simplest model of saccade-pursuit interactions, which would use no interactions other than common target selection and recruitment of shared motoneurons. Instead, saccadic and smooth pursuit movements cooperate to cancel errors of gaze position and velocity, and thus to maximize target visibility through time. How are these two systems coordinated to promote visual localization and identification of moving targets? How are saccades calibrated to correctly foveate a target despite its continued motion during the saccade? The neural model proposed here answers these questions. Modeled interactions encompass motion processing areas MT, MST, FPA, DLPN and NRTP; saccade planning and execution areas FEF, LIP, and SC; the saccadic generator in the brain stem; and the cerebellum. Simulations illustrate the model's ability to functionally explain and quantitatively simulate anatomical, neurophysiological and behavioral data about coordinated saccade-pursuit tracking.

摘要

大脑如何协调扫视和平滑追踪眼球运动,以跟踪以不可预测的方向和速度移动的物体?扫视眼球运动快速注视外周视觉或听觉目标,而平滑追踪眼球运动则使中央凹指向注视的移动目标。对猴子和人类的跟踪数据的分析揭示了最简单的扫视-追踪相互作用模型的预测存在系统性偏差,该模型除了共同的目标选择和共享运动神经元的招募之外,不会使用其他相互作用。相反,扫视和平滑追踪运动合作以消除注视位置和速度的误差,从而通过时间最大化目标可见度。这两个系统如何协调以促进视觉定位和识别移动目标?如何在扫视过程中即使目标继续运动,也能准确地注视目标?这里提出的神经模型回答了这些问题。建模的相互作用包括运动处理区域 MT、MST、FPA、DLPN 和 NRTP;扫视计划和执行区域 FEF、LIP 和 SC;脑干中的扫视发生器;以及小脑。模拟说明了该模型能够从功能上解释和定量模拟关于协调扫视-追踪跟踪的解剖学、神经生理学和行为数据的能力。

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