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首页> 外文期刊>Journal of vision >Toward a model of microsaccade generation: The case of microsaccadic inhibition
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Toward a model of microsaccade generation: The case of microsaccadic inhibition

机译:建立微扫视模型:抑制微扫视的情况

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摘要

Microsaccades are one component of the small eye movements that constitute fixation. Their implementation in the oculomotor system is unknown. To better understand the physiological and mechanistic processes underlying microsaccade generation, we studied microsaccadic inhibition, a transient drop of microsaccade rate, in response to irrelevant visual and auditory stimuli. Quantitative descriptions of the time course and strength of inhibition revealed a strong dependence of microsaccadic inhibition on stimulus characteristics. In Experiment 1, microsaccadic inhibition occurred sooner after auditory than after visual stimuli and after luminance-contrast than after color-contrast visual stimuli. Moreover, microsaccade amplitude strongly decreased during microsaccadic inhibition. In Experiment 2, the latency of microsaccadic inhibition increased with decreasing luminance contrast. We develop a conceptual model of microsaccade generation in which microsaccades result from fixation-related activity in a motor map coding for both fixation and saccades. In this map, fixation is represented at the central site. Saccades are generated by activity in the periphery, their amplitude increasing with eccentricity. The activity at the central, fixation-related site of the map predicts the rate of microsaccades as well as their amplitude and direction distributions. This model represents a framework for understanding the dynamics of microsaccade behavior in a broad range of tasks.
机译:微扫视是构成注视的小眼球运动的组成部分之一。它们在动眼系统中的实施方式尚不清楚。为了更好地了解微扫视产生的生理和机械过程,我们研究了微扫视抑制,这是对无关的视觉和听觉刺激做出反应的微扫视速率的短暂下降。对时间过程和抑制强度的定量描述表明,微囊抑制作用强烈依赖于刺激特征。在实验1中,听觉后微s抑制比视觉刺激后更早发生,并且亮度对比后比颜色对比后更早发生。此外,在微inhibition抑制期间,微扫视幅度大大降低。在实验2中,微acc抑制的潜伏期随着亮度对比度的降低而增加。我们开发了一个微扫视生成的概念模型,其中,微扫视是由固定和扫视的运动图编码中与固定相关的活动产生的。在此地图中,固定点位于中心站点。扫视运动是由外围活动产生的,其幅度随偏心率的增加而增加。地图中心与注视相关的位置上的活动可预测微扫视的速度及其幅度和方向分布。该模型代表了一个框架,用于了解各种任务中微扫视行为的动态。

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