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Eye movement patterns during scene viewing predict individual differences

机译:观看场景期间的眼睛运动模式可预测个体差异

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An important and understudied area in scene perception is the degree to which individual differences influence scene-viewing behavior. The present study investigated this issue by predicting individual differences from regularities in sequential eye movement patterns. Seventy-nine participants completed a free-view memorization task for 40 real-world scenes while their eye movements were recorded. Individual difference measures were collected across subsets of participants including cognitive ability measures (e.g., working memory capacity) and cognitive disorder measures (e.g., autism spectrum disorder: ASD). An area of interest grid composed of 5 radiating rectangular areas from the scene center to the periphery was used to represent observers' tendencies to shift their attention between more central or peripheral scene information. Successor Representation Scanpath Analysis (SRSA, Hayes, Petrov, & Sederberg, 2011) was used to capture statistical regularities in each participant's eye movements across this predefined area of interest grid. A principal component analysis of participant successor representations was performed for each individual difference measure, and these components were then used to predict individual differences scores. SRSA was able to predict several individual difference measures well. Leave-one-out cross validation demonstrated significant prediction across the following measures: working memory capacity (r2=0.45), fluid intelligence (r2=0.43), SAT (r2=0.45), and ASD (r2=0.26). Moreover, the component regression weights were readily interpretable in terms of broad scanning strategies. For instance, higher cognitive ability was associated with the tendency to focus attention more centrally within a scene, and move more systematically among these central areas. Participants with higher ASD scores showed a different pattern, with a greater tendency to focus attention more peripherally within a scene, and move less systematically between the center and periphery of the scene. These results suggest that underlying individual differences in observers significantly influence gaze behavior during real-world scene perception.
机译:场景感知中一个重要且尚未充分研究的领域是个体差异影响场景观看行为的程度。本研究通过预测顺序眼动模式中规律性的个体差异来研究此问题。 79位参与者完成了40个真实场景的自由视图记忆任务,同时记录了他们的眼球运动。跨参与者的子集收集个体差异度量,包括认知能力度量(例如,工作记忆能力)和认知障碍度量(例如,自闭症谱系障碍:ASD)。感兴趣区域网格由从场景中心到外围的5个辐射矩形区域组成,用于表示观察者在更多中心或外围场景信息之间转移注意力的趋势。继任者表示扫描路径分析(SRSA,Hayes,Petrov和Sederberg,2011年)用于捕获每个参与者在此预定义兴趣区域内眼睛运动的统计规律。对每个个体差异度量执行参与者后继代表的主成分分析,然后将这些成分用于预测个体差异得分。 SRSA能够很好地预测几个个体差异度量。留一法交叉验证证明了以下指标的重要预测:工作记忆容量(r2 = 0.45),流体智力(r2 = 0.43),SAT(r2 = 0.45)和ASD(r2 = 0.26)。此外,根据广泛的扫描策略,可以容易地解释分量回归权重。例如,更高的认知能力与将注意力集中在场景中更集中,并在这些中心区域中更系统地移动的趋势相关。具有较高ASD得分的参与者表现出不同的模式,更倾向于将注意力集中在场景的外围,而在场景的中心和外围之间的移动则不太系统。这些结果表明,观察者中潜在的个体差异在真实世界的场景感知过程中会极大地影响凝视行为。

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