Eye tracking and computational approaches to understand the roles of maturation and experience in infant looking
眼动追踪和计算方法可用于了解成熟和经验在婴儿注视中的作用
基本信息
- 批准号:10602809
- 负责人:
- 金额:$ 7.16万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-08-01 至 2026-07-31
- 项目状态:未结题
- 来源:
- 关键词:AdultAgeAttentionBehaviorBehavioralBrainBrain regionCaliforniaCategoriesCerebrumChildCitiesClinicalClutteringsComplexComputer ModelsDevelopmentEnvironmentEventExposure toEyeEye MovementsFaceFamiliarityFutureGoalsHealth BenefitHomeHumanImageIndividualIndividual DifferencesInfantInfant DevelopmentInstructionInterventionKnowledgeLearningLifeLinkMentorshipMethodologyMethodsModelingNeural Network SimulationParentsPatternPersonsPopulationProcessPropertyProxyPublic HealthResearchRoleScanningShapesStimulusStreamSupervisionTechniquesTestingTrainingUniversitiesVariantVisionVisualVisual SystemVisual attentionVisual impairmentWorkattentional controlcareerconvolutional neural networkcortical visual impairmentexperienceexperimental studygazeinfancyinformation gatheringinnovationinsightmovement analysisprenatalsample fixationskillstheoriesvision developmentvisual processvisual processingvisual tracking
项目摘要
Project Summary/Abstract
Infants use their eyes to gather information from their environment and learn about the unique scenes and
objects that surround them. As infants accumulate these experiences, their cortex is concurrently maturing to
support more controlled attention and visual processes. However, it is unclear how much of the development of
gaze control reflects cortical maturation versus individual experiences. Therefore, the proposed project seeks
to evaluate three competing hypotheses regarding respective roles of maturation and experience. We will use
both traditional eye tracking analyses as well as advanced computational modeling. Specifically, in Aim 1, we
will record infant looking behaviors while viewing scenes and objects that range in familiarity and assess how
stimulus properties (e.g., salience, meaningfulness) relate to looking patterns for familiar and unfamiliar images
across the first year of life. In Aim 2, we will relate these looking behaviors to a convolutional neural network
inspired by the mature brain’s visual system. This innovative approach will evaluate the relationship between
infants’ looking behaviors and use of higher-level visual processing across contexts that vary in familiarity.
Ultimately, results from this proposal will inform developmental theories of visual attention by characterizing the
contributions of maturational versus experiential factors. The information gained from the results of this project
may facilitate future assessments and interventions of clinical populations with atypical visual scanning and
attention control. To successfully accomplish these aims, it is necessary that the applicant gains theoretical and
methodological expertise in both infant and adult attention research. This integrative perspective will allow her
to characterize infant attention and visual behaviors using sophisticated methodological and analytical
approaches, which will ultimately generate a wide range of subsequent research questions using similar
techniques. These aims will be most successfully completed under the supervision and mentorship of Drs. Lisa
Oakes and Steven Luck at the University of California, Davis, who are experts on attention in infant and adult
populations, respectively. The proposed training goals focus on expanding content knowledge of attention and
gaining methodological expertise in convolutional neural networks and representational similarity analysis.
Accomplishing these training goals will better prepare the applicant for a successful independent research
career that pushes the field of attention development forward.
项目总结/摘要
婴儿用眼睛从周围环境中收集信息,了解独特的场景,
它们周围的物体。当婴儿积累这些经验时,他们的大脑皮层也同时成熟,
支持更多的控制注意力和视觉过程。然而,目前还不清楚有多少发展,
注视控制反映了皮质成熟与个体经验的对比。因此,拟议项目寻求
评估三个相互竞争的假设,关于成熟和经验各自的作用。我们将使用
传统的眼动跟踪分析以及先进的计算建模。具体而言,在目标1中,我们
将在观看熟悉的场景和物体时记录婴儿的观看行为,并评估如何
刺激特性(例如,显著性,意义)与熟悉和不熟悉图像的寻找模式有关
在生命的第一年。在目标2中,我们将把这些行为与卷积神经网络联系起来。
受到成熟大脑视觉系统的启发。这一创新方法将评估
婴儿的观看行为和使用更高层次的视觉处理在不同的熟悉环境。
最终,这项提议的结果将通过描述视觉注意的特征,
成熟与经验因素的贡献。从该项目的结果中获得的信息
可能有助于未来对具有非典型视觉扫描的临床人群进行评估和干预,
注意力控制为了成功地实现这些目标,申请人必须获得理论知识和
婴儿和成人注意力研究的方法学专业知识。这种综合性的观点将使她
使用复杂的方法和分析来描述婴儿的注意力和视觉行为
方法,这将最终产生广泛的后续研究问题,使用类似的
技术.这些目标将在丽莎博士的监督和指导下最成功地完成
加州大学戴维斯分校的奥克斯和史蒂文·勒克是婴儿和成人注意力方面的专家
人口,分别。提出的培训目标侧重于扩大内容知识的关注,
获得卷积神经网络和代表性相似性分析的方法学专业知识。
完成这些培训目标将更好地准备申请人成功的独立研究
推动注意力领域发展的职业。
项目成果
期刊论文数量(0)
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