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在竞争和非竞争环境下测试婴儿视觉注意的神经过程模型的预测。

Testing predictions of a neural process model of visual attention in infancy across competitive and non-competitive contexts.

机构信息

The University of East Anglia, Norwich, UK.

University of Tennessee, Knoxville, USA.

出版信息

Infancy. 2022 Mar;27(2):389-411. doi: 10.1111/infa.12457. Epub 2022 Feb 17.

DOI:10.1111/infa.12457
PMID:35174955
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9305161/
Abstract

A key question in early development is how changes in neural systems give rise to changes in infants' behavior. We examine this question by testing predictions of a dynamic field (DF) model of infant spatial attention. We tested 5-, 7-, and 10-month-old infants in the Infant Orienting With Attention (IOWA) task containing the original non-competitive cue conditions (when a central stimulus disappeared before a cue onset) and new competitive cue conditions (when a central stimulus remained visible throughout the trial). This allowed testing of five model predictions: (1) that orienting accuracy would be higher and (2) reaction times would be slower for all competitive conditions; (3) that all infants would be slower to orient in the competitive conditions, though (4) older infants would show the strongest competition costs; and (5) that reaction times would be particularly slow for un-cued competitive conditions. Four of these five predictions were supported, and the remaining prediction was supported in part. We next examined fits of the model to the expanded task. New simulation results reveal close fits to the present findings after parameter modification. Critically, developmental parameters of the model were not altered, providing support for the DF model's account of neuro-developmental change.

摘要

早期发展中的一个关键问题是,神经系统的变化如何导致婴儿行为的变化。我们通过测试婴儿空间注意力动态场 (DF) 模型的预测来研究这个问题。我们在包含原始非竞争线索条件(当中央刺激在线索出现之前消失时)和新的竞争线索条件(当中央刺激在整个试验中保持可见时)的婴儿定向与注意力 (IOWA) 任务中测试了 5 个月、7 个月和 10 个月大的婴儿。这允许测试五个模型预测:(1) 定向准确性对于所有竞争条件都会更高,(2) 反应时间会更慢;(3) 所有婴儿在竞争条件下都会更慢定向,尽管 (4) 年龄较大的婴儿会表现出最强的竞争成本;以及 (5) 对于无提示竞争条件,反应时间会特别慢。这五个预测中有四个得到了支持,而其余的预测则部分得到了支持。我们接下来检查了模型对扩展任务的拟合情况。新的模拟结果表明,在修改参数后,该模型与当前发现非常吻合。至关重要的是,模型的发展参数没有改变,为 DF 模型对神经发育变化的解释提供了支持。

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