As within, so without, as above, so below: Common mechanisms can support between- and within-trial category learning dynamics.
As within, so without, as above, so below: Common mechanisms can support between- and within-trial category learning dynamics.
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DOI：
10.1037/rev0000381
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发表时间：
2022-10
影响因子：
5.4
通讯作者：
Turner, Brandon
中科院分区：
文献类型：
--
作者：
Weichart, Emily Ruth;Galdo, Matthew;Sloutsky, Vladimir;Turner, Brandon
学习新类别时的两个基本困难是决定1）哪些信息是相关的，以及2）何时使用这些信息。为了克服这些困难，人们不断地选择要有选择地关注哪些信息维度，并监控它们与当前目标的相关性。虽然先前的理论已经详细说明了观察者如何随着时间的推移学习关注相关维度，但这些理论在很大程度上对如何在试验内分配注意力，应该采样哪些维度的信息以及信息采样的时间顺序如何影响学习保持沉默。在这里，我们使用自适应注意力表征模型（AARM）来证明一组常见的机制可以用来指定：1）在学习过程中，注意力的分布如何在试验之间更新;以及2）注意力如何在试验内的维度之间动态转移。我们通过比较AARM的预测和四个案例研究中观察到的行为来验证我们提出的一套机制，这些案例研究共同涵盖了选择性注意的不同理论方面。我们使用眼动追踪和选择反应数据，以提供一个严格的测试，注意力和决策过程如何动态地相互作用，在类别学习。具体来说，对所选刺激维度的注意力是如何引起决策动力学的，反过来，决策动力学又是如何影响我们通过凝视注视来不断选择关注哪些维度的？
Two fundamental difficulties when learning novel categories are deciding 1) what information is relevant, and 2) when to use that information. To overcome these difficulties, humans continuously make choices about which dimensions of information to selectively attend to, and monitor their relevance to the current goal. Although previous theories have specified how observers learn to attend to relevant dimensions over time, those theories have largely remained silent about how attention should be allocated on a within-trial basis, which dimensions of information should be sampled, and how the temporal ordering of information sampling influences learning. Here, we use the Adaptive Attention Representation Model (AARM) to demonstrate that a common set of mechanisms can be used to specify: 1) how the distribution of attention is updated between trials over the course of learning; and 2) how attention dynamically shifts among dimensions within-trial. We validate our proposed set of mechanisms by comparing AARM’s predictions to observed behavior across four case studies, which collectively encompass different theoretical aspects of selective attention. We use both eye-tracking and choice response data to provide a stringent test of how attention and decision processes dynamically interact during category learning. Specifically, how does attention to selected stimulus dimensions gives rise to decision dynamics, and in turn, how do decision dynamics influence our continuous choices about which dimensions to attend to via gaze fixations?
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DOI：
10.1037/a0016272
发表时间：
2009-09-01
影响因子：
2.6
作者：
Blair, Mark R.;Watson, Marcus R.;Maj, Fillip
通讯作者：
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DOI：
10.1073/pnas.1104047108
发表时间：
2011-06-21
影响因子：
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发表时间：
2020-08-01
影响因子：
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