Unraveling the sub-processes of selective attention: insights from dynamic modeling and continuous behavior
Unraveling the sub-processes of selective attention: insights from dynamic modeling and continuous behavior
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DOI：
10.1007/s10339-015-0666-0
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发表时间：
2015-11-01
影响因子：
1.7
通讯作者：
Scherbaum, Stefan
中科院分区：
文献类型：
--
作者：
Frisch, Simon;Dshemuchadse, Maja;Scherbaum, Stefan
选择性注意使信息处理偏向于与实现我们的目标相关的刺激。然而，这种偏见的本质存在争议：它是否仅仅依赖于目标相关信息的放大，或者是否需要额外的抑制过程来选择性地抑制当前分散注意力的信息？在这里，我们通过动态的、基于建模的方法探索了选择性注意背后的过程，该方法专注于行为随时间的持续演变。我们提出了两个包含不同理论假设的动态神经场模型。对这两个模型的模拟表明，它们在响应时间方面做出了类似的预测，但在连续行为方面却存在显着差异。通过鼠标跟踪观察到的人类数据作为连续的性能衡量标准，揭示了该模型仅基于放大的证据，但没有迹象表明持续存在选择性干扰物抑制。
Selective attention biases information processing toward stimuli that are relevant for achieving our goals. However, the nature of this bias is under debate: Does it solely rely on the amplification of goal-relevant information or is there a need for additional inhibitory processes that selectively suppress currently distracting information? Here, we explored the processes underlying selective attention with a dynamic, modeling-based approach that focuses on the continuous evolution of behavior over time. We present two dynamic neural field models incorporating the diverging theoretical assumptions. Simulations with both models showed that they make similar predictions with regard to response times but differ markedly with regard to their continuous behavior. Human data observed via mouse tracking as a continuous measure of performance revealed evidence for the model solely based on amplification but no indication of persisting selective distracter inhibition.