ABSTRACT

Visual search and working memory (WM) are tightly linked cognitive processes. Theories of attentional selection assume that WM plays an important role in top-down guided visual search. However, computational models of visual search do not model WM. Here we show that an existing model of WM can utilize its mechanisms of rapid plasticity and pattern completion to perform visual search. In this model, a search template, like a memory item, is encoded into the network’s synaptic weights forming a momentary stable attractor. During search, recurrent activation between the template and visual inputs amplifies the target and suppresses non-matching features via mutual inhibition. While the model cannot outperform models designed specifically for search, it can, “off-the-shelf”, account for important characteristics. Notably, it produces search display set-size costs, repetition effects, and multiple-template search effects, qualitatively in line with empirical data. It is also informative that the model fails to produce some important aspects of visual search behaviour, such as suppression of repeated distractors. Also, without additional control structures for top-down guidance, the model lacks the ability to differentiate between encoding and searching for targets. The shared architecture bridges theories of visual search and visual WM, highlighting their common structure and their differences.

摘要

视觉搜索和工作记忆（WM）是紧密联系的认知过程。注意选择理论假设WM在自顶向下的引导式视觉搜索中起着重要的作用。但是，视觉搜索的计算模型不对WM建模。在这里，我们显示了WM的现有模型可以利用其快速可塑性和图案完成的机制执行视觉搜索。在此模型中，将搜索模板（如存储项）编码到网络的突触权重中，形成瞬时稳定的吸引子。在搜索过程中，模板和视觉输入之间的反复激活会放大目标，并通过相互抑制来抑制不匹配的特征。尽管该模型不能胜过专门为搜索设计的模型，但它可以“现成”说明重要特征。值得注意的是 它会根据经验数据定性地生成搜索显示集大小的成本，重复效果和多模板搜索效果。有益的是，该模型未能产生视觉搜索行为的一些重要方面，例如抑制重复的干扰物。同样，由于没有用于自上而下指导的附加控制结构，该模型也缺乏区分编码和搜索目标的能力。共享的体系结构将视觉搜索和视觉WM的理论联系起来，突出了它们的共同结构和差异。由于没有用于自上而下指导的附加控制结构，该模型缺乏区分编码和搜索目标的能力。共享的体系结构将视觉搜索和视觉WM的理论联系起来，突出了它们的共同结构和差异。由于没有用于自上而下指导的附加控制结构，该模型缺乏区分编码和搜索目标的能力。共享架构将视觉搜索和视觉WM的理论联系起来，突出了它们的共同结构和差异。