Institute of Medical Psychology, Goethe University, Heinrich-Hoffmann-Strasse 10, D-60528 Frankfurt am Main, Germany.
Behav Brain Res. 2010 Dec 25;214(2):172-9. doi: 10.1016/j.bbr.2010.05.041. Epub 2010 Jun 1.
Working memory (WM) constitutes a fundamental aspect of human cognition. It refers to the ability to keep information active for further use, while allowing it to be prioritized, modified and protected from interference. Much research has addressed the storage function of WM, however, its 'working' aspect still remains underspecified. Many operations that work on the contents of WM do not appear specific to WM. The present review focuses on those operations that we consider "basic" because they operate in the service of memory itself, by providing its basic functionality of retaining information active, in a stable yet flexible way. Based on current process models of WM we review five strands of research: (1) mnemonic selection of one item amongst others, (2) updating the focus of attention with the selected item, (3) updating the content of visual WM with new item(s), (4) rehearsal of visuospatial information and (5) coping with interference. We discuss the neuronal substrates underlying those operations obtained with functional magnetic resonance imaging and relate them to findings on "executive functions". The presented data support the view that WM emerges from interactions between higher sensory, attentional and mnemonic functions, with separable neural bases. However, interference processing and the representation of rule switching in WM may demand an extension of the current WM models by executive control functions.
工作记忆(WM)是人类认知的基本方面。它指的是保持信息活跃以供进一步使用的能力,同时允许对其进行优先级排序、修改和免受干扰。大量研究已经解决了 WM 的存储功能,但它的“工作”方面仍然没有得到明确说明。许多在 WM 内容上运作的操作似乎并不是特定于 WM 的。本综述重点关注那些我们认为是“基本”的操作,因为它们以记忆本身的服务为运作,通过以稳定而灵活的方式提供保留信息活跃的基本功能。基于当前的 WM 过程模型,我们回顾了五项研究:(1)在其他项目中选择一个项目的记忆选择,(2)用所选项目更新注意力焦点,(3)用新项目更新视觉 WM 的内容,(4)对视空间信息进行复述,以及(5)应对干扰。我们讨论了通过功能磁共振成像获得的这些操作的神经基础,并将其与关于“执行功能”的发现联系起来。所呈现的数据支持这样一种观点,即 WM 是从高级感觉、注意力和记忆功能之间的相互作用中产生的,具有可分离的神经基础。然而,干扰处理和 WM 中规则转换的表示可能需要通过执行控制功能扩展当前的 WM 模型。