Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstrasse 1a, 04103, Leipzig, Germany,
Exp Brain Res. 2014 Feb;232(2):619-28. doi: 10.1007/s00221-013-3770-3. Epub 2013 Dec 10.
Many studies have demonstrated attenuated verbal working memory (WM) under articulatory suppression. However, performance is not completely abolished, suggesting a less efficient, non-articulatory mechanism for the maintenance of verbal information. The neural causes for the reduced efficiency of such a putative complementary maintenance system have not yet been addressed. The present study was conducted to fill this gap. Subjects performed a Sternberg task (a) under articulatory maintenance at low, high, and supracapacity set sizes and (b) under non-articulatory maintenance at low and high set sizes. With functional magnetic resonance imaging, set-size related increases in activity were compared between subvocal articulatory rehearsal and non-articulatory maintenance. First, the results replicate previous findings showing different networks underlying these two maintenance strategies. Second, activation of all key nodes of the articulatory maintenance network increased with the amount of memorized information, showing no plateau at high set sizes. In contrast, for non-articulatory maintenance, there was evidence for a plateau at high set sizes in all relevant areas of the network. Third, for articulatory maintenance, the non-articulatory maintenance network was additionally recruited at supracapacity set sizes, presumably to assist processing in this highly demanding condition. This is the first demonstration of differential neural bottlenecks for articulatory and non-articulatory maintenance. This study adds to our understanding of the performance differences between these two strategies supporting verbal WM.
许多研究已经证明，在发音抑制下，言语工作记忆（WM）会减弱。然而，表现并没有完全被抑制，这表明存在一种效率较低的非发音机制来维持言语信息。这种假设的补充维持系统效率降低的神经原因尚未得到解决。本研究旨在填补这一空白。研究对象在低、高和超容量设定大小下进行斯特恩伯格任务（a），并在低和高设定大小下进行非发音维持任务（b）。使用功能磁共振成像，比较了在次发声发音复述和非发音维持之间与设定大小相关的活动增加。首先，结果复制了先前的发现，表明这两种维持策略有不同的网络基础。其次，与记忆信息数量相关的所有发音维持网络关键节点的激活都随着信息量的增加而增加，在高设定大小下没有平台期。相比之下，对于非发音维持，在网络的所有相关区域都有证据表明在高设定大小下存在平台期。第三，对于发音维持，在超容量设定大小下，非发音维持网络也被招募，这可能是为了在这个要求极高的条件下协助处理。这是首次证明发音和非发音维持之间存在神经瓶颈的差异。本研究有助于我们理解这两种策略在支持言语 WM 方面的表现差异。
