Dynamic hidden states underlying working-memory-guided behavior.
Dynamic hidden states underlying working-memory-guided behavior.
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DOI：
10.1038/nn.4546
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发表时间：
2017-06
影响因子：
25
通讯作者：
Stokes MG
中科院分区：
文献类型：
--
作者：
Wolff MJ;Jochim J;Akyürek EG;Stokes MG
最近的理论模型提出，工作记忆是由“活动沉默”神经状态（例如短期突触可塑性）的快速转变介导的。根据动态编码框架，这种隐藏状态转换灵活地配置记忆网络以实现记忆引导行为，并同样快速地溶解它们以允许遗忘。我们开发了一种新颖的扰动方法来测量脑电图（EEG）中的助记隐藏状态。通过在维护过程中“探测大脑”，我们表明，即使在没有注意力和挥之不去的延迟活动的情况下，记忆项目的特定信息也可以从脉冲响应中解码出来。此外，隐藏记忆非常灵活：引导人们忘记一件物品的指令提示足以从隐藏状态中擦除相应的痕迹。相比之下，暂时无人看管的项目在隐藏状态下保持稳健编码，从而将注意力焦点与线索导向的遗忘分开。最后，隐藏状态编码的强度可以预测工作记忆引导行为的准确性，包括记忆精度。
Recent theoretical models propose that working memory is mediated by rapid transitions in ‘activity-silent’ neural states (e.g., short-term synaptic plasticity). According to the dynamic coding framework, such hidden state transitions flexibly configure memory networks for memory-guided behaviour, and dissolve them equally fast to allow forgetting. We developed a novel perturbation approach to measure mnemonic hidden states in electroencephalogram (EEG). By ‘pinging the brain’ during maintenance, we show that memory item-specific information is decodable from the impulse response, even in the absence of attention and lingering delay activity. Moreover, hidden memories are remarkably flexible: An instruction cue that directs people to forget one item is sufficient to wipe the corresponding trace from the hidden state. In contrast, temporarily unattended items remain robustly coded in the hidden state, decoupling attentional focus from cue-directed forgetting. Finally, the strength of hidden-state coding predicts the accuracy of working memory guided behaviour, including memory precision.