Department of Applied Mathematics, University of Washington, Seattle, WA, 98195, USA.
Departments of Neurobiology and Statistics, University of Chicago, Chicago, IL, 60637, USA.
Commun Biol. 2023 Aug 10;6(1):829. doi: 10.1038/s42003-023-05200-7.
Oscillatory activity is commonly observed during the maintenance of information in short-term memory, but its role remains unclear. Non-oscillatory models of short-term memory storage are able to encode stimulus identity through their spatial patterns of activity, but are typically limited to either an all-or-none representation of stimulus amplitude or exhibit a biologically implausible exact-tuning condition. Here we demonstrate a simple mechanism by which oscillatory input enables a circuit to generate persistent or sequential activity that encodes information not only in the spatial pattern of activity, but also in the amplitude of activity. This is accomplished through a phase-locking phenomenon that permits many different amplitudes of persistent activity to be stored without requiring exact tuning of model parameters. Altogether, this work proposes a class of models for the storage of information in working memory, a potential role for brain oscillations, and a dynamical mechanism for maintaining multi-stable neural representations.
在短期记忆中维持信息时,通常会观察到振荡活动,但它的作用仍不清楚。非振荡的短期记忆存储模型能够通过其活动的空间模式来编码刺激身份,但通常仅限于刺激幅度的全有或全无表示,或者表现出生物上不合理的精确调谐条件。在这里,我们展示了一种简单的机制,通过这种机制,振荡输入可以使电路产生持久或连续的活动,不仅可以在活动的空间模式中编码信息,还可以在活动的幅度中编码信息。这是通过一种相位锁定现象来实现的,该现象允许存储许多不同幅度的持久活动,而不需要精确调整模型参数。总的来说,这项工作为工作记忆中的信息存储提出了一类模型、脑振荡的潜在作用以及维持多稳定神经表示的动力学机制。