Picower Institute for Learning & Memory and Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 and.
Computational Brain Science Laboratory, Department Computational Science & Technology, KTH Royal Institute of Technology, Stockholm, Sweden 11428.
J Neurosci. 2018 Aug 8;38(32):7013-7019. doi: 10.1523/JNEUROSCI.2485-17.2018.
Persistent spiking has been thought to underlie working memory (WM). However, virtually all of the evidence for this comes from studies that averaged spiking across time and across trials, which masks the details. On single trials, activity often occurs in sparse transient bursts. This has important computational and functional advantages. In addition, examination of more complex tasks reveals neural coding in WM is dynamic over the course of a trial. All this suggests that spiking is important for WM, but that its role is more complex than simply persistent spiking.Persistent Spiking Activity Underlies Working Memory, by Christos Constantinidis, Shintaro Funahashi, Daeyeol Lee, John D. Murray, Xue-Lian Qi, Min Wang, and Amy F.T. Arnsten.
持续的尖峰活动被认为是工作记忆 (WM) 的基础。然而，几乎所有支持这一观点的证据都来自于在时间和试验上对尖峰进行平均的研究，这些研究掩盖了细节。在单个试验中，活动通常以稀疏的短暂爆发形式出现。这具有重要的计算和功能优势。此外，对更复杂任务的研究表明，在试验过程中，WM 的神经编码是动态的。所有这些都表明，尖峰活动对于 WM 很重要，但它的作用比简单的持续尖峰活动更为复杂。《持续尖峰活动是工作记忆的基础》，作者 Christos Constantinidis、Shintaro Funahashi、Daeyeol Lee、John D. Murray、Xue-Lian Qi、Min Wang 和 Amy F.T. Arnsten。
