Laboratory for Computational Neurodynamics and Cognition, School of Psychology, University of Ottawa, Ottawa, Ontario, Canada.
PLoS One. 2021 Jan 5;16(1):e0244822. doi: 10.1371/journal.pone.0244822. eCollection 2021.
Sensory stimuli endow animals with the ability to generate an internal representation. This representation can be maintained for a certain duration in the absence of previously elicited inputs. The reliance on an internal representation rather than purely on the basis of external stimuli is a hallmark feature of higher-order functions such as working memory. Patterns of neural activity produced in response to sensory inputs can continue long after the disappearance of previous inputs. Experimental and theoretical studies have largely invested in understanding how animals faithfully maintain sensory representations during ongoing reverberations of neural activity. However, these studies have focused on preassigned protocols of stimulus presentation, leaving out by default the possibility of exploring how the content of working memory interacts with ongoing input streams. Here, we study working memory using a network of spiking neurons with dynamic synapses subject to short-term and long-term synaptic plasticity. The formal model is embodied in a physical robot as a companion approach under which neuronal activity is directly linked to motor output. The artificial agent is used as a methodological tool for studying the formation of working memory capacity. To this end, we devise a keyboard listening framework to delineate the context under which working memory content is (1) refined, (2) overwritten or (3) resisted by ongoing new input streams. Ultimately, this study takes a neurorobotic perspective to resurface the long-standing implication of working memory in flexible cognition.
感觉刺激赋予动物产生内部表象的能力。这种表象可以在没有先前引出输入的情况下持续一定的时间。依赖于内部表象而不是纯粹基于外部刺激,是工作记忆等高级功能的标志性特征。对感觉输入产生的神经活动模式可以在先前输入消失后很长一段时间内继续。实验和理论研究在很大程度上投入到理解动物如何在神经活动的持续回响中忠实地维持感觉表象。然而,这些研究集中在预先指定的刺激呈现协议上,默认情况下排除了探索工作记忆的内容如何与正在进行的输入流相互作用的可能性。在这里,我们使用具有动态突触的尖峰神经元网络研究工作记忆,这些突触受到短期和长期突触可塑性的影响。形式模型体现在一个物理机器人中,作为一种伴随方法,其中神经元活动直接与运动输出相关联。人工代理被用作研究工作记忆容量形成的方法工具。为此,我们设计了一个键盘监听框架,以描绘工作记忆内容(1)细化、(2)覆盖或(3)被正在进行的新输入流抵抗的上下文。最终,这项研究从神经机器人的角度重新审视了工作记忆在灵活认知中的长期影响。