Chen Guozhang, Gong Pulin
School of Physics, University of Sydney, NSW 2006, Australia.
ARC Center of Excellence for Integrative Brain Function, University of Sydney, NSW 2006, Australia.
Sci Adv. 2022 Apr 22;8(16):eabl4995. doi: 10.1126/sciadv.abl4995.
Recent evidence has demonstrated that during visual spatial attention sampling, neural activity and behavioral performance exhibit large fluctuations. To understand the origin of these fluctuations and their functional role, here, we introduce a mechanism based on the dynamical activity pattern (attention spotlight) emerging from neural circuit models in the transition regime between different dynamical states. This attention activity pattern with rich spatiotemporal dynamics flexibly samples from different stimulus locations, explaining many key aspects of temporal fluctuations such as variable theta oscillations of visual spatial attention. Moreover, the mechanism expands our understanding of how visual attention exploits spatially complex fluctuations characterized by superdiffusive motion in space and makes experimentally testable predictions. We further illustrate that attention sampling based on such spatiotemporal fluctuations provides profound functional advantages such as adaptive switching between exploitation and exploration activities and is particularly efficient at sampling natural scenes with multiple salient objects.
最近的证据表明,在视觉空间注意力采样过程中,神经活动和行为表现会出现大幅波动。为了理解这些波动的起源及其功能作用,在此,我们引入一种基于神经回路模型在不同动态状态之间的过渡阶段出现的动态活动模式(注意力聚光灯)的机制。这种具有丰富时空动态的注意力活动模式从不同的刺激位置灵活采样,解释了诸如视觉空间注意力的可变θ振荡等时间波动的许多关键方面。此外,该机制扩展了我们对视觉注意力如何利用以空间超扩散运动为特征的空间复杂波动的理解,并做出了可通过实验验证的预测。我们进一步说明,基于这种时空波动的注意力采样具有深远的功能优势,例如在利用和探索活动之间进行自适应切换,并且在对具有多个显著物体的自然场景进行采样时特别有效。