Visual Working Memory Capacity: From Psychophysics and Neurobiology to Individual Differences

By Steven J. Luck, Edward K. Vogel. Trends in Cognitive Sciences, 2013

994 citations recorded by the source corpus.

Visual working memory capacity is of great interest because it is strongly correlated with overall cognitive ability, can be understood at the level of neural circuits, and is easily measured. Recent studies have shown that capacity influences tasks ranging from saccade targeting to analogical reasoning. A debate has arisen over whether capacity is constrained by a limited number of discrete representations or by an infinitely divisible resource, but the empirical evidence and neural network models currently favor a discrete item limit. Capacity differs markedly across individuals and groups, and recent research indicates that some of these differences reflect true differences in storage capacity whereas others reflect variations in the ability to use memory capacity efficiently.

Subfields: Artificial Intelligence, Cognitive Neuroscience, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/e0a0657991b8305bc41a15bfc76e7e94a47b4b21

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Citations in the corpus

Visual working memory representation as a topological defined perceptual object. (2019, positive): “Downloaded from jov.arvojournals.org on 11/21/2021 (Luck & Vogel, 1997, 2013; Zhang & Luck, 2008).”
THE COGNITIVE NEUROSCIENCE OF WORKING MEMORY (2007, background): “For excellent reviews on these issues see Ma et al. 2014 and Luck & Vogel 2013.”
An Interference Model of Visual Working Memory (2017, background): “This limit has been argued to account for a discrete, slot-like capacity limit (Luck & Vogel, 2013).”
The Distributed Nature of Working Memory. (2017, background): “Behavioral models assume either a slot-based [180,181] or resource-based [182,183] limitation of capacity.”
Prefrontal Cortex Networks Shift from External to Internal Modes during Learning (2016, background): “…theme in cognitive neuroscience is competition for limited neural processing resources— objects are thought to compete for representation in the visual cortex (Desimone and Duncan, 1995), and working memory has a limited capacity to hold only a few items simultaneously (Luck and Vogel, 2013).”
Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents (2018, background): “Interestingly, in humans, individual differences in change detection tests of visual working memory are highly correlated with fluid intelligence (Fukuda et al., 2010; Luck and Vogel, 2013).”
Sensory stimulation enhances visual working memory capacity (2024, unknown): “Visual working memory (vWM) underlies our ability to maintain visual information in an active state 1,2 , which is fundamental for sampling the environment 3,4 , object search 5,6 , and various higher cognitive functions, including decision-making 7 – 9 , goal-directed behavior 10,11 , and…”
Alpha oscillatory activity is causally linked to working memory retention (2023, background): “Because of its essential role in human cognition, investigating the neural mechanisms underlying WM has been a focus of neuroscience research for decades [2,3].”
Intermittent theta burst stimulation over the parietal cortex has a significant neural effect on working memory (2021, unknown): “…studies found that, contralateral delay activity (CDA), a component that originates from the parietal cortex (Becke, Müller, Vellage, Schoenfeld, & Hopf, 2015; Brigadoi et al., 2017; Robitaille, Grimault, & Jolicœur, 2009), also showed such patterns (Luck & Vogel, 2013; Vogel & Machizawa, 2004).”
Shared resources between visual attention and visual working memory are allocated through rhythmic sampling (2019, background): “This led on the one hand to the formulation of the concept of Visual Working Memory (VWM) as the active maintenance of visual information to serve the needs of an ongoing task (Luck and Vogel, 2013).”