Topic: sensory constraints

Working memory (WM) allows us to hold information temporarily and make complex decisions beyond reflexive response to stimuli. One prominent feature of WM is its capacity limit. Despite decades of study, the root of this limit is still not well-understood. Most previous accounts for this limit assume various forms of memory constraints and make strong, often oversimplified, assumptions about sensory representations of stimuli. In this work, we built visual-cognitive neural network models of WM that process raw sensory stimuli. In contrast to intuitions that capacity limit results from memory c