title: Effective visual working memory capacity: an emergent effect from the neural dynamics in an attractor network.
abstract: The study of working memory capacity is of outmost importance in cognitive psychology as working memory is at the basis of general cognitive function. Although the working memory capacity limit has been thoroughly studied, its origin still remains a matter of strong debate. Only recently has the role of visual saliency in modulating working memory storage capacity been assessed experimentally and proved to provide valuable insights into working memory function. In the computational arena, attractor networks have successfully accounted for psychophysical and neurophysiological data in numerous working memory tasks given their ability to produce a sustained elevated firing rate during a delay period. Here we investigate the mechanisms underlying working memory capacity by means of a biophysically-realistic attractor network with spiking neurons while accounting for two recent experimental observations: 1) the presence of a visually salient item reduces the number of items that can be held in working memory, and 2) visually salient items are commonly kept in memory at the cost of not keeping as many non-salient items. Our model suggests that working memory capacity is determined by two fundamental processes: encoding of visual items into working memory and maintenance of the encoded items upon their removal from the visual display. While maintenance critically depends on the constraints that lateral inhibition imposes to the mnemonic activity, encoding is limited by the ability of the stimulated neural assemblies to reach a sufficiently high level of excitation, a process governed by the dynamics of competition and cooperation among neuronal pools. Encoding is therefore contingent upon the visual working memory task and has led us to introduce the concept of effective working memory capacity (eWMC) in contrast to the maximal upper capacity limit only reached under ideal conditions.
authors.affiliation: Department of Information and Communication Technologies, Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain. laura.dempere@upf.edu
authors.forename: Laura
authors.initials: L
authors.lastname: Dempere-Marco
authors.forename: David P
authors.initials: DP
authors.lastname: Melcher
authors.forename: Gustavo
authors.initials: G
authors.lastname: Deco
mesh_terms: D000465:Algorithms; D001288:Attention / Q000502:physiology; D001703:Biophysics / Q000379:methods; D003071:Cognition; D003198:Computer Simulation; D006801:Humans; D008568:Memory / Q000502:physiology*; D008570:Memory, Short-Term / Q000502:physiology*; D008954:Models, Biological; D008959:Models, Neurological; D015233:Models, Statistical; D009042:Motivation; D009415:Nerve Net; D009482:Neurophysiology / Q000379:methods; D011584:Psychology; D014796:Visual Perception / Q000502:physiology