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Resources masquerading as slots: Flexible allocation of visual working memory.

Chris Donkin1, Arthur Kary1, Fatima Tahir1

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Visual working memory capacity is a flexible resource, not strictly item-based or resource-based. A new model shows memory resources are divided among items, impacting fidelity and recall accuracy.

Keywords:
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Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Computational Modeling

Background:

  • The debate on visual working memory (VWM) capacity centers on item-based versus resource-based models.
  • Current models struggle to explain the flexible deployment of mnemonic resources.

Purpose of the Study:

  • To propose and test a novel computational model of VWM capacity.
  • To investigate whether VWM is a flexible resource that can be deployed in a slot-like manner.

Main Methods:

  • Development of a computational model allowing for encoding of all items or a subset.
  • Simulation of a fixed-capacity mnemonic resource divided among memory items.
  • Testing model predictions regarding predictable memory demands.

Main Results:

  • The model demonstrates that encoding fewer items increases individual item fidelity.
  • A trade-off exists: higher fidelity for fewer items necessitates an explicit guessing process for unencoded items.
  • Participants were predicted to encode entire sets more often under predictable memory load.

Conclusions:

  • VWM capacity is best understood as a flexible resource, adaptable to task demands.
  • The proposed model offers a unified account for both item-based and resource-based VWM phenomena.
  • Predictability of memory demands influences encoding strategies, supporting a flexible resource view.