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Contrasting single and multi-component working-memory systems in dual tasking.
Menno Nijboer1, Jelmer Borst1, Hedderik van Rijn2
1Dept. of Artificial Intelligence, University of Groningen, The Netherlands.
Cognitive Psychology
|February 10, 2016
Summary
Working memory interference in dual tasking arises from interactions between its components, not a single bottleneck. A distributed working memory model explains behavioral and neuroimaging data better than centralized models.
Area of Science:
- Cognitive Psychology
- Neuroscience
- Computational Modeling
Background:
- Working memory is crucial for dual tasking but its interference mechanisms are debated.
- Existing models propose either a single bottleneck or interactions between working memory components.
Purpose of the Study:
- To investigate the underlying mechanism of working memory interference during dual tasking.
- To compare centralized versus distributed models of working memory.
Main Methods:
- Collected behavioral and fMRI data during a multitasking paradigm with varied working memory loads.
- Developed and tested computational cognitive models representing centralized and distributed working memory.
Main Results:
- A distributed working memory model, comprising attentional focus, declarative memory, and rehearsal, significantly outperformed a centralized model.
- The distributed model accurately predicted both behavioral performance and neuroimaging findings.
Conclusions:
- Working memory interference in dual tasking is best explained by interactions among distinct cognitive resources.
- This supports a distributed, systems-level view of working memory rather than a single bottleneck.
