Distinct role of flexible and stable encodings in sequential working memory

Neural Netw. 2020 Jan:121:419-429. doi: 10.1016/j.neunet.2019.09.034. Epub 2019 Sep 28.

Abstract

The serial-position effect in working memory is considered important for studying how a sequence of sensory information can be retained and manipulated simultaneously in neural memory circuits. Here, via a precise analysis of the primacy and recency effects in human psychophysical experiments, we propose that stable and flexible codings take distinct roles of retaining and updating information in working memory, and that their combination induces serial-position effects spontaneously. We found that stable encoding retains memory to induce the primacy effect, while flexible encoding used for learning new inputs induces the recency effect. A model simulation based on human data, confirmed that a neural network with both flexible and stable synapses could reproduce the major characteristics of serial-position effects. Our new prediction, that the control of resource allocation by flexible-stable coding balance can modulate memory performance in sequence-specific manner, was supported by pre-cued memory performance data in humans.

Keywords: Flexible and stable encodings; Human psychophysics; Neural network simulation; Serial-position effect; Working memory.

MeSH terms

  • Brain / physiology
  • Humans
  • Memory, Short-Term*
  • Models, Neurological*
  • Neural Networks, Computer*