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A neural model of schemas and memory encoding

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Abstract

The ability to rapidly assimilate new information is essential for survival in a dynamic environment. This requires experiences to be encoded alongside the contextual schemas in which they occur. Tse et al. (Science 316(5821):76–82, 2007) showed that new information matching a preexisting schema is learned rapidly. To better understand the neurobiological mechanisms for creating and maintaining schemas, we constructed a biologically plausible neural network to learn context in a spatial memory task. Our model suggests that this occurs through two processing streams of indexing and representation, in which the medial prefrontal cortex and hippocampus work together to index cortical activity. Additionally, our study shows how neuromodulation contributes to rapid encoding within consistent schemas. The level of abstraction of our model further provides a basis for creating context-dependent memories while preventing catastrophic forgetting in artificial neural networks.

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Acknowledgements

We thank the participants of the 2017 Telluride Neuromorphic Cognition Workshop, especially Xinyun Zou, Brent Komer, Georgios Detorakis, and Scott Koziol, who worked on a preliminary project leading to the creation of this model.

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Authors and Affiliations

  1. Department of Cognitive Sciences, University of California, Irvine, Irvine, CA, USA

    Tiffany Hwu & Jeffrey L. Krichmar

  2. HRL Laboratories, LLC, Malibu, CA, USA

    Tiffany Hwu

  3. Department of Computer Science, University of California, Irvine, Irvine, CA, USA

    Jeffrey L. Krichmar

Authors
  1. Tiffany Hwu
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  2. Jeffrey L. Krichmar
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Correspondence to Tiffany Hwu.

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This article is part of the Special Issue entitled ‘Complex Spatial Navigation in Animals, Computational Models and Neuro-inspired Robots’.

This material is based upon work supported by the United States Air Force and DARPA under contract no. FA8750-18-C-0103, and other support in part by Toyota Motor North America and HRL Laboratories, LLC. Any opinions, findings and conclusions or recommendations ex-pressed in this material are those of the author(s) and do not necessarily reflect the views of the United States Air Force and DARPA.

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Hwu, T., Krichmar, J.L. A neural model of schemas and memory encoding. Biol Cybern 114, 169–186 (2020). https://doi.org/10.1007/s00422-019-00808-7

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