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Surprise response as a probe for compressed memory states

Author

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  • Hadar Levi-Aharoni
  • Oren Shriki
  • Naftali Tishby

Abstract

The limited capacity of recent memory inevitably leads to partial memory of past stimuli. There is also evidence that behavioral and neural responses to novel or rare stimuli are dependent on one’s memory of past stimuli. Thus, these responses may serve as a probe of different individuals’ remembering and forgetting characteristics. Here, we utilize two lossy compression models of stimulus sequences that inherently involve forgetting, which in addition to being a necessity under many conditions, also has theoretical and behavioral advantages. One model is based on a simple stimulus counter and the other on the Information Bottleneck (IB) framework which suggests a more general, theoretically justifiable principle for biological and cognitive phenomena. These models are applied to analyze a novelty-detection event-related potential commonly known as the P300. The trial-by-trial variations of the P300 response, recorded in an auditory oddball paradigm, were subjected to each model to extract two stimulus-compression parameters for each subject: memory length and representation accuracy. These parameters were then utilized to estimate the subjects’ recent memory capacity limit under the task conditions. The results, along with recently published findings on single neurons and the IB model, underscore how a lossy compression framework can be utilized to account for trial-by-trial variability of neural responses at different spatial scales and in different individuals, while at the same time providing estimates of individual memory characteristics at different levels of representation using a theoretically-based parsimonious model.Author summary: Surprise responses reflect expectations based on preceding stimuli representations, and hence can be used to infer the characteristics of memory utilized for a task. We suggest a quantitative method for extracting an individual estimate of effective memory capacity dedicated for a task based on the correspondence between a theoretical surprise model and electrophysiological single-trial surprise responses. We demonstrate this method on EEG responses recorded while participants were performing a simple auditory task; we show the correspondence between the theoretical and physiological surprise, and calculate an estimate of the utilized memory. The generality of this framework allows it to be applied to different EEG features that reflect different modes and levels of the processing hierarchy, as well as other physiological measures of surprise responses. Future studies may use this framework to construct a handy diagnostic tool for a quantitative, individualized characterization of memory-related disorders.

Suggested Citation

  • Hadar Levi-Aharoni & Oren Shriki & Naftali Tishby, 2020. "Surprise response as a probe for compressed memory states," PLOS Computational Biology, Public Library of Science, vol. 16(2), pages 1-21, February.
  • Handle: RePEc:plo:pcbi00:1007065
    DOI: 10.1371/journal.pcbi.1007065
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    References listed on IDEAS

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    1. Jonathan Rubin & Nachum Ulanovsky & Israel Nelken & Naftali Tishby, 2016. "The Representation of Prediction Error in Auditory Cortex," PLOS Computational Biology, Public Library of Science, vol. 12(8), pages 1-28, August.
    2. Rik van Dinteren & Martijn Arns & Marijtje L A Jongsma & Roy P C Kessels, 2014. "P300 Development across the Lifespan: A Systematic Review and Meta-Analysis," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-13, February.
    3. Gagan Narula & Joshua A. Herbst & Joerg Rychen & Richard H. R. Hahnloser, 2018. "Learning auditory discriminations from observation is efficient but less robust than learning from experience," Nature Communications, Nature, vol. 9(1), pages 1-11, December.
    4. Sid Kouider & Bria Long & Lorna Le Stanc & Sylvain Charron & Anne-Caroline Fievet & Leonardo S. Barbosa & Sofie V. Gelskov, 2015. "Neural dynamics of prediction and surprise in infants," Nature Communications, Nature, vol. 6(1), pages 1-8, December.
    5. Niels Chr Hansen & Peter Vuust & Marcus Pearce, 2016. ""If You Have to Ask, You'll Never Know": Effects of Specialised Stylistic Expertise on Predictive Processing of Music," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-20, October.
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