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bioRxiv · 10.1101/319103

Error-correcting dynamics in visual working memory

Panichello, M. F.·DePasquale, B.·Pillow, J. W.·Buschman, T.
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Abstract

Working memory is critical to cognition, decoupling behavior from the immediate world. Yet, it is imperfect; internal noise introduces errors into memory representations (1, 2). Such errors accumulate over time (3-5) and increase with the number of items simultaneously held in working memory (6-10). Here, we show that error-correcting attractor dynamics mitigate the impact of noise on working memory. These dynamics pull memories towards a few stable representations in mnemonic space, inducing a bias in memory representations but reducing the effect of noise. Model-based and model-free analyses show attractor dynamics account for the frequency, bias, and precision of working memory reports in both humans and monkeys. Furthermore, attractor dynamics were optimized to the context; they adapted to the statistics of the environment, such that memories drifted towards contextually-predicted values. Our results suggest attractor dynamics mediate errors in working memory by counteracting noise and integrating contextual information into memories.

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Panichello, M. F., DePasquale, B., Pillow, J. W., Buschman, T.. 2018-05-10. Error-correcting dynamics in visual working memory. https://doi.org/10.1101/319103

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