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Pupil-Linked Arousal is Sensitive to Model Reset but not Model Update


Dayan,  P       
Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Basgol, H., Dayan, P., & Franz, V. (2022). Pupil-Linked Arousal is Sensitive to Model Reset but not Model Update. Poster presented at 63rd Annual Meeting of the Psychonomic Society (PS 2022), Boston, MA, USA.

Cite as: https://hdl.handle.net/21.11116/0000-000B-369D-8
Humans use internal models to make predictions. When the environment changes and predictions are suddenly violated, there
is model reset, excess arousal, and learning of a new model. This appears to be accompanied by locus coeruleus activity/norepinephrine release (LC-NE) and pupil dilation responses (PDRs). Following Zhao et al. (Nature Communications, 2019), we explored this phenomenon using switches between regular and random patterns of tones. A regular pattern admits a simple model which, when violated by a switch to a random pattern, putatively induces model reset. The converse switch should only lead to progressive model change, as violations of a random model are statistically more obscure. We also considered a novel way of inducing model reset by switching between different regular patterns. With N=21 participants, we replicated Zhao et al. (2019), showing that PDRs are induced by switches from regular
to either random or regular patterns but not by switches from random to regular patterns. In addition, we detected a later pupil constriction induced by switches from one regular to another regular pattern.
Results suggest that LC-NE is indeed sensitive to model reset.