ArticleFrontiers in neurorobotics2022
Reclaiming saliency: Rhythmic precision-modulated action and perception.
Article in Frontiers in neurorobotics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- An active inference account of stuttering behavior.Frontiers in human neuroscience · 2025Article
- A computational approach to selective attention in embodied approaches to cognitive archaeology.Journal of the Royal Society, Interface · 2024Review
- Active Vision in Binocular Depth Estimation: A Top-Down Perspective.Biomimetics (Basel, Switzerland) · 2023Article
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6 authors.
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Abstract
Computational models of visual attention in artificial intelligence and robotics have been inspired by the concept of a saliency map. These models account for the mutual information between the (current) visual information and its estimated causes. However, they fail to consider the circular causality between perception and action. In other words, they do not consider where to sample next, given current beliefs. Here, we reclaim salience as an active inference process that relies on two basic principles: uncertainty minimization and rhythmic scheduling. For this, we make a distinction between attention and salience. Briefly, we associate attention with precision control, i.e., the confidence with which beliefs can be updated given sampled sensory data, and salience with uncertainty minimization that underwrites the selection of future sensory data. Using this, we propose a new account of attention based on rhythmic precision-modulation and discuss its potential in robotics, providing numerical experiments that showcase its advantages for state and noise estimation, system identification and action selection for informative path planning.
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