ArticleScientific reports2019
Introducing a Bayesian model of selective attention based on active inference.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
34 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prediction in Autism Spectrum Disorder: A Systematic Review of Empirical Evidence.Autism research : official journal of the International Society for Autism Research · 2021Pooled it
- Unveiling the Aha! moment: A computational account of insight in active inference.Psychonomic bulletin & review · 2026Review
- Writing Increases Precision-Weighted Inference of Conceptual Organization: A Bayesian-Brain Active-Inference Model of the Writing-over-Speaking Advantage in Analytic Thinking.Brain sciences · 2026Article
- Voluntary Attention Selectively Modulates Omission Responses.Human brain mapping · 2026Article
- The phantastic organ: predictive processing in the brain.Frontiers in psychology · 2026Review
- Load-dependent processing of prediction violations in task-irrelevant space.Journal of vision · 2025Article
- Negative affect-driven impulsivity as hierarchical model-based overgeneralization.Trends in cognitive sciences · 2025Review
- Expectation-driven sensory adaptations support enhanced acuity during categorical perception.Nature neuroscience · 2025Article
- The interplay of uncertainty, relevance and learning influences auditory categorization.Scientific reports · 2025Article
- Conscious active inference I: A quantum model naturally implements the path integral needed for real-time planning and control.Computational and structural biotechnology journal · 2025Review
- Deep computational neurophenomenology: a methodological framework for investigating the how of experience.Neuroscience of consciousness · 2025Article
- Active inference goes to school: the importance of active learning in the age of large language models.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Article
- A computational approach to selective attention in embodied approaches to cognitive archaeology.Journal of the Royal Society, Interface · 2024Review
- Motor "laziness" constrains fixation selection in real-world tasks.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Improved emotion differentiation under reduced acoustic variability of speech in autism.BMC medicine · 2024Article
- Bistable perception, precision and neuromodulation.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Forgetting ourselves in flow: an active inference account of flow states and how we experience ourselves within them.Frontiers in psychology · 2024Article
- Consciousness, (meta)cognition, and culture.Quarterly journal of experimental psychology (2006) · 2023Article
- Autistic traits shape neuronal oscillations during emotion perception under attentional load modulation.Scientific reports · 2023Article
- AttentionMNIST: a mouse-click attention tracking dataset for handwritten numeral and alphabet recognition.Scientific reports · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Information gathering comprises actions whose (sensory) consequences resolve uncertainty (i.e., are salient). In other words, actions that solicit salient information cause the greatest shift in beliefs (i.e., information gain) about the causes of our sensations. However, not all information is relevant to the task at hand: this is especially the case in complex, naturalistic scenes. This paper introduces a formal model of selective attention based on active inference and contextual epistemic foraging. We consider a visual search task with a special emphasis on goal-directed and task-relevant exploration. In this scheme, attention modulates the expected fidelity (precision) of the mapping between observations and hidden states in a state-dependent or context-sensitive manner. This ensures task-irrelevant observations have little expected information gain, and so the agent - driven to reduce expected surprise (i.e., uncertainty) - does not actively seek them out. Instead, it selectively samples task-relevant observations, which inform (task-relevant) hidden states. We further show, through simulations, that the atypical exploratory behaviours in conditions such as autism and anxiety may be due to a failure to appropriately modulate sensory precision in a context-specific way.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.