Perceptual awareness and active inference
Open accessAbstract
Perceptual awareness depends upon the way in which we engage with our sensorium. This notion is central to active inference, a theoretical framework that treats perception and action as inferential processes. This variational perspective on cognition formalizes the notion of perception as hypothesis testing and treats actions as experiments that are designed (in part) to gather evidence for or against alternative hypotheses. The common treatment of perception and action affords a useful interpretation of certain perceptual phenomena whose active component is often not acknowledged. In this article, we start by considering Troxler fading – the dissipation of a peripheral percept during maintenance of fixation, and its recovery during free (saccadic) exploration. This offers an important example of the failure to maintain a percept without actively interrogating a visual scene. We argue that this may be understood in terms of the accumulation of uncertainty about a hypothesized stimulus when free exploration is disrupted by experimental instructions or pathology. Once we take this view, we can generalize the idea of using bodily (oculomotor) action to resolve uncertainty to include the use of mental (attentional) actions for the same purpose. This affords a useful way to think about binocular rivalry paradigms, in which perceptual changes need not be associated with an overt movement.
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The notion of mental action -in which covert attentional policies are selected in a way analogous to those driving overt behaviour -highlights the fundamental explanatory role of such executive processes as attentional regulation (i.e., precision-optimisation) and decision-making (i.e., planning-as-inference) in AI-C.
“However, the notion of mental action -in which covert attentional policies are selected in a way analogous to those driving overt behaviour (Limanowski & Friston, 2018; Parr, Corcoran, et al., 2019) -highlights the fundamental explanatory role of such executive processes as attentional regulation (i.e., precision-optimisation) and decision-making (i.e., planning-as-inference) in AI-C.”
From Integrated information and predictive processing theories of consciousness: An adversarial collaborative review (2026) · cites this paper as Parr, Corcoran, et al., 2019
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- Authors
- Parr, T., Corcoran, A. W., Friston, K. J., & Hohwy, J.
- Affiliations
- Wellcome Centre for Human Neuroimaging (GB)
- Monash University (AU)
- Corresponding author
- Parr, Thomas
- Venue
- Neuroscience of Consciousness
- Publisher
- Oxford University Press (OUP)
- Published
- 2019-01-01
- Volume
- 2019
- Issue
- 1
- Pages
- niz012-niz012
- ISSN
- 2057-2107 (ISSN-L)
- PMC
- PMC6734140
- OpenAlex
- W2973013188
- Cited by
- 91
- References
- 134
- Citations by year
- 2026: 9 · 2025: 13 · 2024: 13 · 2023: 16 · 2022: 12 · 2021: 14 · 2020: 12 · 2019: 1 · 2018: 1
- FWCI
- 5.67
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Neuroscience of Consciousness (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Monash University Research Portal (Monash University) (submittedVersion, other-oa)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Rosetrees Trust (173346)
- Australian Government Research Training Program
- RTP
- Wellcome Principal Research Fellow (088130/Z/09/Z)
- Australian Research Council (DP160102770, DP190101805)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Embodied and Extended Cognition
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Philosophy and Theoretical Science
- Keywords
- perceptual awareness, active inference, perceptual uncertainty, saccades, attention, binocular rivalry, perception-action coupling, hypothesis testing, free exploration, visual perception
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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