The DOI matches its Crossref record.
Surfing Uncertainty: Prediction, Action, and the Embodied Mind
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“In addition, although Broca's area typically activates during performance of IS tasks [43], there are reasons for caution in assuming that neural signatures elicited by task instructions will align with IS that arises more spontaneously [17].”
From Inner speech as language process and cognitive tool (2023) · cites this paper as [43]
In the citing paper
“Hierarchical predictive processing (HPP) offers powerfully explanatory implementational and algorithmic details for active inference (Clark, 2016), providing a single mechanism for both perception and action.”
From An Integrated World Modeling Theory (IWMT) of Consciousness (2020) · cites this paper as Clark, 2016
In the citing paper
“According to these theories, predictions and incoming sensory input each have an associated precision (inverse variance) reflecting their confidence or reliability.”
From Precision weighting of cortical unsigned prediction error signals benefits learning, is mediated by dopamine, and is impaired in psychosis (2021) · cites this paper as [8]
In the citing paper
“a mechanism known as ‘precision weighting’ modulates the impact within the overall system that sets of errors have: high weighting drives learning and further engagement, while low weighting renders error units relatively impotent”
From Active inference goes to school: the importance of active learning in the age of large language models (2024) · cites this paper as [33]
In the citing paper
“The AIF aims to deliver a process theory explaining how agents remain within expected bounds, minimizing uncertainty within volatile environments”
From Active inference goes to school: the importance of active learning in the age of large language models (2024) · cites this paper as [33]
In the citing paper
“In AIF terms, the brain encodes a probabilistic generative model of the causes of its sensations, which it leverages to generate action”
From Active inference goes to school: the importance of active learning in the age of large language models (2024) · cites this paper as [33]
In the citing paper
“If predictions fail to match the incoming sensory data, ‘prediction errors’ are generated that propagate upward through the hierarchy of the generative model, driving action and revised prediction.”
From Active inference goes to school: the importance of active learning in the age of large language models (2024) · cites this paper as [33]
In the citing paper
“Rather than passively waiting for incoming sensory information, systems are proactive, generating ‘top–down’ predictions about future states”
From Active inference goes to school: the importance of active learning in the age of large language models (2024) · cites this paper as [33]
In the citing paper
“In predictable situations, organisms may rely on automatized reflexive responses (in which case, the biologically viable predictions are made through natural selection and embodied in the phenotype; see Clark, 2016).”
From The Hard Problem of Consciousness and the Free Energy Principle (2019) · cites this paper as Clark, 2016
Citations
Cited by
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Towards a neuroscience of active sampling and curiosity
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Ramstead, M. J. D., Veissière, S. P. L., & Kirmayer, L. J. (2016) · Frontiers in Psychology · doi:10.3389/fpsyg.2016.01090 · Cited by 422
Effects of Cognitive Load on Driving Performance: The Cognitive Control Hypothesis
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The Hard Problem of Consciousness and the Free Energy Principle
Solms, M. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.02714 · Cited by 239
“In predictable situations, organisms may rely on automatized reflexive responses (in which case, the biologically viable predictions are made through natural selection and embodied in the phenotype; see Clark, 2016).”
The power of predictions: An emerging paradigm for psychological research
Hutchinson, J. B., & Barrett, L. F. (2019) · Current Directions in Psychological Science · doi:10.1177/0963721419831992 · Cited by 216
A nice surprise? Predictive processing and the active pursuit of novelty
Clark, A. (2018) · Phenomenology and the Cognitive Sciences · doi:10.1007/s11097-017-9525-z · Cited by 156
Self-citationSafron, A. (2020) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2020.00030 · Cited by 133
“Hierarchical predictive processing (HPP) offers powerfully explanatory implementational and algorithmic details for active inference (Clark, 2016), providing a single mechanism for both perception and action.”
A Theory of Resonance: Towards an Ecological Cognitive Architecture
Raja, V. (2018) · Minds and Machines · doi:10.1007/s11023-017-9431-8 · Cited by 115
Happily entangled: prediction, emotion, and the embodied mind
Miller, M., & Clark, A. (2018) · Synthese · doi:10.1007/s11229-017-1399-7 · Cited by 114
Self-citationHaarsma, J., Fletcher, P. C., Griffin, J. D., Taverne, H. J., Ziauddeen, H., Spencer, T. J., Miller, C., Katthagen, T., Goodyer, I., Diederen, K. M. J., et al. (2021) · Molecular Psychiatry · doi:10.1038/s41380-020-0803-8 · Cited by 108
Where There is Life There is Mind: In Support of a Strong Life-Mind Continuity Thesis
Kirchhoff, M. D., & Froese, T. (2017) · Entropy · doi:10.3390/e19040169 · Cited by 114
Active inference as a theory of sentient behavior
Pezzulo, G., Parr, T., & Friston, K. (2024) · Biological Psychology · doi:10.1016/j.biopsycho.2023.108741 · Cited by 109
If perception is probabilistic, why does it not seem probabilistic?
Block, N. (2018) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2017.0341 · Cited by 91
Allostasis as a core feature of hierarchical gradients in the human brain
Katsumi, Y., Theriault, J. E., Quigley, K. S., & Barrett, L. F. (2022) · Network Neuroscience · doi:10.1162/netn_a_00240 · Cited by 88
Psychotic Experiences in Schizophrenia and Sensitivity to Sensory Evidence
Weilnhammer, V., Röd, L., Eckert, A.-L., Stuke, H., Heinz, A., & Sterzer, P. (2020) · Schizophrenia Bulletin · doi:10.1093/schbul/sbaa003 · Cited by 65
From symbols to icons: the return of resemblance in the cognitive neuroscience revolution
Williams, D., & Colling, L. (2018) · Synthese · doi:10.1007/s11229-017-1578-6 · Cited by 69
What are the contents of representations in predictive processing?
Wiese, W. (2017) · Phenomenology and the Cognitive Sciences · doi:10.1007/s11097-016-9472-0 · Cited by 66
Williams, D. (2020) · Synthese · doi:10.1007/s11229-018-1768-x · Cited by 63
Action is enabled by systematic misrepresentations
Wiese, W. (2017) · Erkenntnis · doi:10.1007/s10670-016-9867-x · Cited by 60
Fabry, R. E., & Kukkonen, K. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.02648 · Cited by 59
Degeneracy and Redundancy in Active Inference
Sajid, N., Parr, T., Hope, T. M., Price, C. J., & Friston, K. J. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa148 · Cited by 49
Increasing Our Insular World View: interoception and Psychopathology for Psychotherapists.
Duquette, P. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00135 · Cited by 54
Dual Process Theory: Embodied and Predictive; Symbolic and Classical
Bellini-Leite, S. C. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.805386 · Cited by 52
Expecting some action: predictive processing and the construction of conscious experience
Nave, K., Deane, G., Miller, M., & Clark, A. (2022) · Review of Philosophy and Psychology · doi:10.1007/s13164-022-00644-y · Cited by 50
Self-citationDeane, G. (2021) · Neuroscience of Consciousness · doi:10.1093/nc/niab024 · Cited by 38
Rapaport, H., Clapham, H., Adams, J., Lawson, W., Porayska-Pomsta, K., & Pellicano, E. (2024) · Autism · doi:10.1177/13623613231198916 · Cited by 35
Mills, C., Zamani, A., White, R., & Christoff, K. (2021) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2019.0692 · Cited by 27
Neural and neuronal discoordination in schizophrenia: from ensembles through networks to symptoms
Krajcovic, B., Fajnerova, I., Horacek, J., Kelemen, E., Kubik, S., Svoboda, J., & Stuchlik, A. (2019) · Acta Physiologica · doi:10.1111/apha.13282 · Cited by 29
Pragmatism and the predictive mind
Williams, D. (2018) · Phenomenology and the Cognitive Sciences · doi:10.1007/s11097-017-9556-5 · Cited by 22
Is free-energy minimisation the mark of the cognitive?
Kiverstein, J., & Sims, M. (2021) · Biology & Philosophy · doi:10.1007/s10539-021-09788-0 · Cited by 23
The Free Energy Principle: Good Science and Questionable Philosophy in a Grand Unifying Theory
Sánchez-Cañizares, J. (2021) · Entropy · doi:10.3390/e23020238 · Cited by 16
Gendron, M., Mesquita, B., & Barrett, L. F. (2020) · Culture, Mind, and Brain · doi:10.1017/9781108695374.010 · Cited by 20
Aubert‐Teillaud, B., Bran, A., & Vaidis, D. C. (2023) · European Journal of Social Psychology · doi:10.1002/ejsp.2981 · Cited by 19
Surprise! Why enactivism and predictive processing are parting ways: The case of improvisation
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The myth of the Bayesian brain
Mangalam, M. (2025) · European Journal of Applied Physiology · doi:10.1007/s00421-025-05855-6 · Cited by 14
Di Paolo, L. D., White, B., Guénin-Carlut, A., Constant, A., & Clark, A. (2024) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2023.0148 · Cited by 14
“Rather than passively waiting for incoming sensory information, systems are proactive, generating ‘top–down’ predictions about future states [33,35].”
InfluentialSelf-citationEditorial: Predictive Processing and Consciousness
Miller, M., Clark, A., & Schlicht, T. (2022) · Review of Philosophy and Psychology · doi:10.1007/s13164-022-00666-6 · Cited by 8
Self-citationAkgun, M., & Toker, S. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790980 · Cited by 2
Metadata
- Authors
- Clark, A.
- Corresponding author
- Clark, Andy
- ORCID
- Clark, Andy
- Venue
- Oxford University Press eBooks
- Publisher
- Oxford University Press
- Published
- 2016-01-01
- OpenAlex
- W4241976975
- Cited by
- 1,358
- References
- 0
- Citations by year
- 2026: 199 · 2025: 161 · 2024: 147 · 2023: 116 · 2022: 103 · 2021: 108 · 2020: 122 · 2019: 221 · 2018: 99 · 2017: 59 · 2016: 22
- FWCI
- 65.79
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Oxford University Press eBooks (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Tourism, Leisure and Hospitality Management › Adventure Sports and Sensation Seeking
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Sociology and Political Science › Risk Perception and Management
- Keywords
- uncertainty
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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.
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