Every Good Regulator of a System Must Be a Model of That System

The theory of constructed emotion: an active inference account of interoception and categorization

Barrett, L. F. (2016) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsw154 · Cited by 1,426 · see citing works

Ecological interface design: theoretical foundations

Vicente, K. J., & Rasmussen, J. (1992) · IEEE Transactions on Systems, Man and Cybernetics · doi:10.1109/21.156574 · Cited by 1,084 · see citing works

Active interoceptive inference and the emotional brain

Seth, A. K., & Friston, K. J. (2016) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2016.0007 · Cited by 945 · see citing works

The theory of constructed emotion: an active inference account of interoception and categorization

Barrett, L. F. (2017) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsx060 · Cited by 950 · see citing works

Life as we know it

Friston, K. (2013) · Journal of The Royal Society Interface · doi:10.1098/rsif.2013.0475 · Cited by 754 · see citing works

Active Inference, homeostatic regulation and adaptive behavioural control

Pezzulo, G., Rigoli, F., & Friston, K. (2015) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2015.09.001 · Cited by 650 · see citing works

An active inference theory of allostasis and interoception in depression

Barrett, L. F., Quigley, K. S., & Hamilton, P. (2016) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2016.0011 · Cited by 554 · see citing works

The Markov blankets of life: autonomy, active inference and the free energy principle

Kirchhoff, M., Parr, T., Palacios, E., Friston, K., & Kiverstein, J. (2018) · Journal of The Royal Society Interface · doi:10.1098/rsif.2017.0792 · Cited by 463 · see citing works

From cognitivism to autopoiesis: towards a computational framework for the embodied mind

Allen, M., & Friston, K. J. (2018) · Synthese · doi:10.1007/s11229-016-1288-5 · Cited by 386 · see citing works

A free energy principle for biological systems

Karl, F. (2012) · Entropy · doi:10.3390/e14112100 · Cited by 377 · see citing works

Direct Fit to Nature: An Evolutionary Perspective on Biological and Artificial Neural Networks

Hasson, U., Nastase, S. A., & Goldstein, A. (2020) · Neuron · doi:10.1016/j.neuron.2019.12.002 · Cited by 387 · see citing works

Free-Energy Minimization and the Dark-Room Problem

Friston, K., Thornton, C., & Clark, A. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00130 · Cited by 367 · see citing works

Answering Schrödinger's question: A free-energy formulation

Ramstead, M. J. D., Badcock, P. B., & Friston, K. J. (2018) · Physics of Life Reviews · doi:10.1016/j.plrev.2017.09.001 · Cited by 354 · see citing works

The anatomy of choice: active inference and agency

Friston, K., Schwartenbeck, P., FitzGerald, T., Moutoussis, M., Behrens, T., & Dolan, R. J. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00598 · Cited by 340 · see citing works

Being a Beast Machine: The Somatic Basis of Selfhood

Seth, A. K., & Tsakiris, M. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.08.008 · Cited by 357 · see citing works

Bayesian approaches to autism: Towards volatility, action, and behavior.

Palmer, C. J., Lawson, R. P., & Hohwy, J. (2017) · Psychological Bulletin · doi:10.1037/bul0000097 · Cited by 307 · see citing works

The anatomy of choice: dopamine and decision-making.

Friston, K., Schwartenbeck, P., FitzGerald, T., Moutoussis, M., Behrens, T., & Dolan, R. J. (2014) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2013.0481 · Cited by 289 · see citing works

Minimal self-models and the free energy principle.

Limanowski, J., & Blankenburg, F. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00547 · Cited by 263 · see citing works

Knowing one's place: a free-energy approach to pattern regulation

Friston, K., Levin, M., Sengupta, B., & Pezzulo, G. (2015) · Journal of The Royal Society Interface · doi:10.1098/rsif.2014.1383 · Cited by 234 · see citing works

The emergence of global systemic risk

Centeno, M. A., Nag, M., Patterson, T. S., Shaver, A., & Windawi, A. J. (2015) · Annual Review of Sociology · doi:10.1146/annurev-soc-073014-112317 · Cited by 240 · see citing works

Homeostatic reinforcement learning for integrating reward collection and physiological stability

Keramati, M., & Gutkin, B. (2014) · eLife · doi:10.7554/elife.04811 · Cited by 218 · see citing works

A variational approach to niche construction

Constant, A., Ramstead, M. J. D., Veissière, S. P. L., Campbell, J. O., & Friston, K. J. (2018) · Journal of The Royal Society Interface · doi:10.1098/rsif.2017.0685 · Cited by 204 · see citing works

Computational psychosomatics and computational psychiatry: Toward a joint framework for differential diagnosis

Petzschner, F. H., Weber, L. A. E., Gard, T., & Stephan, K. E. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.05.012 · Cited by 181 · see citing works

The sense of should: A biologically-based framework for modeling social pressure

Theriault, J. E., Young, L., & Barrett, L. F. (2021) · Physics of Life Reviews · doi:10.1016/j.plrev.2020.01.004 · Cited by 201 · see citing works

Sentience and the Origins of Consciousness: From Cartesian Duality to Markovian Monism

Friston, K. J., Wiese, W., & Hobson, J. A. (2020) · Entropy · doi:10.3390/e22050516 · Cited by 186 · see citing works

Pharmacological Fingerprints of Contextual Uncertainty

Marshall, L., Mathys, C., Ruge, D., de Berker, A. O., Dayan, P., Stephan, K. E., & Bestmann, S. (2016) · PLOS Biology · doi:10.1371/journal.pbio.1002575 · Cited by 158 · see citing works

Forms of prediction in the nervous system

Teufel, C., & Fletcher, P. C. (2020) · Nature Reviews Neuroscience · doi:10.1038/s41583-020-0275-5 · Cited by 155 · see citing works

Prediction error, ketamine and psychosis: An updated model

Corlett, P. R., Honey, G. D., & Fletcher, P. C. (2016) · Journal of Psychopharmacology · doi:10.1177/0269881116650087 · Cited by 142 · see citing works

Universal darwinism as a process of bayesian inference

Campbell, J. O. (2016) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2016.00049 · Cited by 140 · see citing works

Markov blankets, information geometry and stochastic thermodynamics

Parr, T., Da Costa, L., & Friston, K. (2020) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2019.0159 · Cited by 141 · see citing works

Towards a neuronal gauge theory

Sengupta, B., Tozzi, A., Cooray, G. K., Douglas, P. K., & Friston, K. J. (2016) · PLOS Biology · doi:10.1371/journal.pbio.1002400 · Cited by 132 · see citing works

A mathematical model of embodied consciousness.

Rudrauf, D., Bennequin, D., Granic, I., Landini, G., Friston, K., & Williford, K. (2017) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2017.05.032 · Cited by 118 · see citing works

Learning action-oriented models through active inference

Tschantz, A., Seth, A. K., & Buckley, C. L. (2020) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1007805 · Cited by 121 · see citing works

Predictive Coding: a Theoretical and Experimental Review

Millidge, B., Seth, A., & Buckley, C. L. (2021) · arXiv · doi:10.48550/arxiv.2107.12979 · Cited by 106 · see citing works

The first prior: From co-embodiment to co-homeostasis in early life

Ciaunica, A., Constant, A., Preissl, H., & Fotopoulou, K. (2021) · Consciousness and Cognition · doi:10.1016/j.concog.2021.103117 · Cited by 105 · see citing works

Deep active inference

Ueltzhöffer, K. (2018) · Biological Cybernetics · doi:10.1007/s00422-018-0785-7 · Cited by 98 · see citing works

Neurocomputational mechanisms underlying emotional awareness: Insights afforded by deep active inference and their potential clinical relevance

Smith, R., Lane, R. D., Parr, T., & Friston, K. J. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.09.002 · Cited by 89 · see citing works

Apical drive-A cellular mechanism of dreaming?

Aru, J., Siclari, F., Phillips, W. A., & Storm, J. F. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.09.018 · Cited by 74 · see citing works

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 · see citing works

The concept of complexity in organisations and information systems

Backlund, A. (2002) · Kybernetes · doi:10.1108/03684920210414907 · Cited by 48 · see citing works

Consciousness in active inference: Deep self-models, other minds, and the challenge of psychedelic-induced ego-dissolution

Deane, G. (2021) · Neuroscience of Consciousness · doi:10.1093/nc/niab024 · Cited by 38 · see citing works

The attention schema theory in a neural network agent: Controlling visuospatial attention using a descriptive model of attention

Wilterson, A. I., & Graziano, M. S. A. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2102421118 · Cited by 26 · see citing works

Pragmatism and the predictive mind

Williams, D. (2018) · Phenomenology and the Cognitive Sciences · doi:10.1007/s11097-017-9556-5 · Cited by 22 · see citing works

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 · see citing works

The Brain as a Cultural Artifact: Concepts, Actions, and Experiences within the Human Affective Niche

Gendron, M., Mesquita, B., & Barrett, L. F. (2020) · Culture, Mind, and Brain · doi:10.1017/9781108695374.010 · Cited by 20 · see citing works

Body and world as phenomenal contents of the brain's reality model

Merker, B. (2013) · The Unity of Mind, Brain and World · doi:10.1017/cbo9781139207065.002 · Cited by 13 · see citing works

Robust agents learn causal world models

Richens, J., & Everitt, T. (2024) · arXiv · doi:10.48550/arxiv.2402.10877 · Cited by 5 · see citing works

Attention schema in neural agents

Liu, D., Bolotta, S., Zhu, H., Bengio, Y., & Dumas, G. (2023) · arXiv · doi:10.48550/arxiv.2305.17375 · Cited by 1 · see citing works