Vanilla PP for Philosophers

Adams, R. A., Huys, Q. J. & Roiser, J. P. (2016). Computational psychiatry: Towards a mathematically informed understanding of mental illness. J Neurol Neurosurg Psychiatry, 87 (1), 53-63. https://dx.doi.org/10.1136/jnnp-2015-310737

Anderson, M. L. (2017). Of Bayes and bullets: An embodied, situated, targeting-based account of predictive processing. En T. Metzinger & W. Wiese (Eds.) Philosophy and predictive processing. MIND Group.

Anderson, M. L. & Chemero, T. (2013). The problem with brain GUTs: Conflation of different senses of ‘’prediction’’ threatens metaphysical disaster. Behavioral and Brain Sciences, 36 (3), 204–205.

Badets, A., Koch, I. & Philipp, A. M. (2014). A review of ideomotor approaches to perception, cognition, action, and language: Advancing a cultural recycling hypothesis. Psychological Research, 80 (1), 1–15. https://dx.doi.org/10.1007/s00426-014-0643-8

Bastos, A. M., Usrey, W. M., Adams, R. A., Mangun, G. R., Fries, P. & Friston, K. J. (2012). Canonical microcircuits for predictive coding. Neuron, 76 (4), 695-711. https://dx.doi.org/10.1016/j.neuron.2012.10.038

Bogacz, R. (2015). A tutorial on the free-energy framework for modelling perception and learning. Journal of Mathematical Psychology. https://dx.doi.org/10.1016/j.jmp.2015.11.003

Brodski, A., Paasch, G.-F., Helbling, S. & Wibral, M. (2015). The faces of predictive coding. The Journal of Neuroscience, 35 (24), 8997-9006. https://dx.doi.org/10.1523/jneurosci.1529-14.2015

Brook, A. (2013). Kant’s view of the mind and consciousness of self. En E. N. Zalta (Ed.) The Stanford Encyclopedia of Philosophy.

Bruineberg, J. (2017). Active inference and the primacy of the ‘I can’. En T. Metzinger & W. Wiese (Eds.) Philosophy and predictive processing. MIND Group.

Bruineberg, J., Kiverstein, J. & Rietveld, E. (2016). The anticipating brain is not a scientist: The free-energy principle from an ecological-enactive perspective. Synthese, 1–28. https://dx.doi.org/10.1007/s11229-016-1239-1

Burr, C. (2017). Embodied decisions and the predictive brain. En T. Metzinger & W. Wiese (Eds.) Philosophy and predictive processing. MIND Group.

Butz, M. V. (2017). Which structures are out there? Learning predictive compositional concepts based on social sensorimotor explorations. En T. Metzinger & W. Wiese (Eds.) Philosophy and predictive processing. MIND Group.

Clark, A. (2013a). Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and Brain Sciences, 36 (3), 181–204. https://dx.doi.org/10.1017/S0140525X12000477

Clark, A. (2013b). The many faces of precision (Replies to commentaries on ‘’Whatever next? Neural prediction, situated agents, and the future of cognitive science’’). Frontiers in Psychology, 4, 270. https://dx.doi.org/10.3389/fpsyg.2013.00270

Clark, A. (2013c). Are we predictive engines? Perils, prospects, and the puzzle of the porous perceiver. Behavioral and Brain Sciences, 36 (3), 233–253. https://dx.doi.org/10.1017/S0140525X12002440

Clark, A. (2015). Radical predictive processing. The Southern Journal of Philosophy, 53, 3–27. https://dx.doi.org/10.1111/sjp.12120

Clark, A. (2016). Surfing uncertainty: Prediction, action, and the embodied mind. Oxford University Press.

Clark, A. (2017). How to knit your own Markov blanket: Resisting the second law with metamorphic minds. En T. Metzinger & W. Wiese (Eds.) Philosophy and predictive processing. MIND Group.

Clark, A. (En prensa). Busting out: Predictive brains, embodied minds, and the puzzle of the evidentiary veil. Noûs. https://dx.doi.org/10.1111/nous.12140

Clowes, M. B. (1969). Pictorial relationships – A syntactic approach. En B. Meltzer & D. Michie (Eds.) (pp. 361–383). Edinburgh University Press.

Colombo, M. (2017). Social motivation in computational neuroscience: Or if brains are prediction machines then the Humean theory of motivation is false. En J. Kieverstein (Ed.) Routledge handbook of philosophy of the social mind. Routledge.

Dennett, D. C. (2013). Intuition pumps and other tools for thinking. Norton & Company.

Dewhurst, J. (2017). Folk psychology and the Bayesian brain. En T. Metzinger & W. Wiese (Eds.) Philosophy and predictive processing. MIND Group.

Downey, A. (2017). Radical sensorimotor enactivism & predictive processing. Providing a conceptual framework for the scientific study of conscious perception. En T. Metzinger & W. Wiese (Eds.) Philosophy and predictive processing. MIND Group.

Dołega, K. (2017). Moderate predictive processing. En T. Metzinger & W. Wiese (Eds.) Philosophy and predictive processing. MIND Group.

Drayson, Z. (2017). Modularity and the predictive mind. En T. Metzinger & W. Wiese (Eds.) Philosophy and predictive processing. MIND Group.

Egan, F. (2014). How to think about mental content. Philosophical Studies, 170 (1), 115-135. https://dx.doi.org/10.1007/s11098-013-0172-0

Eliasmith, C. (2000). How neurons mean: A neurocomputational theory of representational content. PhD dissertation, Washington University in St. Louis. Department of Philosophy.

Engel, A. K., Fries, P. & Singer, W. (2001). Dynamic predictions: Oscillations and synchrony in top-down processing. Nat Rev Neurosci, 2 (10), 704–716.

Fabry, R. E. (2017a). Predictive processing and cognitive development. En T. Metzinger & W. Wiese (Eds.) Philosophy and predictive processing. MIND Group.

Fabry, R. E. (2017b). Transcending the evidentiary boundary: Prediction error minimization, embodied interaction, and explanatory pluralism. Philosophical Psychology, 1–20. https://dx.doi.org/10.1080/09515089.2016.1272674

Feldman, H. & Friston, K. J. (2010). Attention, uncertainty, and free-energy. Frontiers in Human Neuroscience, 4. https://dx.doi.org/10.3389/fnhum.2010.00215

Friston, K. (2003). Learning and inference in the brain. Neural Networks, 16 (9), 1325–1352.

Friston, K. (2005). A theory of cortical responses. Philosophical Transactions of the Royal Society B: Biological Sciences, 360 (1456), 815-836. https://dx.doi.org/10.1098/rstb.2005.1622

Friston, K. (2008). Hierarchical models in the brain. PLoS Computational Biology, 4 (11), e1000211. https://dx.doi.org/10.1371/journal.pcbi.1000211

Friston, K. (2009). The free-energy principle: A rough guide to the brain? Trends in Cognitive Sciences, 13 (7), 293–301. https://dx.doi.org/10.1016/j.tics.2009.04.005

Friston, K. (2010). The free-energy principle: A unified brain theory? Nature Reviews Neuroscience, 11 (2), 127–138. https://dx.doi.org/10.1038/nrn2787

Friston, K. & Buzsáki, G. (2016). The functional anatomy of time: What and when in the brain. Trends in Cognitive Sciences, 20 (7), 500–511. https://dx.doi.org/10.1016/j.tics.2016.05.001

Friston, K. & Kiebel, S. (2009). Predictive coding under the free-energy principle. Philosophical Transactions of the Royal Society B: Biological Sciences, 364 (1521), 1211–1221. https://dx.doi.org/10.1098/rstb.2008.0300

Friston, K. J. & Stephan, K. E. (2007). Free-energy and the brain. Synthese, 159 (3), 417-458. https://dx.doi.org/10.1007/s11229-007-9237-y

Friston, K., Mattout, J. & Kilner, J. (2011). Action understanding and active inference. Biological Cybernetics, 104 (1-2), 137–160. https://dx.doi.org/10.1007/s00422-011-0424-z

Friston, K., Samothrakis, S. & Montague, R. (2012a). Active inference and agency: Optimal control without cost functions. Biological Cybernetics, 106 (8), 523-541. https://dx.doi.org/10.1007/s00422-012-0512-8

Friston, K., Adams, R., Perrinet, L. & Breakspear, M. (2012b). Perceptions as hypotheses: Saccades as experiments. Frontiers in Psychology, 3 (151). https://dx.doi.org/10.3389/fpsyg.2012.00151

Friston, K. J., Stephan, K. E., Montague, R. & Dolan, R. J. (2014). Computational psychiatry: The brain as a phantastic organ. The Lancet Psychiatry, 1 (2), 148–158. https://dx.doi.org/10.1016/S2215-0366(14)70275-5

Giordanetti, P., Pozzo, R. & Sgarbi, M. (2012). Kant‘s philosophy of the unconscious. De Gruyter.

Gonzalez-Gadea, M. L., Chennu, S., Bekinschtein, T. A., Rattazzi, A., Beraudi, A., Tripicchio, P., Moyano, B., Soffita, Y., Steinberg, L., Adolfi, F., Sigman, M., Marino, J., Manes, F. & Ibanez, A. (2015). Predictive coding in autism spectrum disorder and attention deficit hyperactivity disorder. Journal of Neurophysiology, 114 (5), 2625-2636. https://dx.doi.org/10.1152/jn.00543.2015

Gregory, R. L. (1980). Perceptions as hypotheses. Philosophical Transactions of the Royal Society of London. B, Biological Sciences, 290 (1038), 181–197.

Grush, R. (2004). The emulation theory of representation: Motor control, imagery, and perception. Behavioral and Brain Sciences, 27 (3), 377–396.

Gładziejewski, P. (2016). Predictive coding and representationalism. Synthese, 559–582. https://dx.doi.org/10.1007/s11229-015-0762-9

Harkness, D. L. & Keshava, A. (2017). Moving from the what to the how and where – Bayesian models and predictive processing. En T. Metzinger & W. Wiese (Eds.) Philosophy and predictive processing. MIND Group.

Herbart, J. F. (1825). Psychologie als Wissenschaft neu gegründet auf Erfahrung, Metaphysik und Mathematik. Zweiter, analytischer Teil. Unzer.

Hohwy, J. (2010). The hypothesis testing brain: Some philosophical applications. En W. Christensen, E. Schier & J. Sutton (Eds.) Proceedings of the 9th conference of the Australasian society for cognitive science (pp. 135–144). Macquarie Centre for Cognitive Science. https://dx.doi.org/10.5096/ASCS200922

Hohwy, J. (2012). Attention and conscious perception in the hypothesis testing brain. Frontiers in Psychology, 3. https://dx.doi.org/10.3389/fpsyg.2012.00096

Hohwy, J. (2013). The predictive mind. Oxford University Press.

Hohwy, J. (2016). The self-evidencing brain. Noûs, 50 (2), 259–285. https://dx.doi.org/10.1111/nous.12062

Hohwy, J. (2017). How to entrain your evil demon. En T. Metzinger & W. Wiese (Eds.) Philosophy and predictive processing. MIND Group.

Hommel, B. (2015). The theory of event coding (TEC) as embodied-cognition framework. Frontiers in Psychology, 6. https://dx.doi.org/10.3389/fpsyg.2015.01318

Hommel, B., Müsseler, J., Aschersleben, G. & Prinz, W. (2001). The theory of event coding (TEC): A framework for perception and action planning. Behavioral and Brain Sciences, 24, 849–878. https://dx.doi.org/10.1017/S0140525X01000103

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Kiefer, A. (2017). Literal perceptual inference. En T. Metzinger & W. Wiese (Eds.) Philosophy and predictive processing. MIND Group.

Lake, B. M., Salakhutdinov, R. & Tenenbaum, J. B. (2015). Human-level concept learning through probabilistic program induction. Science, 350 (6266), 1332-1338. https://dx.doi.org/10.1126/science.aab3050

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Lenoir, T. (2006). Operationalizing Kant: Manifolds, models, and mathematics in Helmholtz’s theories of perception. En M. Friedman & A. Nordmann (Eds.) The Kantian legacy in nineteenth-century science (pp. 141–210). Cambridge, MA: MIT Press.

Limanowski, J. (2017). (Dis-)attending to the body. Action and self-experience in the active inference framework. En T. Metzinger & W. Wiese (Eds.) Philosophy and predictive processing. MIND Group.

Lotze, R. H. (1852). Medicinische Psychologie oder Physiologie der Seele. Weidmann’sche Buchhandlung.

Metzinger, T. (2004). Being no one: The self-model theory of subjectivity. MIT Press.

Metzinger, T. (2017). The problem of mental action. Predictive control without sensory sheets. En T. Metzinger & W. Wiese (Eds.) Philosophy and predictive processing. MIND Group.

Palmer, C. J., Paton, B., Kirkovski, M., Enticott, P. G. & Hohwy, J. (2015). Context sensitivity in action decreases along the autism spectrum: A predictive processing perspective. Proceedings of the Royal Society of London B: Biological Sciences, 282 (1802). https://dx.doi.org/10.1098/rspb.2014.1557

Prinz, W. (1990). A common coding approach to perception and action. En O. Neumann & W. Prinz (Eds.) Relationships between perception and action (pp. 167–201). Heidelberg: Springer.

Quadt, L. (2017). Action-oriented predictive processing and social cognition. En T. Metzinger & W. Wiese (Eds.) Philosophy and predictive processing. MIND Group.

Seth, A. K. (2015). The cybernetic Bayesian brain: From interoceptive inference to sensorimotor contingencies. En T. Metzinger & J. M. Windt (Eds.) Open MIND. MIND Group. https://dx.doi.org/10.15502/9783958570108.

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