What Simulations Teach Us About Ordinary Objects

Arthur C. Schwaninger 1
  • 1 University of Zurich, , Zurich, Switzerland


Under the label of scientific metaphysics, many naturalist metaphysicians are moving away from a priori conceptual analysis and instead seek scientific explanations that will help bring forward a unified understanding of the world. This paper first reviews how our classical assumptions about ordinary objects fail to be true in light of quantum mechanics. The paper then explores how our experiences of ordinary objects arise by reflecting on how our neural system operates algorithmically. Contemporary models and simulations in computational neuroscience are shown to provide a theoretical framework that does not conflict with existing fundamental physical theories, and nonetheless helps us make sense of the manifest image. It is argued that we must largely explain how the manifest image arises in algorithmic terms, so that we can pursue a metaphysics about ordinary objects that is scientifically well founded.

If the inline PDF is not rendering correctly, you can download the PDF file here.

  • Austin, John Langshaw. Sense and Sensibilia. Oxford University Press, 1962.

  • Bengio, Yoshua, Benjamin Scellier, Olexa Bilaniuk, Joao Sacramento, and Walter Senn. “Feedforward Initialization for Fast Inference of Deep Generative Networks Is Biologically Plausible.” ArXiv Preprint ArXiv:1606.01651, 2016.

  • Benovsky, Jiri. Eliminativism, Objects, and Persons: The Virtues of Non-Existence. 1 [edition]. Routledge Studies in Metaphysics 13. New York: Taylor & Francis, 2018.

  • Berkes, Pietro, and Gergő Orbán. “Spontaneous Cortical Activity Reveals Hallmarks of an Optimal Internal Model of the Environment.” Science 331, no. 6013 (January 7, 2011): 83–88.

  • Brown, Jason W. “Foundations of Cognitive Metaphysics.” Process Studies 27, no. 1 (1998): 79–92.

  • Chen, Liang-Chieh, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L. Yuille. “Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs.” ArXiv:1412.7062 [Cs], December 22, 2014. http://arxiv.org/abs/1412.7062.

  • Clark, Andy. “Whatever next? Predictive Brains, Situated Agents, and the Future of Cognitive Science.” Behavioral and Brain Sciences 36, no. 03 (June 2013): 181–204.

  • Decock, Lieven. “Cognitive Metaphysics.” Frontiers in Psychology 9: 1700, (2018).

  • Dennett, Daniel C. “Kinds of Things—Towards a Bestiary of the Manifest Image.” In Scientific Metaphysics, edited by Don Ross, James Ladyman, and Harold Kincaid. Oxford University Press, 2013.

  • Dennett, Daniel C. “Real Patterns.” The Journal of Philosophy 88, no. 1 (1991): 27–51.

  • Downing, Lisa. “George Berkeley.” In Stanford Encyclopedia of Philosophy, edited by Edward N. Zalta, 17. Winter 2018 Edition, 2004. https://plato.stanford.edu/archives/win2018/entries/berkeley/.

  • Esfeld, Michael. “Holism in Cartesianism and in Today’s Philosophy of Physics.” Journal for General Philosophy of Science 30 (1999): 20.

  • Esfeld, Michael. “Quantum Holism and the Philosophy of Mind.” Journal of Consciousness Studies 6, no. 1 (1999).

  • French, Steven, and Michael Redhead. “Quantum Physics and the Identity of Indiscernibles.” The British Journal for the Philosophy of Science 39, no. 2 (1988): 233–46.

  • Friston, Karl J., and Klaas E. Stephan. “Free-Energy and the Brain.” Synthese 159, no. 3 (November 12, 2007): 417–58.

  • Gatys, Leon A., Alexander S. Ecker, Matthias Bethge, Aaron Hertzmann, and Eli Shechtman. “Controlling Perceptual Factors in Neural Style Transfer.” ArXiv:1611.07865 [Cs], November 23, 2016.

  • Goodfellow, Ian. “NIPS 2016 Tutorial: Generative Adversarial Networks.” ArXiv Preprint ArXiv:1701.00160, 2016.

  • Goodfellow, Ian, Yoshua Bengio, and Aaron Courville. Deep Learning. Adaptive Computation and Machine Learning. Cambridge, Massachusetts London, England: The MIT Press, 2016.

  • Goodfellow, Ian, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. “Generative Adversarial Nets.” In Advances in Neural Information Processing Systems, 2672–2680, 2014.

  • Gribbin, John. In Search of Schrödinger’s Cat - Quantum Physics and Reality. New York: Bantam Books, 1984.

  • Harman, Graham. “I Am Also of the Opinion That Materialism Must Be Destroyed.” Environment and Planning D: Society and Space 28, no. 5 (October 2010): 772–90.

  • Heller, Mark. The Ontology of Physical Objects: Four-Dimensional Hunks of Matter. New York: Cambridge University Press, 1990.

  • Hinton, Geoffrey, and Terrence J Sejnowski. “Learning and Relearning in Boltzmann Machines.” Parallel Distributed Processing: Explorations in the Microstructure of Cognition 1, no. 282–317 (1986): 2.

  • Hofweber, Thomas. “Empirical Evidence and the Metaphysics of Ordinary Objects.” In The Nature of Ordinary Objects, edited by Javier Cumpa and Bill Brewer, 1st ed., 27–47. Cambridge University Press, 2019.

  • Hohwy, Jakob. The Predictive Mind. First edition. Oxford, United Kingdom; New York, NY, United States of America: Oxford University Press, 2013.

  • Howard, Don. “Holism, Separability, and the Metaphysical Implications of the Bell Experiments.” In Philosophical Consequences of Quantum Theory: Reflections on Bell’s Theorem, edited by James Cushing and Ernan McMullin. Notre Dame, Indiana: University of Notre Dame Press, 1989.

  • Inwagen, Peter van. “Being, Existence, and Ontological Commitment.” In Metametaphysics: New Essays on the Foundations of Ontology, edited by David Chalmers, David Manley, and Ryan Wasserman. Oxford University Press, 2009.

  • Inwagen, Peter van. Existence: Essays in Ontology. Cambridge University Press, 2014.

  • Karras, Tero, Samuli Laine, and Timo Aila. “A Style-Based Generator Architecture for Generative Adversarial Networks.” ArXiv:1812.04948 [Cs, Stat], December 12, 2018. http://arxiv.org/abs/1812.04948.

  • Korman, Daniel Z., and Dana Zemack. Objects: Nothing out of the Ordinary. First edition. Oxford, United Kingdom; New York, NY: Oxford University Press, 2015.

  • Ladyman, James, and Don Ross. Every Thing Must Go: Metaphysics Naturalized. Oxford; New York: Oxford University Press, 2007.

  • Lewis, David K. Parts of Classes. Oxford, UK; Cambridge, Mass., USA: B. Blackwell, 1991.

  • Maudlin, Tim. “Part and Whole in Quantum Mechanics.” In Interpreting Bodies, edited by Elena Castellani, 46–60. Princeton University Press, 1998.

  • McDonough, Jeffrey K. “Berkeley on Ordinary Objects.” In The Bloomsbury Companion to Berkeley, edited by Bertil Belfrage and Richard Brook, 14. Bloomsbury Academic, 2017.

  • Merricks, Trenton. Objects and Persons. New York: Oxford University Press, 2001.

  • Oppenheim, Paul, and Hilary Putnam. “Unity of Science as a Working Hypothesis,” 1958.

  • Petrovici, Mihai Alexandru. Form Versus Function: Theory and Models for Neuronal Substrates. Springer Theses. Cham: Springer International Publishing, 2016.

  • Quine, W. V. Ontological Relativity: And Other Essays. The John Dewey Essays in Philosophy, no. 1. New York: Columbia University Press, 1969.

  • Radford, Alec, Luke Metz, and Soumith Chintala. “Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks.” ArXiv Preprint ArXiv:1511.06434, 2015. https://arxiv.org/abs/1511.06434.

  • Rao, Rajesh PN, and Dana H. Ballard. “Predictive Coding in the Visual Cortex: A Functional Interpretation of Some Extra-Classical Receptive-Field Effects.” Nature Neuroscience 2, no. 1 (1999): 79–87.

  • Rescher, Nicholas. Process Philosophy: A Survey of Basic Issues. University of Pittsburgh Pre, 2000.

  • Rosenberg, Alex. The Atheist’s Guide to Reality: Enjoying Life without Illusions. WW Norton & Company, 2011.

  • Sacramento, João, Rui Ponte Costa, Yoshua Bengio, and Walter Senn. “Dendritic Cortical Microcircuits Approximate the Backpropagation Algorithm,” n.d., 12.

  • Sacramento, João, Rui Ponte Costa, Yoshua Bengio, and Walter Senn. “Dendritic Error Backpropagation in Deep Cortical Microcircuits.” ArXiv:1801.00062 [Cs, q-Bio], December 29, 2017. http://arxiv.org/abs/1801.00062.

  • Scellier, Benjamin, and Yoshua Bengio. “Equilibrium Propagation: Bridging the Gap between Energy-Based Models and Backpropagation.” Frontiers in Computational Neuroscience 11 (May 4, 2017).

  • Schrödinger, E. “Die gegenwärtige Situation in der Quantenmechanik.” Naturwissenschaften 23, no. 48 (November 1, 1935): 807–12.

  • Sellars, Wilfrid. Science, Perception, and Reality, Ridgeview Publishing Company, 1963.

  • Smith, Brian Cantwell. On the Origin of Objects. Cambridge, MA: MIT Press, 1996.

  • Smith, Brian Cantwell. “Reply to Dennett.” In Philosophy of Mental Representation, edited by Hugh Clapin, 237–65, 2002.

  • Spratling, M. W. “Image Segmentation Using a Sparse Coding Model of Cortical Area V1.” IEEE Transactions on Image Processing 22, no. 4 (April 2013): 1631–43.

  • Stebbing, Lizzie Susan. Philosophy and the Physicists. New York: Dover Publications, 1937.

  • Strawson, Peter Frederick. Individuals: An Essay in Descriptive Metaphysics. London: Methuen, 1959.

  • Stroud, Barry. “Transcendental Arguments.” The Journal of Philosophy 65, no. 9 (1968): 241–56.

  • Swanson, Link R. “The Predictive Processing Paradigm Has Roots in Kant.” Frontiers in Systems Neuroscience 10 (October 10, 2016).

  • Thomasson, Amie L. “Ontological Minimalism.” American Philosophical Quarterly 38, no. 4 (2001): 319–31.

  • Wiese, Wanja, and Thomas Metzinger. “Vanilla PP for Philosophers: A Primer on Predictive Processing,” 2017, 18.

  • Wolpert, David H, and William G Macready. “No Free Lunch Theorems for Optimization.” IEEE Transactions on Evolutionary Computation 1, no. 1 (1997): 67–82.

  • Zhang, Hui, Jason E. Fritts, and Sally A. Goldman. “Image Segmentation Evaluation: A Survey of Unsupervised Methods.” Computer Vision and Image Understanding 110, no. 2 (May 1, 2008): 260–80.


Journal + Issues

Open Philosophy is an international Open Access, peer-reviewed academic journal covering all areas of philosophy. The objective of Open Philosophy is to foster free exchange of ideas and provide an appropriate platform for presenting, discussing and disseminating new concepts, current trends, theoretical developments and research findings related to the broadest philosophical spectrum.