Why do you fear the bogeyman? An embodied predictive coding model of perceptual inference
Tóm tắt
Why are we scared by nonperceptual entities such as the bogeyman, and why does the bogeyman only visit us during the night? Why does hearing a window squeaking in the night suggest to us the unlikely idea of a thief or a killer? And why is this more likely to happen after watching a horror movie? To answer these and similar questions, we need to put mind and body together again and consider the embodied nature of perceptual and cognitive inference. Predictive coding provides a general framework for perceptual inference; I propose to extend it by including interoceptive and bodily information. The resulting embodied predictive coding inference permits one to compare alternative hypotheses (e.g., is the sound I hear generated by a thief or the wind?) using the same inferential scheme as in predictive coding, but using both sensory and interoceptive information as evidence, rather than just considering sensory events. If you hear a window squeaking in the night after watching a horror movie, you may consider plausible a very unlikely hypothesis (e.g., a thief, or even the bogeyman) because it explains both what you sense (e.g., the window squeaking in the night) and how you feel (e.g., your high heart rate). The good news is that the inference that I propose is fully rational and gives minds and bodies equal dignity. The bad news is that it also gives an embodiment to the bogeyman, and a reason to fear it.
Tài liệu tham khảo
Anderson, A. K., & Phelps, E. A. (2001). Lesions of the human amygdala impair enhanced perception of emotionally salient events. Nature, 411, 305–309. doi:10.1038/35077083
Barsalou, L. W. (2008). Grounded cognition. Annual Review of Psychology, 59, 617–645. doi:10.1146/annurev.psych.59.103006.093639
Carhart-Harris, R. L., & Friston, K. J. (2010). The default-mode, ego-functions and free-energy: A neurobiological account of Freudian ideas. Brain, 133, 1265–1283. doi:10.1093/brain/awq010
Clark, A. (2013). Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and Brain Sciences, 36, 181–204. doi:10.1017/S0140525X12000477
Damasio, A. (2000). The feeling of what happens: Body and emotion in the making of consciousness. New York, NY: Harcourt Brace.
Dayan, P., Hinton, G. E., Neal, R. M., & Zemel, R. S. (1995). The Helmholtz machine. Neural Computation, 7, 889–904.
Ernst, M. O., & Bülthoff, H. H. (2004). Merging the senses into a robust percept. Trends in Cognitive Sciences, 8, 162–169. doi:10.1016/j.tics.2004.02.002
Feldman, H., & Friston, K. J. (2010). Attention, uncertainty, and free-energy. Frontiers in Human Neuroscience, 4, 215. doi:10.3389/fnhum.2010.00215
Friston, K. (2005). A theory of cortical responses. Philosophical Transactions of the Royal Society B, 360, 815–836. doi:10.1098/rstb.2005.1622
Friston, K. (2010). The free-energy principle: A unified brain theory? Nature Reviews Neuroscience, 11, 127–138. doi:10.1038/nrn2787
Friston, K., Adams, R. A., Perrinet, L., & Breakspear, M. (2012). Perceptions as hypotheses: Saccades as experiments. Frontiers in Psychology, 3, 151. doi:10.3389/fpsyg.2012.00151
Friston, K., Daunizeau, J., & Kiebel, S. J. (2009). Reinforcement learning or active inference? PLoS ONE, 4, e6421. doi:10.1371/journal.pone.0006421
Garrett, A. S., & Maddock, R. J. (2001). Time course of the subjective emotional response to aversive pictures: Relevance to fMRI studies. Psychiatry Research, 108, 39–48.
Grau-Moya, J., Hez, E., Pezzulo, G., & Braun, D. A. (2013). The effect of model uncertainty on cooperation in sensorimotor interactions. Journal of the Royal Society Interface, 10, 10130554. doi:10.1098/rsif.2013.0554
Grau-Moya, J., Ortega, P. A., & Braun, D. A. (2012). Risk-sensitivity in Bayesian sensorimotor integration. PLoS Computational Biology, 8, e1002698. doi:10.1371/journal.pcbi.1002698
Grush, R. (2004). The emulation theory of representation: Motor control, imagery, and perception. Behavioral and Brain Sciences, 27, 377–396.
Halloy, A. (2012). Gods in the Flesh: Learning Emotions in the. Xangô Possession Cult (Brazil). Ethnos: Journal of Anthropology, 77, 177-202. doi:10.1080/00141844.2011.586465
Helmholtz, H. von. (1962). Concerning the perceptions in general. In J. P. C. Southall (Ed. and Trans.), Helmholtz’s Treatise on physiological optics (Vol. 3). New York, NY: Dover. (Original work published 1866).
Hinton, G. E. (2007a). Learning multiple layers of representation. Trends in Cognitive Sciences, 11, 428–434. doi:10.1016/j.tics.2007.09.004
Hinton, G. E. (2007b). To recognize shapes, first learn to generate images. Progress in Brain Research, 165, 535–547. doi:10.1016/S0079-6123(06)65034-6
Hirstein, W., & Ramachandran, V. S. (1997). Capgras syndrome: A novel probe for understanding the neural representation of the identity and familiarity of persons. Proceedings of the Royal Society B, 264, 437–444. doi:10.1098/rspb.1997.0062
Hohwy, J., Roepstorff, A., & Friston, K. (2008). Predictive coding explains binocular rivalry: An epistemological review. Cognition, 108, 687–701. doi:10.1016/j.cognition.2008.05.010
James, W. (1890). The principles of psychology. New York, NY: Henry Holt.
Kahneman, D. (2003). A perspective on judgment and choice: Mapping bounded rationality. American Psychologist, 58, 697–720. doi:10.1037/0003-066X.58.9.697
Kiebel, S. J., Daunizeau, J., & Friston, K. J. (2008). A hierarchy of time-scales and the brain. PLoS Computational Biology, 4, e1000209. doi:10.1371/journal.pcbi.1000209
Koller, D., & Friedman, N. (2009). Probabilistic graphical models: Principles and techniques. Cambridge, MA: MIT Press.
Machens, C. K., Gollisch, T., Kolesnikova, O., & Herz, A. V. M. (2005). Testing the efficiency of sensory coding with optimal stimulus ensembles. Neuron, 47, 447–456. doi:10.1016/j.neuron.2005.06.015
Montague, P. R., Dolan, R. J., Friston, K. J., & Dayan, P. (2012). Computational psychiatry. Trends in Cognitive Sciences, 16, 72–80. doi:10.1016/j.tics.2011.11.018
Montague, P. R., & King-Casas, B. (2007). Efficient statistics, common currencies and the problem of reward-harvesting. Trends in Cognitive Sciences, 11, 514–519. doi:10.1016/j.tics.2007.10.002
Pezzulo, G. (2008). Coordinating with the future: The anticipatory nature of representation. Minds and Machines, 18, 179–225. doi:10.1007/s11023-008-9095-5
Pezzulo, G. (2011). Grounding procedural and declarative knowledge in sensorimotor anticipation. Mind and Language, 26, 78–114.
Pezzulo, G. (2012). An active inference view of cognitive control. Frontiers in Theoretical and Philosophical Psychology, 3, 478. doi:10.3389/fpsyg.2012.00478
Pezzulo, G., Barsalou, L. W., Cangelosi, A., Fischer, M. H., McRae, K., & Spivey, M. J. (2011). The mechanics of embodiment: A dialog on embodiment and computational modeling. Frontiers in Cognition, 2(5), 1–21. doi:10.3389/fpsyg.2011.00005
Pezzulo, G., Barsalou, L. W., Cangelosi, A., Fischer, M. H., McRae, K., & Spivey, M. J. (2013). Computational grounded cognition: A new alliance between grounded cognition and computational modeling. Frontiers in Psychology, 3, 612. doi:10.3389/fpsyg.2012.00612
Pezzulo, G., & Castelfranchi, C. (2009). Thinking as the control of imagination: a conceptual framework for goal-directed systems. Psychological Research, 73, 559–577.
Rao, R. P. N., & Ballard, D. H. (1999). Predictive coding in the visual cortex: A functional interpretation of some extra-classical receptive-field effects. Nature Neuroscience, 2, 79–87. doi:10.1038/4580
Roy, D. (2005). Semiotic schemas: A framework for grounding language in action and perception. Artificial Intelligence, 167, 170–205.
Seth, A. K., Suzuki, K., & Critchley, H. D. (2012). An interoceptive predictive coding model of conscious presence. Frontiers in Psychology, 2, 395. doi:10.3389/fpsyg.2011.00395
Spivey, M. (2007). The continuity of mind. Oxford, UK: Oxford University Press.
Stanovich, K. E., & West, R. F. (2000). Individual differences in reasoning: Implications for the rationality debate? Behavioral and Brain Sciences, 23, 645–665. disc. 665–726.
Tenenbaum, J. B., Kemp, C., Griffiths, T. L., & Goodman, N. D. (2011). How to grow a mind: Statistics, structure, and abstraction. Science, 331, 1279–1285. doi:10.1126/science.1192788
Wacongne, C., Changeux, J.-P., & Dehaene, S. (2012). A neuronal model of predictive coding accounting for the mismatch negativity. Journal of Neuroscience, 32, 3665–3678. doi:10.1523/JNEUROSCI.5003-11.2012
Wilson-Mendenhall, C. D., Barrett, L. F., Simmons, W. K., & Barsalou, L. W. (2011). Grounding emotion in situated conceptualization. Neuropsychologia, 49, 1105–1127. doi:10.1016/j.neuropsychologia.2010.12.032