View By Topic:
- Explanation, evidence, and general philosophy of science
- Foundations of computational neuroscience
- Includes: Bayes, Dopamine, Free-energy principle, Neroeconomics, RL, Large-scale brain simulations, Representationalism
- Social norms and moral psychology
(33) Colombo, M. (online first). Bayesian cognitive science, predictive brains, and the nativism debate. Synthese.
(32) Wright, C., Colombo, M., & Beard, A. (2017). HIT and Brain Reward Function: A Case of Mistaken Identity (Theory). History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences. 64, 28-40. [preprint]
(30) Colombo, M., & Hartmann, S. (2017). Bayesian Cognitive Science, Unification, and Explanation. The British Journal for Philosophy of Science, 68, 451-484 [preprint]
(27) Colombo, M. (2017). Social motivation in computational neuroscience. Or if brains are prediction machines, then the Humean theory of motivation is false. In J. Kiverstein (Ed.) Routledge Handbook of Philosophy of the Social Mind (pp. 320-340). New York: Routledge. [preprint]
(26) Colombo, M. & Wright, C.D. (2017). Explanatory Pluralism: An Unrewarding Prediction Error for Free Energy Theorists. Brain and Cognition, 112, 3-12. [preprint]
(25) Colombo, M. (2017). Why Build a Virtual Brain? Large-Scale Neural Simulations as Jump Start for Cognitive Computing. Journal of Experimental & Theoretical Artificial Intelligence, 29, 361-370. [preprint]
(21) Colombo, M. (2015). Why Build a Virtual Brain? Large-scale Neural Simulations as Test-bed for Artificial Computing Systems. In D.C. Noelle, R. Dale, A.S. Warlaumont, J. Yoshimi, T. Matlock, C.D. Jennings, & P.P. Maglio (Eds.), Proceedings of the 37th Annual Conference of the Cognitive Science Society (pp. 429-34). Austin, TX: Cognitive Science Society. [preprint]
(20) Colombo, M. (2015). For a Few Neurons More. Tractability and Neurally-Informed Economic Modelling. The British Journal for Philosophy of Science, 66, 713-736.[preprint]
(18) Colombo, M., & Sprenger, J. (2014). The Predictive Mind and Chess-Playing. A Reply to Shand (2014). Analysis, 74, 603-608. [preprint]
(16) Colombo, M. (2014). Neural Representationalism, the Hard Problem of Content, and Vitiated Verdicts. A Reply to Hutto & Myin (2013). Phenomenology and the Cognitive Sciences, 13, 257-274. [preprint]
(15) Colombo, M. (2014). Explaining Social Norm Compliance. A Plea for Neural Representations. Phenomenology and the Cognitive Sciences, 13: 217-138. [preprint]
(14) Colombo, M. (2014). Deep and Beautiful. The Reward Prediction Error Hypothesis of Dopamine. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences, 45, 57-67. [preprint]
(10) Colombo, M. (2013). Moving Forward (and Beyond) the Modularity Debate. A Network Perspective. Philosophy of Science, 80, 356-377.[preprint]
(7) Colombo, M., & Seriès, P. (2012). Bayes in the Brain. On Bayesian Modelling in Neuroscience. The British Journal for Philosophy of Science, 63, 697-723. [preprint]
(6) Colombo, M. (2010). How ‘Authentic Intentionality’ can be enabled. A Neurocomputational Hypothesis. Minds and Machines, 20, 183-202. [preprint]
(5) Colombo, M. (2009). What Can Neuroscience Offer to Economics? Humana.Mente: Journal of Philosophical Studies, 10, 41-59. [Invited] [pdf]
(3) Colombo, M. (2009). Does Embeddedness Tell Against Computationalism? A Tale of Bees and Sea Hares. AISB09 Proceedings of the 2nd Symposium on Computing and Philosophy, 16-21.
(2) Colombo, M. (2008). No-Brainer Predictions. Predictive Models in the Ultimatum Game. Rerum Causae Journal of the LSE Philosophy Society, 1, 42-50. [pdf]
(1) Di Francesco, M., Motterlini, M., & Colombo, M. (2007). In search of the neurobiological basis of decision-making: Explanation, Reduction and Emergence. Functional Neurology, 22, 197-204. [Invited] [pdf]
