Unification Strategies in Cognitive Science

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Cognitive science is an interdisciplinary conglomerate of various research fields and disciplines, which increases the risk of fragmentation of cognitive theories. However, while most previous work has focused on theoretical integration, some kinds of integration may turn out to be monstrous, or result in superficially lumped and unrelated bodies of knowledge. In this paper, I distinguish theoretical integration from theoretical unification, and propose some analyses of theoretical unification dimensions. Moreover, two research strategies that are supposed to lead to unification are analyzed in terms of the mechanistic account of explanation. Finally, I argue that theoretical unification is not an absolute requirement from the mechanistic perspective, and that strategies aiming at unification may be premature in fields where there are multiple conflicting explanatory models.

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  • Anderson J. R. (2007). How Can the Mind Occur in the Physical Universe? Oxford: Oxford University Press.

  • Arbib M. A. (2005). From monkey-like action recognition to human language: An evolutionary framework for neurolinguistics. Behavioral and Brain Sciences 28(2) 105-24-67. https://doi.org/10.1017/S0140525X05000038

  • Arbib M. A. (2012). How the brain got language: the mirror system hypothesis. New York: Oxford University Press.

  • Baddeley A. D. (2000). The episodic buffer: A new component of working memory? Trends in Cognitive Sciences 4(11) 417-423. https://doi.org/10.1016/S1364-6613(00)01538-2

  • Baddeley A. D. & Hitch G. (1974). Working Memory. In G. H. Bower (Ed.) Psychology of Learning and Motivation (Vol. 8 pp. 47-89). New York / San Francisco / London: Academic Press. https://doi.org/10.1016/S0079-7421(08)60452-1

  • Bechtel W. (1986). The Nature of Scientific Integration. In W. Bechtel (Ed.) Integrating Scientific Disciplines (pp. 3-52). Dordrecht: Springer Netherlands. https://doi.org/10.1007/978-94-010-9435-1 1

  • Bechtel W. (2008). Mental Mechanisms. New York: Routledge (Taylor & Francis Group).

  • Bechtel W. (2016). Investigating neural representations: the tale of place cells. Synthese 193(5) 1287-1321. https://doi.org/10.1007/s11229-014-0480-8

  • Bechtel W. & McCauley R. N. (1999). Heuristic identity theory (or back to the future): The mind-body problem against the background of research strategies in cognitive neuroscience. In Proceedings of the 21st Annual Meeting of the Cognitive Science Society (pp. 67-72). Mahwah NJ: Erlbaum.

  • Benhamou S. (1996). No evidence for cognitive mapping in rats. Animal Behaviour 52(1) 201-212.

  • Bickle J. (1998). Psychoneural reduction the new wave. Cambridge Mass.: MIT Press.

  • BooneW. & Piccinini G. (2015). The cognitive neuroscience revolution. Synthese. https://doi.org/10.1007/s11229-015-0783-4

  • Busemeyer J. R. & Diederich A. (2010). Cognitive modeling. Los Angeles: Sage.

  • Byrne M. D. (2012). Unified theories of cognition.Wiley Interdisciplinary Reviews: Cognitive Science 3(4) 431-438. https://doi.org/10.1002/wcs.1180

  • Chaitin G. J. (1987). Algorithmic information theory. Cambridge [Cambridgeshire]; New York: Cambridge University Press.

  • Churchland P. M. (1985). Reduction qualia and the direct introspection of brain states. The Journal of Philosophy 82(1) 8-28.

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

  • Clark A. (2016). Surfing uncertainty: prediction action and the embodied mind.

  • Cooper R. P. (2007). The Role of Falsification in the Development of Cognitive Architectures: Insights from a Lakatosian Analysis. Cognitive Science 31(3) 509-533. https://doi.org/10.1080/15326900701326592

  • Cosmides L. & Tooby J. (1987). From Evolution to Behavior: Evolutionary Psychology as the Missing Link. In J. Dupre (Ed.) The Latest on the Best. Essays on Evolution and Optimality (pp. 277-303). Cambridge Mass.: MIT Press.

  • Craver C. F. (2002). Interlevel experiments and multilevel mechanisms in the neuroscience of memory. Philosophy of Science 69(S3) 83-97.

  • Craver C. F. (2007a). Explaining the Brain. Mechanisms and the mosaic unity of neuroscience. Oxford: Oxford University Press.

  • Craver C. F. (2007b). Explaining the Brain. Mechanisms and the mosaic unity of neuroscience. Oxford: Oxford University Press.

  • Craver C. F. & Darden L. (2013). In search of mechanisms: discoveries across the life sciences.

  • Cummins R. (1984). Functional analysis. Conceptual Issues in Evolutionary Biology: An Anthology.

  • Cummins R. (2000). “How does it work” versus “what are the laws?”: Two conceptions of psychological explanation. In F. Keil & R. A. Wilson (Eds.) Explanation and Cognition (pp. 117-145). Cambridge Mass.: MIT Press.

  • Danks D. (2014). Unifying the mind: cognitive representations as graphical models. Cambridge Mass.: MIT Press.

  • Darden L. & Maull N. (1977). Interfield Theories. Philosophy of Science 44(1) 43-64.

  • Dawson M. (1998). Understanding cognitive science. Malden Mass.: Blackwell.

  • Derdikman D. & Moser E. I. (2010). A manifold of spatial maps in the brain. Trends in Cognitive Sciences 14(12) 561-9. https://doi.org/10.1016/j.tics.2010.09.004

  • di Pellegrino G. Fadiga L. Fogassi L. Gallese V. & Rizzolatti G. (1992). Understanding motor events: a neurophysiological study. Experimental Brain Research 91(1) 176-80.

  • Eliasmith C. (2013). How to build the brain: a neural architecture for biological cognition. New York: Oxford University Press.

  • Eliasmith C. Stewart T. C. Choo X. Bekolay T. DeWolf T. Tang Y. ... Rasmussen D. (2012). A Large-Scale Model of the Functioning Brain. Science 338(6111) 1202-1205. https://doi.org/10.1126/science.1225266

  • Fodor J. A. (1968). Psychological explanation: an introduction to the philosophy of psychology. New York: Random House.

  • Forster M. & Sober E. (1994). How to Tell When Simpler More Unified or Less Ad Hoc Theories will Provide More Accurate Predictions. The British Journal for the Philosophy of Science 45(1) 1-35. https://doi.org/10.1093/bjps/45.1.1

  • Gallese V. (2003). The Roots of Empathy: The Shared Manifold Hypothesis and the Neural Basis of Intersubjectivity. Psychopathology 36(4) 171-180. https://doi.org/10.1159/000072786

  • Glennan S. S. (2002). Rethinking Mechanistic Explanation. Philosophy of Science 69(S3) S342-S353. https://doi.org/10.1086/341857

  • Goodman N. (1961). Safety Strength Simplicity. Philosophy of Science 28(2) 150-151. https://doi.org/10.1086/287795

  • Hempel C. & Oppenheim P. (1948). Studies in the Logic of Explanation. Philosophy of Science 15(2) 135-175.

  • Hensel W. M. (2013). On Reduction and Interfield Integration in Neuroscience. In M. Miłkowski & K. Talmont-Kamiński (Eds.) Regarding the Mind Naturally: Naturalist Approaches to the Sciences of the Mental (pp. 167-181). Newcastle upon Tyne: Cambridge Scholars Publishing.

  • Hickok G. (2014). The myth of mirror neurons: the real neuroscience of communication and cognition. New York: WW Norton.

  • Hochstein E. (2015). One mechanism many models: a distributed theory of mechanistic explanation. Synthese. https://doi.org/10.1007/s11229-015-0844-8

  • Hooker C. A. (1981a). Towards a General Theory of Reduction. Part I: Historical and Scientific Setting. Dialogue 20(1) 38-59. https://doi.org/10.1017/S0012217300023088

  • Hooker C. A. (1981b). Towards a General Theory of Reduction. Part II: Identity in Reduction. Dialogue 20(2) 201-236. https://doi.org/10.1017/S0012217300023301

  • Hooker C. A. (1981c). Towards a General Theory of Reduction. Part III: Cross- Categorical Reduction. Dialogue 20(3) 496-529. https://doi.org/10.1017/S0012217300023593

  • Hora J. & Campos P. (2015). A review of performance criteria to validate simulation models. Expert Systems 32(5) 578-595. https://doi.org/10.1111/exsy.12111

  • Kitcher P. (1989). Explanatory Unification and the Causal Structure of the World. In P. Kitcher & W. C. Salmon (Eds.) Scientific Explanation (Vol. 505 pp. 410-505). Minneapolis: University of Minnesota Press.

  • Kohler E. Keysers C. Umiltà M. A. Fogassi L. Gallese V. & Rizzolatti G. (2002). Hearing sounds understanding actions: action representation in mirror neurons. Science (New York N.Y.) 297(5582) 846-8. https://doi.org/10.1126/science.1070311

  • Laird J. E. Newell A. & Rosenbloom P. S. (1987). SOAR: An architecture for general intelligence. Artificial Intelligence 33(1) 1-64. https://doi.org/10.1016/0004-3702(87)90050-6

  • Li M. & Vitanyi P. (1993). An Introduction to Kolmogorov Complexity and Its Applications. New York Berlin Heidelberg: Springer-Verlag.

  • McCulloch W. S. & Pitts W. (1943). A Logical Calculus of the Ideas Immanent in Nervous Activity. Bulletin of Mathematical Biophysics 5 115-133.

  • Metta G. Natale L. Nori F. Sandini G. Vernon D. Fadiga L. ... Montesano L. (2010). The iCub humanoid robot: An open-systems platform for research in cognitive development. Neural Networks 23(8) 1125-1134. https://doi.org/10.1016/j.neunet.2010.08.010

  • MiłkowskiM. (2013). Explaining the Computational Mind. CambridgeMass.:MIT Press.

  • Morse A. F. Herrera C. Clowes R. Montebelli A. & Ziemke T. (2011). The role of robotic modelling in cognitive science. New Ideas in Psychology 29(3) 312-324. https://doi.org/10.1016/j.newideapsych.2011.02.001

  • Mouras H. Stol´eru S. Moulier V. P´el´egrini-Issac M. Rouxel R. Grandjean B. ... Bittoun J. (2008). Activation of mirror-neuron system by erotic video clips predicts degree of induced erection: an fMRI study. NeuroImage 42 1142-1150. https://doi.org/10.1016/j.neuroimage.2008.05.051

  • Newell A. (1973). You can’t play 20 questions with nature and win: Projective comments on the papers of this symposium. In W. G. Chase (Ed.) Visual information processing (pp. 283-308). New York: Academic Press.

  • Newell A. (1990). Unified Theories of Cognition. Cambridge Mass. and London: Harvard University Press.

  • O’Reilly R. C. & Munakata Y. (2000). Computational Explorations in Cognitive Neuroscience. Understanding the Mind by Simulating the Brain. Cambridge Mass.: MIT Press.

  • Piccinini G. & Craver C. F. (2011). Integrating psychology and neuroscience: functional analyses as mechanism sketches. Synthese 183(3) 283-311. https://doi.org/10.1007/s11229-011-9898-4

  • Ponseti J. Bosinski H. A. Wolff S. Peller M. Jansen O. Mehdorn H. M. ... Siebner H. R. (2006). A functional endophenotype for sexual orientation in humans. NeuroImage 33(3) 825-833. https://doi.org/10.1016/j.neuroimage.2006.08.002

  • Popper K. R. (1959). The logic of scientific discovery. New Yorker The. Hutchinson.

  • Quine W. V. (1948). On What There Is. The Review of Metaphysics 2(5) 21-38.

  • Ramón y Cajal S. (1990). New ideas on the structure of the nervous system in man and vertebrates. (L. W. Swanson Trans.). Cambridge Mass.: MIT Press.

  • Richardson R. C. (2007). Evolutionary Psychology as Maladapted Psychology. Cambridge Mass.: MIT Press.

  • Rizzolatti G. & Craighero L. (2004). The mirror-neuron system. Annual Review of Neuroscience 27 169-92. https://doi.org/10.1146/annurev.neuro.27.070203.144230

  • Roberts S. & Pashler H. (2000). How persuasive is a good fit? A comment on theory testing. Psychological Review 107(2) 358.

  • Salmon W. C. (1998). Causality and explanation. Oxford University Press USA.

  • Schaffner K. F. (1993). Discovery and explanation in biology and medicine. Chicago: University of Chicago Press.

  • Schurz G. (1991). Relevant Deduction: From Solving Paradoxes Towards a General Theory. Erkenntnis 35 391-437. https://doi.org/10.1007/BF00388295

  • Thagard P. (2000). Coherence in thought and action. Cambridge Mass.: MIT Press.

  • Thagard P. (2007). Coherence Truth and the Development of Scientific Knowledge. Philosophy of Science 74 28-47.

  • Van Orden G. C. & Kloos H. (2003). The Module Mistake. Cortex 39(1) 164-166. https://doi.org/10.1016/S0010-9452(08)70092-3

  • Votsis I. (2015). Unification: Not Just a Thing of Beauty. THEORIA. An International Journal for Theory History and Foundations of Science 30(1) 97. https://doi.org/10.1387/theoria.12695

  • Weisberg M. (2006). Robustness Analysis. Philosophy of Science 73(5) 730-742. https://doi.org/10.1086/518628

  • Zenil H. (2010). Compression-based investigation of the dynamical properties of cellular automata and other systems. Journal of Complex Systems 19(1).

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