Abstract
In the last 20 years or so, since the publication of a seminal paper by Watts and Strogatz (Nature 393(6684):440–442, 1998), an interest in topological explanations (Huneman in Synthese 177:213–245, 2010) has spread like a wild fire over many areas of science, e.g. ecology, evolutionary biology, medicine, and cognitive neuroscience. The topological approach is still very young by all standards, and even within special sciences it still doesn’t have a single methodological programme that is applicable across all areas of science. That is why this special issue is important as a first systematic philosophical study of topological explanations and their relation to a well understood and widespread explanatory strategy, such as mechanistic one.
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References
Barabási, A. L., Gulbahce, N., & Loscalzo, J. (2011). Network medicine: A network-based approach to human disease. Nature Reviews Genetics, 12(1), 56–68.
Barabasi, A. L., & Oltvai, Z. N. (2004). Network biology: Understanding the cell’s functional organization. Nature Reviews Genetics, 5, 101–113.
Barabási, A. L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509–512.
Batterman, R. W. (2009). On the explanatory role of mathematics in empirical science. The British Journal for the Philosophy of Science, axp018.
Batterman, R. W. (2002). Asymptotics and the role of minimal models. The British Journal for the Philosophy of Science, 53(1), 21–38.
Bassett, D. S., & Bullmore, E. T. (2009). Human brain networks in health and disease. Current Opinion in Neurology, 22(4), 340.
Bechtel, W., & Richardson, R. C. (2010). Discovering complexity: Decomposition and localization as strategies in scientific research (2nd ed.). Cambridge, MA: MIT Press/Bradford Books.
Bokulich, A. (2011). How scientific models can explain. Synthese, 180(1), 33–45.
Bullmore, E., & Sporns, O. (2009). Complex brain networks: Graph theoretical analysis of structural and functional systems. Nature Reviews Neuroscience, 10(3), 186–198.
Craver, C. F. (2014). The ontic account of scientific explanation. In Explanation in the special sciences (pp. 27–52). Dordrecht: Springer.
Craver, C. F. (2007). Explaining the brain: Mechanisms and the mosaic unity of neuroscience. New York: Oxford University Press.
Craver, C., & Kaplan, D. M. (2011). The explanatory force of dynamical and mathematical models in neuroscience: A mechanistic perspective. Philosophy of Science, 78(4), 601–627.
Cupal, J., Kopp, S., & Stadler, P. F. (2000). RNA shape space topology. Artificial Life, 6(1), 3–23.
Huneman, P. (2010). Topological explanations and robustness in biological sciences. Synthese, 177, 213–245.
Jackson, F., & Pettit, P. (1990). Program explanation: A general perspective. Analysis, 50(2), 107–117.
Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67, 1–25.
Rosenberg, A. (2015). Making mechanism interesting. Synthese. doi:10.1007/s11229-015-0713-5.
Seung, S. H. (2012). Connectome: How the brain’s wiring makes us who we are. New York: Houghton Mifflin Harcourt Trade.
Sporns, O. (2012). Discovering the human connectome. Cambridge, MA: MIT Press.
Sporns, O., Tononi, G., & Kötter, R. (2005). The human connectome: A structural description of the human brain. PLoS Computational Biology, 1(4), e42.
Stadler, B. M., & Stadler, P. F. (2004). The topology of evolutionary biology. In Modelling in molecular biology (pp. 267–286). Berlin: Springer.
Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small-world’ networks. Nature, 393(6684), 440–442.
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Kostić, D. Mechanistic and topological explanations: an introduction. Synthese 195, 1–10 (2018). https://doi.org/10.1007/s11229-016-1257-z
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DOI: https://doi.org/10.1007/s11229-016-1257-z