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Explicating Top-Down Causation Using Networks and Dynamics

Published online by Cambridge University Press:  01 January 2022

William Bechtel
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Abstract

In many fields in the life sciences investigators refer to downward or top-down causal effects. Craver and I defended the view that such cases should be understood in terms of a constitution relation between levels in a mechanism and intralevel causal relations (occurring at any level). We did not, however, specify when entities constitute a higher-level mechanism. In this article I appeal to graph-theoretic representations of networks, now widely employed in systems biology and neuroscience, and associate mechanisms with modules that exhibit high clustering. As a result of interconnections within clusters, mechanisms often exhibit complex dynamic behaviors that constrain how individual components respond to external inputs, a central feature of top-down causation.

Type
Research Article
Information
Philosophy of Science , Volume 84 , Issue 2 , April 2017 , pp. 253 - 274
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

†

I thank three anonymous referees for this journal for their very helpful comments and suggestions. I also thank John Norton and visiting fellows at the Center for Philosophy of Science at the University of Pittsburgh in 2014–15, especially Sara Green, Raphael Scholl, and Maria Serban, for their spirited discussion of an earlier draft of this paper. Likewise, I thank members of the audience at the Workshop on Levels of Organization, Causality, and Top-Down Relations sponsored by the IAS Research Centre for Life, Mind, and Society, University at the Basque Country, San Sebastian, in June 2015, especially Leonardo Bich, Alvaro Moreno, and Kepa Ruiz-Mirazo, for valuable discussion at and after the workshop. Finally, I thank Jason Winning for many productive discussions concerning constraints and mechanism.

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