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When Is a Brain Like the Planet?

Published online by Cambridge University Press:  01 January 2022

Clark Glymour
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Abstract

Time series of macroscopic quantities that are aggregates of microscopic quantities, with unknown one-many relations between macroscopic and microscopic states, are common in applied sciences, from economics to climate studies. When such time series of macroscopic quantities are claimed to be causal, the causal relations postulated are representable by a directed acyclic graph and associated probability distribution—sometimes called a dynamical Bayes net. Causal interpretations of such series imply claims that hypothetical manipulations of macroscopic variables have unambiguous effects on variables “downstream” in the graph, and such macroscopic variables may be predictably produced or altered even while particular microstates are not. This paper argues that such causal time series of macroscopic aggregates of microscopic processes are the appropriate model for mental causation.

Type
Research Article
Information
Philosophy of Science , Volume 74 , Issue 3 , July 2007 , pp. 330 - 346
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

‡

I am grateful to Jim Woodward, Michael Strevens, Elliott Sober, and John Campbell for valuable comments and corrections to a previous draft of this essay and to the participants in a conference on fMRI issues sponsored by the Rutgers Department of Philosophy in 2006, and especially to Steve Hanson, for stimulating discussions that caused substantial revisions in this essay. The graph of Figure 5 was obtained by Joseph Ramsey by applying a Bayesian search procedure, the Greedy Equivalence Search algorithm, implemented in the TETRAD IV program (http://www.phil.cmu.edu/projects/tetrad) to the lagged variables of unpublished data from Steve Hanson's laboratory. The title of this essay was offered as a joke by Mara Harrell, but I took it seriously. Research for this paper was supported in part by a grant to the University of California, Berkeley from the James S. McDonnell Foundation, by grants from the National Aeronautics and Space Administration to Carnegie Mellon University and to the Florida Institute for Human and Machine Cognition, and by a grant to Rutgers and Carnegie Mellon from the James S. McDonnell Foundation.

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