This paper discusses two challenges for a Boolean method for establishing constitutive regularity statements which, according to the regularity theory of mechanistic constitution, form the core of any mechanistic explanation in neuroscience. After presenting the regularity definition for the constitution relation and a methodology for constitutive inference, the paper discusses the problem of full variation of tested mechanistic factors and the problem of informational redundancy. A solution is offered for each problem. The first requires some adjustments to the original theory (...) by introducing the technical notion of a set of types satisfying independent instantiability. The second one is resolved by demonstrating that the problem of informational redundancy is based on a confusion that fails to challenge the theory. It is concluded that the methodology of constitutive inference is consistent and plausible with respect to actual practice in neuroscience. (shrink)

This paper is concerned with the content of the causal proportionality constraint. It investigates two general versions of the constraint, namely “horizontal” and “vertical” proportionality. Moreover, it discusses whether proportionality is considered an ontic or an epistemic, i.e. explanatory, constraint on causation in the context of some of the most prominent theories of causation. The following main claims are defended: (1) The horizontal (HP) and the vertical version (VP) of the proportionality constraint are logically independent. (2) HP is implied by (...) some prominent theories of causation, not by others. (3) None of the discussed popular theories of causation contradicts either HP or VP. (4) HP and VP are not ontic or epistemic principles as such; rather, whether they are ontic or epistemic depends on the theories chosen plus background assumptions about the existence of higher-level causes and their non-identity to lower-level ones. (shrink)

In this paper I reconstruct and evaluate the validity of two versions of causal exclusion arguments within the theory of causal Bayes nets. I argue that supervenience relations formally behave like causal relations. If this is correct, then it turns out that both versions of the exclusion argument are valid when assuming the causal Markov condition and the causal minimality condition. I also investigate some consequences for the recent discussion of causal exclusion arguments in the light of an interventionist theory (...) of causation such as Woodward's (2003) and discuss a possible objection to my causal Bayes net reconstruction. (shrink)

Jaegwon Kim’s (2005) most recent formulation of the so-called Supervenience Argument against Non-Reductive Physicalism is discussed. The two stages of Kim’s argument can be seen as instances of, what I will call, the Generalized Exclusion Argument.