Peter Menzies

Abductive inference and delusional belief

Delusional beliefs have sometimes been considered as rational inferences from abnormal experiences. We explore this idea in more detail, making the following points. First, the abnormalities of cognition that initially prompt the entertaining of a delusional belief are not always conscious and since we prefer to restrict the term “experience” to consciousness we refer to “abnormal data” rather than “abnormal experience”. Second, we argue that in relation to many delusions (we consider seven) one can clearly identify what the abnormal cognitive data are which prompted the delusion and what the neuropsychological impairment is which is responsible for the occurrence of these data; but one can equally clearly point to cases where this impairment is present but delusion is not. So the impairment is not sufficient for delusion to occur: a second cognitive impairment, one that affects the ability to evaluate beliefs, must also be present. Third (and this is the main thrust of our paper), we consider in detail what the nature of the inference is that leads from the abnormal data to the belief. This is not deductive inference and it is not inference by enumerative induction; it is abductive inference. We offer a Bayesian account of abductive inference and apply it to the explanation of delusional belief.

Causal Models, Token Causation, and Processes

Judea Pearl (2000) has recently advanced a theory of token causation using his structural equations approach. This paper examines some counterexamples to Pearl’s theory, and argues that the theory can be modified in a natural way to overcome them.

The causal structure of mechanisms

Recently, a number of philosophers of science have claimed that much explanation in the sciences, especially in the biomedical and social sciences, is mechanistic explanation. I argue the account of mechanistic explanation provided in this tradition has not been entirely satisfactory, as it has neglected to describe in complete detail the crucial causal structure of mechanistic explanation. I show how the interventionist approach to causation, especially within a structural equations framework, provides a simple and elegant account of the causal structure of mechanisms. This account explains the many useful insights of traditional accounts of mechanism, such as Carl Cravers account in his book Explaining the Brain (2007), but also helps to correct the omissions of such accounts. One of these omissions is the failure to provide an explicit formulation of a modularity constraint that plays a significant role in mechanistic explanation. One virtue of the interventionist/structural equations framework is that it allows for a simple formulation of a modularity constraint on mechanistic explanation. I illustrate the role of this constraint in the last section of the paper, which describes the form that mechanistic explanation takes in the computational, information-processing paradigm of cognitive psychology.

Intrinsic Versus Extrinsic Conceptions of Causation

Hume begins his famous discussion of causation in the Enquiry with these words. “There are no ideas, which occur in metaphysics, more obscure and uncertain, than those of power, force, energy, or necessary connexion, of which it is every moment necessary to treat in all our disquisitions” (VII, pp. 61–2). It is well-known how he goes on to subject these ideas to a ‘sceptical doubt’, arguing that they are incoherent because they do not have their origins in any kind of sensory impression. Hume’ s own ‘sceptical solution’ to this doubt is also well-known: he argues that the only sensorily verifiable definition of causation must be drawn from things “extraneous and foreign”, in particular, from the relations of temporal priority, spatial contiguity and regularity. He argues that the conception of the causal relation as consisting in a necessary connexion is due to our projecting onto the world a “felt determination of the mind” to pass from cause to effect.