Cognitive Models Are Not Mechanistic Models (#MechanismWeek 2)

So far we have talked about what mechanisms are and what sort of model counts as properly mechanistic. The next question is to have a look in more detail at the models of cognitive science and see how far they can take us towards mechanistic explanations.

Last time I discussed the examples of research on memory, visual object recognition and categorisation. This kind of functional modelling work is the rule, not the exception in cognitive science - it's how we're taught to work and how the field moves along.

@PsychScientists A mechanism is a graph with at least three boxes and two arrows.

— Tim van der Zee (@Research_Tim) May 24, 2016

This kind of program feels like it's heading towards mechanism . Every division into new sub-capacities comes from work showing the two sub-capacities function differently and are therefore the result of different mechanisms. Every new representational model adds a new component (part or process) that handles another part of the capacity. There is one basic problem, however. None of these models make any explicit reference to any real parts or processes that have been empirically identified by other work - for example, 'working memory' still refers to a capacity, not a component. This means there is no reason to think this new capacity maps onto any particular parts and processes or if it does, to which parts and processes.

We are, in effect, doing science backwards: modelling first, running experiments later, and the result is that we are not actually on a trajectory towards mechanistic models, just better functional ones. This is a problem to the extent you want access to the many real benefits mechanistic models offer, in particular the ability to explain rather than simply describe a mechanism (see Bechtel & Abrahamsen, 2010 and the last post). This post reviews whether functional models explain or whether they can be part of a trajectory towards an explanation. The answer, unsurprisingly, will be no.

Mechanisms and Models of Mechanisms (#MechanismWeek 1)

In this first #MechanismWeek post, I will define a mechanism and briefly describe the kind of models of mechanisms you can build. I begin with various kinds of functional models (Cummins, 1975, 2001; Weiskopf, 2011). These either break capacities of systems into more coherent, easily studied sub-capacities (think of breaking memory into long term memory and short term memory as a simple example) or model them with components that may or may not be really implemented in the organism (e.g. geons, exemplars).

I will then introduce the idea of a dynamic causal mechanistic model (Bechtel & Abrahamsen, 2010) which attempt to map model components directly onto the real parts and processes of the mechanism at hand. The argument is that while functional models provide useful descriptions of mechanisms, they do not provide an explanation of that mechanism, and that only mechanistic models can explain.