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.

A Quick Review and Analysis of Perceptual Control Theory

Perceptual Control Theory (PCT; Powers, 1973) is a theory that proposes behaviour is about the control of perception. We act so as to keep some perceived part of the world at some state, and it's by doing this to sensible variables that we come to exhibit functional behaviour. People have noted the seeming overlap between PCT and the ecological approach, and it's advocates (mainly Richard Marken and Warren Mansell) all talk about it in revolutionary terms that should also feel a bit familiar.

I first encounted it in the context of an interview with Richard Marken on a now defunct blog (pdf of the archived page; link to page and scroll down to "Interview with Richard Marken"). Marken and I got into it a bit in the comments, as you will see! I was not impressed. However, Mansell & Marken (2015) have just published what they pitch as a clear exposition of what PCT actually is and how it works. I took the opportunity to read this and evaluate PCT as a 'grand theory of behaviour'.

My basic opinion has not changed. PCT is not wrong in most of it's basic claims, but it has no theory of information or how that information comes to be made or relate to the dynamics of the world. It's an unconstrained model fitting exercise, and it's central ideas simply don't serve as the kind of guide to discovery as a good theory should. Ecological psychology does a much more effective job of solving the relevant problems. 

Thinking about representations in relation to mechanisms

As Chemero (2011) observed, there are two ways to think about debates in science. We can either debate about the actual facts of the matter in the world or we can debate about the best way to explain the world. Some debates aren't amenable to the first type of debate, because there is no evidence that can definitively rule out one of the options. The only debate we can really have about representations is in terms of their role in explanations of behaviour. This is different than how I thought about representations a few years back when I wanted to argue that invoking representations was inherently a bad idea. Now I think we need to consider the utility or representations as part of explanations for psychological phenomena. In this post, I will argue that the concept of representations is not helpful in developing a particular class of explanation - ontic mechanistic explanations (described below). This is the first of two posts on this idea. In the next post I will attempt to explicitly compare cognitive and ecological approaches to behaviour in terms of how well they set us up to identify real parts and operations.

Dynamic Mechanistic Explanations in Radical Embodied Cognitive Science

I'm on my way back from an enactivist/embodiment conference in Warsaw. I gave a talk (slides) in which I argued that in order to make theories of distributed/embodied cognition work, you have to have something like a theory of ecological information as the glue to hold it all together. All the talks I saw that discussed any kind of plan for distributing cognition were missing this piece and desperately needed it, so I'm hoping the talk will make people realise this tool exists and can help. Drop me a line if you would like any help!

I argued specifically that information lets us propose mechanistic explanations for distributed cognitive systems. We recently came across the philosophical literature on what mechanisms are and how to make them, and it seemed immediately clear that we should be doing this (and that we already are; see below). 

It turns out, though, that some of the radical camp (specifically Chemero and Silberstein) don't think we can have distributed cognition mechanisms, but that this is ok because we still get explanations out of our dynamical models. 

This post will briefly review what dynamic mechanistic explanation is and why they are so useful (Bechtel & Abrahamsen, 2010). I'll briefly summarise the radical opposition to mechanisms, point out their answer doesn't work, then talk an example that shows we can have radical dynamic mechanistic explanatory models without giving anything up. The trick, as ever, will be to rely heavily on information as the component part that allows cognitive mechanisms to extend out over body and environment. 

Perception, Action & Dynamical Systems

Over Easter I visited the Center of Functionally Integrative Neuroscience at Aarhus University in Denmark, courtesy of the Interacting Minds group. I gave a talk, got the tour, and met some of the faculty and students - some interesting opportunities for future collaborations, I hope - thanks for the hospitality!

I wanted to lay out the basics of the talk I gave. I took the opportunity to present some ideas that have been developing as I work on this blog, reading Chemero and working on coordination experiments. There is a core of people in Aarhus interested in things ecological, as well as dynamical systems, so it was a good audience to try these ideas out and they seemed to go over well. This is also the sketch of a paper Sabrina and I are going to work on over the summer.

The take home message of the talk was simple - dynamical systems is the right kind of mindset for cognitive science, but it is not a theory of behaviour. Dynamics merely provides the right kind of modelling tools - the form of the model must be based on hypotheses about the specific kind of dynamical systems we are or else they are merely an exercise in data-fitting. Ecological psychology is the right theory, and the Bingham model of coordinated rhythmic movement is currently the only example of a genuinely perception-action dynamical systems model. My thoughts here are largely from my response to Chapter 4 of Chemero (on 'the dynamical stance') and Chapter 5, his initial attempt to use dynamics to serve as a guide to discovery which I think fails and which Chemero then replaces with ecological psychology. The description of Bingham's model comes from here.

Identifying the Visual Information for Relative Phase

Bingham's model predicts that the information for relative phase is the relative direction of movement. The first direct test of this hypothesis was the experiment that followed on from my learning study, in which we systematically perturbed the various candidate information variables to see which affected performance in the perceptual judgement task.

I like this study a lot, if I do say so myself. It's a serious attempt to make a strong test of the model's predictions, and we invested a lot of time in the methodology. This is also that rare paper that benefited from a vigorous review process; the end result is, I think, a clear, careful, and detailed presentation of a critical result for the perception-action approach Geoff and I are developing.

Readers interested in the issue of how you can scientifically study information from an ecological perspective should certainly read the paper (Ken, that's you :); it's my go-to reference for how I believe this has to be done. The main lesson - it's hard to do this properly, but the rewards, in terms of unambiguous data, are clear.

What Does Coordinated Rhythmic Movement Have To Do With Anything?

In which I provide an answer to a question I get asked by everyone, including grant reviewers, students and random people who make the mistake of asking what I do for a living.

I've spent numerous recent posts talking about coordinated rhythmic movement. This is my bread-and-butter experimental task, my go-to example for studying all aspects of perception, action and learning. I'm branching out, now I have my own faculty position, but coordination is where it's at. 

The single most common question I get is "why study this? Surely it's just some fake movement task; I mean finger-wiggling, who ever even does that?" I wouldn't mind so much, but I even get this question from grant reviewers, scientists who should know the answer. Doing science properly is important, but communicating that my methods achieve this matters too, not least because today's funding climate demands it.

So, coordinated rhythmic movement: what the hell?

A Perception/Action Model of Coordination

Other coordination posts are here.

The role of perception in the dynamic leading to the HKB phenomena has been made clear by the work so far. But the exact form of this dynamic had yet to be modelled; the HKB model only consists of two cosine functions superimposed on each other to produce the two attractors at 0° and 180°, and the dynamic pattern hypothesis it embodies made predictions which did not held up empirically. It was now time to take an explicitly perception/action approach to modelling the task, which means it's finally time to turn to (my PhD advisor) Geoff Bingham's model (2001, 2004a, 2004b). This model is a fully perception/action model, and the modelling strategy Bingham lays out is, I think, a masterclass in how to go about building models of this kind.