Language, thought and the ecological approach; A Purple Peril

As part of a class on cognitive psychology, I give a seminar in which we talk about the research on the relationship between language and thought. In particular, I show this great talk by Lera Boroditsky as a starting point. She talks about the kind of research in this area, and talks about results such as how we linguistically interact with space and time affecting how we physically interact with these things. For example, some languages like English use an egocentric frame of reference when talking about space (e.g. describing things as being to the left or right, where the origin of this space is the speaker). Other languages use a geocentric frame of reference (e.g. describing things as being to the south of you). In order to be able to speak and understand the language, you therefore have to be able to remain oriented in space, and speakers of these kinds of languages have been shown to be capable of impressive feats of dead reckoning previously thought impossible in humans. 

The reason this is all interesting is in the context of how the field is changing how it thinks about language; is it magical, or merely interesting? If the former, language becomes a unique human cognitive capacity that requires specific neural mechanisms that serve language and nothing else. If the latter, language becomes an integrated part of our cognitive systems and we should expect it to show these connections to other capacities. 

The weight of evidence right now I think favours the latter view. In fact, one whole strand of embodied cognition (Shapiro’s ‘conceptualisation’ hypothesis strand) explicitly pursues these connections between language and other capacities, for example Lakoff’s work on metaphors being grounded in action. Language, while still phenomenal in what it can do, is not different in kind to the rest of cognition. 

The field is still very much at the ‘functional model’ stage of developing explanations, however. The research mostly just catalogues linguistic differences and cognitive differences and works to map those onto each other in a fairly metaphorical, word-association kind of way (e.g. politics is talked about in terms of left and right wing so this should connect to physical movements to the left and the right). Our ecological questions has become, what kind of mechanism might allow this kind of cross-talk, and as I’ve been chatting to students I’ve been connecting a few dots for myself. This post sketches the outline of a mechanistic, ecological research programme for attacking the fascinating problem of the relationship between language and thought.

Ecological Mechanisms and Models of Mechanisms (#MechanismWeek 4)

Mechanistic models are great, but so far cognitive science doesn't have any. We have functional models (of, for example, memory or categorisation) and dynamical models (of, for example, neural networks) but none of these can support the kind of explanations mechanistic models can. Is that it for psychology, or can we do better?

Here we propose that it's possible to do psychology in a way that allows for the development of explanatory, mechanistic models. The trick, as we have discussed, is to identify the correct level of analysis at which to ground those models. These models will definitely end up being multi-level (Craver, 2007), but the form of these final models will be dictated and constrained by the nature of the real parts and operations at the grounding level.

The correct level of analysis, we propose, is the ecological level. Specifically, ecological information is going to be the real component whose nature will place the necessary constraints on both our empirical investigations of psychological mechanisms as well as the mechanistic models we develop.

Let's see how this might work.

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.

#MechanismWeek (a week of posts commencing June 20th 2016)

Cognitive science is, in principle, the search to understand the mechanisms that cause our behaviour to look the way that it does. We run experiments designed to figure out the form of the behaviour to be explained, and we propose models that try to account for the behaviour. But how well are we doing, and can we do better?

It turns out that there is a rich and extremely useful philosophical literature about mechanisms. Specifically, there is a lot of clear and accessible work describing what mechanisms are, and, more importantly, how science can go about modelling those mechanisms. This literature has provided us with a wonderfully useful central focus for our ongoing work, and I wanted to walk through the key issues here. (We have covered this topic in a couple of posts - here and here - but there are several interlocking issues that I want to spell out one at a time).

Sabrina is in Warsaw June 23-25th attending the Mechanistic Integration and Unification in Cognitive Science conference, where she will present on how ecological information provides the key to mechanistic explanations in psychology.

To celebrate, there will be a new post from her every day of the week commencing June 20th 2016 on the topic of mechanisms, specifically cognitive mechanisms, and how to model them. Below is a list describing the upcoming posts and providing links to some useful reading.

We'd like to invite you all to play along, either in the comments or on Twitter (where we live as @PsychScientists; suggested hashtag #MechanismWeek). I've sketched out the week below, with recommended readings so yo can play along.

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.