The Perturbation Experiment as a Way to Study Perception

When you study perception, your goal is to control the flow of information going into the system so that you can measure the resulting behaviour and evaluate how that information is being used. There are two ways to do this, one (sometimes) used by me, one used by, well, everyone else. In this post I'm going to compare and contrast the methods and describe why the perturbation method is what we should all be doing.

The standard method is to present experimentally isolated cues and test whether people can detect those cues. The perturbation experiment presents a 'full cue' environment but selectively interferes with the link between a single variable and the property it might be information about. These two different methods lead to very different ways of thinking and talking about perceptual abilities. 

The Task Dynamics of Throwing to a Maximum Distance

In my last post I went over the formal concept of task dynamics as a way of analysing a task to identify the affordances in that task. This post will examine the task dynamics of projectile motion and relate these to throwing to a maximum distance.This version of the task has been studied in detail over the last few years. There is another version of the task, namely throwing to hit a target (same dynamic, different parameters, therefore same task) and we will get to that later; we're working now on data from this task.

Part of my goal here is to lay out the research programme you should be following, if you want to study anything to do with perception and action. If you are interested in movement, and you aren't doing this kind of analysis as part of your work, then, I will suggest, you are doing it wrong. As we will see in future posts, this level of detail isn't just playing with numbers; a formal understanding of the underlying dynamics governing the task we are studying is utterly crucial if we want to be able to understand what people are doing, rather than simply describe their behaviour. 

Also it's fun :)

Are babies super? Performance, competence and infant habituation

Are babies really more competent than we give them credit? (No.)

Developmental psychology is filled with studies that claim to show the hidden abilities of babies. The claim is that babies come pre-packaged with all kinds of knowledge and skills that provides them with the foot in the door they need to learn about the world. Babies are limited in their ability to demonstrate this knowledge, however, because of their immature bodies and inability to control these well. In the language of the field, there is hidden competence concealed by problems with performance, and researchers (such as Liz Spelke and Renee Baillargeon) are interested in finding ways to reveal this hidden competence.

At IU we referred to such studies as 'super baby' studies, because they purported to show that infants were remarkably competent and knowledgeable about the world. Besides the rampant dualism of 'mind' being concealed by 'body', these studies are good examples of a common problem (the psychologist's fallacy) in psychological research, one that a rigorous application of embodied cognition helps fix.

Theory, and Why It's Time Psychology Got One

Psychology has a problem. We have no core theory to guide our research; no analogue to the theories of evolution or relativity. When particle physicists recently found that some neutrinos had apparently travelled faster than light, it never actually occurred to them that this is what had happened. On the basis of the extraordinarily well supported theory of relativity, everyone went 'huh, that's weird - I wonder what we did wrong?', and proceeded to use that theory to generate hypotheses they could then test. It would take a lot of fast neutrinos to disprove relativity.

Psychology, though, when faced with an empirical result that violates the laws of physics, can't find any principled reason to reject the result and instead spends a lot of time squabbling about whether Bem's result might possibly be true because 'quantum'. Worse, when people do replicate the experiment and fail to support the original result, they can't get their 'null result' published. It's a bit embarrassing, really.

One of the problems of having no core theory is that you can't simply rule things out as options. Psychologists almost all consider this a strength: we can pick and choose from a variety of mechanisms which enables us to cope with our messy and erratic subject matter. Can't imagine how perception can explain a result? Just hypothesise a mental representation to fill the gap. After all, no single theory is going to account for the opportunistic and idiosyncratic behaviour of people, so why limit ourselves? We tried that with behaviourism, and it got us nowhere. Let's stay flexible.

Robots, Representation, & Dynamical Systems

When cognitive science tries to explain a given behaviour, it typically looks in one of two places for it's explanation. Some people go looking in the brain for the representation that encodes the solution to the task; these people typically treat the brain as the source of the observed structure in behaviour. Some of us, however, go looking in perception for the necessary access to the properties of the world that enable us to couple our resources to those in the environment. We consider the origin of behaviour to be the dynamical system formed by this coupling; the system provides a set of constraints and behaviour emerges as the constrained system works over time.

It's sometimes a little hard to tease these suggestions apart: after all, they  typically both predict that we succeed at the task at hand. When studying people, the best way to try and separate these two suggestions out is to examine how we succeed. For instance, in catching a fly ball, the brain-based prediction solution says we will run in a direct line to where we think the ball will land; the perception-based coupling solution suggests we will run along curved paths as we attempt to move so as to produce the information required. In this case, data supports the latter hypothesis, but it's not always that easy.

Sometimes, you've just got to start from scratch and build yourself a robot.

Lissajous feedback and coordination stability

Understanding the perceptual information you provide people in a task is a critical element of the perception-action analysis. Last time I talked about the new form of coordination feedback I developed to allow us to train coordinated rhythmic movements without perturbing the task dynamic. Prior to this, the most common form of augmented feedback was the Lissajous plot - these are the result of plotting the displacements of two harmonic oscillators against one another, and the unique shape associated with each relative phase can be used as a template on the screen. People can then try to move so as to make a dot trace that shape.

Lissajous plots (have a play with them in this Excel file) are transformed feedback, because they take a coordinated movement and represent it on the screen as the motion of a single dot. This type of feedback has been used extensively to train people to perform novel coordinations, but until recently no-one had thought to investigate the consequences of transforming the information about relative phase. Kovacs, Buchanan and Shea have recently begun doing exactly this, and, in line with the perception-action approach developed by Bingham and pushed at every opportunity by myself, these authors have found that Lissajous plots completely alter the nature of the task, with serious consequences for the studies that rely on it.

Visual feedback for training novel coordinations

The key feature of coordinated rhythmic movements is that not all coordinations are stable. Most other rhythms can be learned, however, which is why we can have jazz drumming. People have been training participants to perform novel coordinations (especially 90°, the least stable rhythm without training) for years now, and have been asking all the standard learning questions - how long does learning take? Does it transfer to other coordinations? 

The first real studies on learning were by Kelso and Zanone (Kelso & Zanone, 2002; Zanone & Kelso, 1992a, b, 1997). I briefly reviewed the results of these studies here, which have lead to to the dynamic pattern hypothesis. This account describes stable states as attractors in a state space defined by relative phase as the order parameter, and learning is the creation of a new attractor centred on the target novel phase. This account ran into problems quite quickly but is still alive and kicking in a modified form; stability is the governing principle now, and from this perspective the feedback displays used for training don't matter so long as they support stable action. 

However, from our perception-action standpoint, the feedback displays matter a lot, because these are what's providing the perceptual information about the coordinated movement. Early learning studies all used some kind of transformed feedback, which we could never use because it altered the overall perception-action dynamic. In order to look at action learning directly, we needed a new form of feedback. 

So I invented one.

Chemero (2009) Chapter 8: Neurophilosophy Meets RECS

Chemero's book finishes with two chapters on some philosophical consequences of taking a radical, embodied approach to cognitive science. Chapter 8 is about the mind-body problem, and how various attempts to reduce cognitive science to, say, neuroscience, can be vigorously resisted via the RECS approach, without being dualist about the mind. There are many people who think cognitive science can be reduced to neuroscience (intertheoretic reduction), but one plank of any embodied approach is that this won't work. RECS is particularly committed to a more extended notion of cognition and so a strategy for resisting reduction is critical. Chemero's plan won't rely on the usual philosophical manoeuvres such as Martian pain mechanisms or zombies. Like me, Chemero is concerned that these create the impression that philosophers aren't tackling real problems; he wants the philosophical conclusions of RECS to be grounded in data, and I thoroughly endorse this approach.

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.

How to Build a Valid Measure of Behaviour

One of the main problems facing psychology as a science is the issue of validity - what is the relationship between what you measured and what you are actually interested in? One of the things I like about studying movement is how straight-forward this issue is - we're interested in the control of action, so I just measure the action! The most common directly measured kinematic variable is displacement, or position over time; you can then derive (via differentiation) the various rates of change of the previous variable (velocity, acceleration, jerk, and, I kid you not, snap, crackle, and pop). In human movement we never tend to go past jerk, and you can do pretty well with just position and it's rate of change, velocity.

This post will discuss how we start from these basic kinematics and derive a measure of coordination that is  entirely valid, covers the entire space of possible states and provides a unique number for every possible state within that space. Psychology doesn't have a lot of these kinds of variables, but you need to be able to characterise your state space to do the kind of modelling I've been describing and advocating.

"Moving Through Time" and embodied cognition

In which I am a bit rude about a rubbish paper and worry about how to kill papers like it.

The term 'embodied cognition' has been checked out of the library by a lot of different people, all of whom use it to mean something different. My least favourite definition comes from the cognitive literature, which considers embodiment to be about how internal, abstract cognitive function can be 'revealed' motorically (the Barselou (2008) version of embodiment). This definition is rooted firmly in the assumption of mental representation. For me, embodiment is only interesting if it contributes in a meaningful way to what cognition is, and thus I define embodied cognition in the other direction - embodied cognition is about how cognition is shaped by the kind of perceiving-acting organism we are.

Internal representation or behavioural dynamics?

More on Gibson later, but I wanted to get to this today. Yesterday I saw a talk about eye tracking, and how people control smooth pursuit movements (the tracking movements your eyes can make when you’re following something continuously). Tracking performance is a quandary for cognitive folks, because we are often very good at it. For instance, if you ask people to track a moving stimulus and record their eye movements, they will successfully foveate the target with almost no lag or erratic need to play catch up (foveating means using the fovea, the densely packed high resolution region on the retina we rely on for precise visual perception). The lack of ‘catch-up’ is the interesting bit, and cognitive psychology thinks that it is evidence of prediction by the system. Prediction requires a predictor, which for cognitive psychology is always a representation.

The main thing I learned from this talk is this: I am a rampant ego-maniac who is convinced I am right and other people are wrong, but at least I am capable of entertaining the idea that there is another way to conceive of the task. This speaker (and at least one other person in the room) was completely unaware that their perspective entailed assumptions about the underlying mechanism and simply couldn’t conceive of another way to describe the task: for them, prediction was clearly required and therefore internal representation was clearly required.