Tuesday, 25 January 2011

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.

Tuesday, 18 January 2011

Perceptual Learning Stabilises Action: A Test of the Bingham Model

Bingham's perception-action model was initially inspired by perceptual judgement studies (using vision and proprioception). The HKB phenomena are movement phenomena, however; simply noting that the same qualitative pattern is seen in different judgement and action studies is a good first step but only suggestive, at best. We therefore next took simultaneous judgement & action measures from a movement task where we manipulated the feedback display (Wilson et al, 2005a). For instance, when the display showed 0°, movement was stable, even when the movement was at, for example, 90°. Perception of relative phase was driving the stability of the movements.

On the basis of all this data, the model predicts that the reason 0° and 180° are easy is that the information specifying that you are moving this way is easily perceived. There is provisional evidence to support relative direction of motion as the specifying information (Bogaerts et al, 2003; Wilson et al, 2005b; Wimmers et al, 1992) with relative speed acting as a noise term. This variable certainly predicts the observed pattern, as the relative direction of motion is only stable at 0° and 180°. It is maximally variable at 90°, which would explain why movements here are also maximally unstable. The model is therefore explaining the problem with moving at 90° as a problem detecting the information required to maintain the coordination; as we saw in the case of friction, no information means unstable behaviour.

The model therefore makes a critical prediction. If we could improve people's ability to perceive 90°, they should gain the ability to move at 90° without any practice at the movement itself. All previous learning studies had entailed training people to move by having them move, with the help of various forms of transformed feedback methods (visual metronomes or Lissajous plots; more on this when I discuss feedback). The prediction, that movement stability should improve with improved perceptual ability, is a strong test of both the model and the modelling strategy in general, and the experiment to test it was the first half of my dissertation.

Friday, 14 January 2011

Reading Group - Gibson (1979) Chapter 6 Part 1

Chapter 6: Events and the information for perceiving events

Thus far, Gibson has been talking about how we perceive objects. But, things in the world often move around, so we'd better be able to perceive things that are extended in time as well. First off, Gibson describes the properties of surfaces that are relevant to events. He then identifies a number of things that can happen to surfaces during events. The nature of these changes will determine what types of optical information might specify particular events (this will be discussed in Chapter 6 Part 2).

Tuesday, 11 January 2011

There's No Prospective Information About Friction, or, Why I Fell Over on the Ice

In which I justify why I, a healthy perceiver-actor, slipped and fell on a clearly visible icy patch, breaking my wrist for the second time, using SCIENCE.

It's been a cold, icy winter here this year, and 6 weeks ago I slipped on a patch of ice and fell entirely on my (previously broken) wrist. The ensuing physics did enough damage that I needed surgery to set the wrist with two pins, and I am only today out of the cast. These kinds of falls and injuries are very common; half of all falls  in the US are caused by insufficient friction, and the types of injuries (broken wrists and collarbones, etc) suggest reactive responses to the slip - people using their arms to try and regain a sudden, unexpected loss of balance. 

The two papers I'm going to talk about are from the lab of my favourite developmental psychologist, Karen Adolph, who has done some excellent affordance work using the transition from crawling to walking as a way to studying the changing perception-action performance of children. This research, however, asked about whether a perceiver can detect information about upcoming friction conditions and use this information for prospective control. The answer seems to be no, because there isn't any information. Given that action requires information, the absence of information might explain the often catastrophic failures of action we see on ice and other low-friction surfaces.

At least, that will be my story.

Tuesday, 14 December 2010

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.

Friday, 3 December 2010

Stuff on the Internet (3 December 2010)

Some things that have come our way recently that are somewhat on topic for the blog.

Science
Ed Yong has a (paywalled) piece in the New Scientist about how birds visually perceive magnetic fields. He followed up on Not Exactly Rocket Science with interviews with two scientists working on this fascinating question: Klaus Schulten and Thorsten Ritz. 

NPR covers an interesting study on the fact that blindfolded humans tend to walk in circles. This fairly robust result is not due to handedness or any obvious biomechanical asymmetry, but seems to be the result of sensorimotor drift accumulating in the system (link to paper). Without calibration by vision, our sense of direction becomes increasingly noisy. This relates nicely to some data from a study some colleagues and I really need to write up, in which we got people to misperceive which finger was receiving vibrations after an extended period without vision of the hands.

The biomechanics of pterodactyl flight. 

Baroness Greenfield continues her war on the neurological consequences of modern technology.

Cool toys...er, I mean, educational stuff
Microsoft's Kinect motion tracker uses structured infra-red light arrays to passively track multiple moving objects. Deformations in the field are robust enough to detect game-specific motions as well as faces, etc. There's apparently a lot of people using the IR fields in their art (e.g here, via BoingBoing; mildly NSFW depending on where you work) and I think these could be a fun way to teach optic arrays to students. All I need is a Kinect and an IR sensitive camera...dear Microsoft...

Hi-speed video taken from a train.

Media
I caught up on some Rationally Speaking podcasts while recuperating from surgery on my wrist; these are the ones that caught my eye:
Newton TV: I haven't had a chance to really poke around, but what could be wrong with science videos hosted by scientists?

Blogging
There's a new blog  on being a science blogger called The Science of Blogging. We're looking forward to some good advice for broadening our reach a bit.

This editorial about the dangers of science blogging is almost entirely wrong.

Tuesday, 23 November 2010

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?