Saturday, 21 October 2017

What Limits the Accuracy of Human Throwing?

Throwing a projectile in order to hit a target requires you to produce one lot of the set of release parameters that result in a hit; release angle, velocity (speed and direction) and height (relative to the target). My paper last year on the affordances of targets quantified these sets using a task dynamical analysis.

There is one additional constraint; these release parameters have to occur during a very short launch window. This window is the part of the hand's trajectory during which the ball must be released in order to intercept the target. It is very easy to release slightly too late (for example) and drill the projectile into the ground.

How large is this launch window? It is surprisingly, terrifyingly small; Calvin (1983) and Chowdhary & Challis (1999) have suggested it is on the order of 1ms. Those papers used a sensitivity analysis on simulated trajectories to show that accuracy is extremely sensitive to timing errors and this millisecond level precision is required to produce an accurate throw.

Smeets, Frens & Brenner (2002) tested this hypothesis with dart throwing. If this intense pressure on timing the launch window determines accuracy, then throwers should organise their behaviour and throw in a way that makes their launch window as tolerant of errors as possible. They replicated the sensitivity analyses on human data to see if people try to give themselves the maximum error tolerance in the launch, or whether they were trying to accommodate errors in other variables.

What they found is that the launch window timing is not the limiting factor. Their throwers (who were not especially expert) did not throw so as to minimise the sensitivity of the launch window timing to errors. Quite the contrary; they lived in a fairly sensitive region of the space, and then didn't make timing errors. They did throw so as to reduce the sensitivity to speed errors, however, and errors in the targeting came from errors in the spatial path of the hand that the system did not adequately compensate for, rather than the timing of the hand's release. (The authors saw some evidence that the position, speed and direction of the hand trajectory were organised into a synergy, which aligns nicely with the motor abundance hypothesis).

I would like to replicate and extend this analysis process using more detailed simulations and data from better throwers. I've become convinced it's a very useful way to think of what is happening during the throw. I also think these results point to some interesting things about throwing. Specifically, while timing and speed must both be produced with great accuracy, the system has developed two distinct solutions to coping with errors. Timing errors are reduced by evolving neural systems that can reliably produce the required precision. Speed errors have been left to an online perception-action control process which adapts the throw to suit local demands. The latter is the more robust solution; so why was timing solved with brain power?

Saturday, 16 September 2017

The Information for Progressive Occlusion

Gibson's ecological psychology is weird, if you are coming from a more traditional information-processing background. The two approaches make radically different assumptions about the nature of the world to be perceived; they have radically different ontologies. This means that there is little if any useful overlap in the way they do things, and communicating across the gap is very hard. I have a recent paper - preprint here - where I go into detail about the two ontologies as I defend ecological psychology from interface theory. It's essentially Turvey et al, 1981, but that's a bear of a read if you aren't already ecologically minded. Do mine first :)

Anyway, concrete examples help. My go-to is the outfielder problem but people are tired of that one. My other favourite is progressive occlusion (Gibson, Kaplan, Reynolds & Wheeler, 1969; Kaplan, 1969). Gibson worked this example up himself in great detail and so it stands as a nice concrete example to illustrate some elements of the ecological ontology. Given the recent total solar eclipse, it seems like the right time to blog it!

This post will review occlusion, talk about how it works and work with some demos. These are all linked from here; there is Matlab/Psychtoolbox code to run a demo, a video of that running and a Powerpoint with some slides. I'll refer to these throughout - occlusion is a dynamic process and so you need to see it moving for it to make sense.


Thursday, 31 August 2017

Expectations and the Size-Weight Illusion

The size-weight illusion (SWI) occurs when people are asked to judge the weights of two different sized but identically weighted objects. The smaller object is judged to be heavier. There are a variety of explanations for this illusion (see Buckingham, 2014 for a review). I'm going to be reviewing some papers on it as I develop some experiments connected to my throwing research.

One set of explanations is 'bottom up', i.e. perceptual. Amazeen & Turvey, 1996 suggested that people do not perceive weight but inertia (this is the dynamic touch hypothesis about the inertia tensor) and Zhu & Bingham (2011) have proposed the illusion is not the misperception of weight but the correct perception of throwability (I obviously quite like this one, and have discussed it here). Interestingly Zhu et al (2013) have since shown that the inertia tensor does not explain the throwing related SWI!

The second set of explanations is 'top down'. The basic hypothesis is that the sensorimotor system expects larger things to weigh more than smaller things, within a class of 'things'. This expectation has been learned over time via experience of the real world in which this is basically true. Large mugs weight more than small mugs, even if large mugs weigh less than small anvils.

There are two interesting papers that have looked at the top-down hypothesis.

Monday, 17 July 2017

Dear Disney; Let Me Help You VR

Disney posted a video recently from some researchers getting people to catch real balls in virtual reality (VR). It was a nice demo of some technology, and I don't actually want to be down on these researchers, but of course the psychology was lacking and there were some weird moments which I thought I would note for posterity. Also, Disney researchers, if you're reading, call me :)



Sunday, 21 May 2017

Ecological Information Is a Perceptual Mapping That Tracks Evolutionary Fitness

Interface theory in cartoon form. Thanks to Louise
Barrett for reminding me this exists :)
In my last post I was thinking out loud about some ecological lines of attack on interface theory (Hoffman et al, 2015). The first line of attack (Hoffman et al mischaracterise Gibson) fell over eventually; they don't quite go at it right, but using ecological information does fit their definition of a naive realist perceptual strategy ( 'a perceptual strategy for which X [perceptual experience] ⊂ W [the world] and P [the perceptual mapping] is an isomorphism on this subset that preserves all structures on W'; pg 1483). The second line of attack (everything they say about veridicality vs fitness applies only to inferential, constructivist theories of perception and Gibson's not playing that game) is true but not that interesting or convincing to anyone with established views.

Thanks to chats on Twitter (thanks Greg!) and applying the basic move of 'those aren't working but IT is still weird, what's next?', my new line of attack relates to a result from their simulations.

Friday, 19 May 2017

Does Interface Theory Have Consequences for the Ecological Approach?

I've been working on a commentary about interface theory (Hoffman, Singh & Prakash, 2015) which I have previously blogged about here. I'm still interested because it is, in part, a fairly direct shot at the ecological approach and I'm always keen to break those if I can. My piece stalled out, though, so I thought I'd spend some time here thinking out loud about the argument that stalled and another critique that came up as I re-read the paper.

To unbury the lede I just finished writing: the primary thing Hoffman et al get wrong about Gibson is that they think he wanted his theory to produce veridical perceptions, not simply adaptive ones. Gibson actually wanted adaptive perceptions, but found a way in which they were also veridical. This emphasis matters; Gibson does not stand or fall on issues of veridicality. In addition, every one of Hoffman et al's big swings apply only to inferential, constructivist theories of perception; Gibson is immune on these grounds as well. All Hoffman et al have done is redraw the terrain inferential theories have to traverse, and it will be interesting to see if anyone takes the bait. But the major argument simply remains, is perception inferential or ecological, and may the best data set win.

Tuesday, 2 May 2017

Exploring Some Handwriting Data (Experiment 1)

I have been trying to science handwriting for a year or two now, and I've had some time to dive into some recent data I collected to address some issues coming up in earlier studies. I had first run two training studies and analysed them using the lognormal model (which I blogged about here), but I immediately realised we were facing some wild individual variation; there are many ways to produce the necessary movement kinematics for a given letter and they might all be just fine. There is no single right way to produce a letter, so long as it's legible.

I therefore ran a simple study to quantify the within and between participant variation in letter production, as measured using the lognormal parameters nbLog and SNR/nbLog. A quick reminder; SNR is the signal-to-noise ratio and is a measure of the model fit; nbLog is the number of lognormal curves needed to fit the data; and the ratio of the two takes the model fit and penalises it by how hard the model had to work to get there. The data are here if you care to play

Participants viewed each letter of the alphabet, one at a time on a screen. Their job was to simply write that letter on a Wacom tablet where I could record the 2D kinematics of their movements. People saw each letter 10 times in a fully randomised order for a total of 260 trials.

Note: what is coming is entirely exploratory. I am literally just poking around to map out what I'm up against given the nature of the DVs. I am still figuring out the right analysis to capture what I want to say, so any thoughts welcome.