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.

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.

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.