FaceGen – 3D modelling software for faces

I’ve recently been playing with a bit of software called FaceGen, and it’s basically awesome. As you might expect it’s a piece of 3D modelling software which is specialised in producing human face stimuli. You can either start off with a randomly-generated example, or upload your own (or someone else’s) picture, which the software can then extrapolate and model in 3D. The 3D model can then be modified to your heart’s content along various parameters – age, sex, race, emotional expression etc. etc. It really is an awesomely powerful piece of software, and pretty easy to use too, with the interface mostly based around a set of sliders for manipulating the various dimensions of the stimulus.

Here’s a brief video which gives an overview of some of the features:

The full version of FaceGen costs $299, but there is a free demo version that you can play with, available here.

Face stimuli have always posed a problem for researchers, and historically there have basically been two choices. The first is to use a standardised face-set such as the Ekman faces:

These stimuli have the benefit of being naturalistic, i.e. they are of real people, but several significant drawbacks. These face sets are often idiosyncratic in various ways and may not have all the facial expressions you might need, for all the picture subjects. In addition, they’re often not well-balanced in terms of race, age, sex etc. In particular the ‘classic’ Ekman face set is looking very dated and frankly, pretty ghastly, these days. Another more recent example would be the NimStim face set.

The second option is to use schematic or computer-generated faces such as these from this paper:

These have the big benefit of precise experimental controllability, but the obvious drawback that they aren’t very naturalistic at all. 

The FaceGen software seems to offer the best of both worlds, in that you can create an almost infinite variety of precisely-produced images and easily control for confounding factors like age and race, while at the same time the stimuli it produces are pretty naturalistic – particularly so, if you import ‘real’ pictures and then modify them. I’m currently setting up an experiment which will use some face stimuli and I’m almost certainly going to use stimuli produced using FaceGen.

For more on faces in psychology research see my previous post on face-morphing. TTFN!

BrainDesire, Online Experiments, Neuro-business and a Plea for Openness

I’ve recently had some correspondence with the CEO of a company called Brain and Science which runs a site called BrainDesire. The site purports to use…

“…the latest discoveries in brain science, and applies them to dating, relationships and love. Discover BrainDesire and find out which men or women have a real potential for dating and for a serious relationship with you.”

It does this by an online test, where you enter the name of the person you are romantically interested in and the name is then used in a relatively simple priming experiment where the name is used as the prime and the task is a lexical decision. The idea is that the name of Mr or Ms Right leads to higher arousal, and therefore a faster reaction time for the lexical decision. Once the test is complete, your results are then available for a modest fee.

My initial reaction to this was “pffftt… yeah, right”, and expressing this opinion on twitter was what first attracted the attention of the CEO of the company. We ended up having quite a technical discussion by e-mail about the scientific basis of the procedure BrainDesire uses and my assessment of it is now much better informed. There are several potential issues with the test which were immediately apparent.

Firstly, the scientific basis of the test. It’s largely based on a 2006 paper by Bianchi-Demicheli, Grafton and Ortigue which demonstrates the reaction time speeding effect when a beloved’s name is used as a prime. These authors are well respected scientists who generally do outstanding work and I have no reason to suppose that there is anything wrong with the paper (yes, I could get nit-picky about the methods, but I could do that with almost any paper). Incidentally, Scott Grafton and Stephanie Ortigue comprise the Scientific Advisory Board of the company. What I do have an issue with though, is that this result has never really been convincingly replicated. There’s another paper from 2007 which uses the same task in a fMRI scanner, and pretty-much replicates the result, however the effects are much weaker and the sample size is much smaller, plus only women were used in this experiment. Not totally convincing.