Ed Brayton

I was sad to hear of the death of Ed Brayton a few days ago.  He was a humanist and secular community leader, blogger, journalist and board member for the Center for Inquiry, Michigan.  Following a long battle with illness, he checked himself into hospice care, and died comfortably a few days later.

I think I first heard Ed Brayton in 2008 when he appeared as a guest on an episode of Reginald Finley's The Infidel Guy Show, which I listened to regularly while at university.

For the 12 years since then I've read Ed's blog and listened to his radio shows and podcasts.  I was delighted a couple of years ago when he returned to the airwaves with a new podcast, for which he had plans, though the most recent episodes are marked by his deteriorating health.  Unfortunately, the podcast has already lapsed from the web, so I will add what I have of it to the archive of Ed's other shows I have hosted. Throughout the time I followed him, Ed's staunch commitment to his humanist values, and rejection of tribalism, were an inspiration.  And when online atheism took an ugly turn in the last few years, Ed continued to find and highlight the good.

While I didn't know Ed personally, I always appreciated his words, and am sad that he is gone.

Who Framed Roger Rabbit

Check out this amazing video of Bob Hoskins clowning around on a blue-screen stage to do the Toon Town scene of Who Framed Roger Rabbit.  Early blue-screen cinema, I guess, so he doesn't even really have props or sight guides to play off against.

I can't remember where I saw this, possibly Important If True, back when that was a thing.

New preprint: "Understanding the role of linguistic distributional knowledge in cognition"

I have recently submitted a paper based on some work I have been doing at my job at the Embodied Cognition Lab at Lancaster University. In it, we look at a large set of linguistic distributional models commonly used in cognitive psychology, evaluating each on a benchmark behavioural dataset.

Linguistic distributional models are computer models of knowledge, which learn representations of words and their associations from statistical regularities in huge collections of natural language text, such as databases of TV subtitles. The idea is that, just like people, these algorithms can learn something about the meanings of words by only observing how they are used, rather than through direct experience of their referents. To the degree that they do, they can then be used to model the kind of knowledge which people could gain in the same way. These models can be made to perform various tasks which rely on language, or predict how humans will perform these tasks under experimental conditions, and in this way we can evaluate them as models of human semantic memory.

We show, perhaps unsurprisingly*, that different kinds of models are better or worse at capturing different aspects of human semantic processes.

A preprint of the report is available on Psyarxiv.


*unsurprising to you as you read this, perhaps, but actually this is the largest systematic comparison of models as-yet undertaken, and thereby the first to actually effectively weigh the evidence on this question.

New(ish) paper: "Entrainment to the CIECAM02 and CIELAB colour appearance models in the human cortex"

Not so long ago I had a paper published in Vision Research.  It's on some work I did some years ago with my friend and collaborator Andrew Thwaites.  In it we look at the entrainment of magnetoencephalographic activity in early visual cortex to colour information in visual stimulus using two competing computational models of colour.  In other words, when and where people's brainwaves directly track the colour of moving images they were seeing on a screen, using two theories about how colour could be represented in the brain.

The paper is in Elsevier's "open archive", which hopefully means you can read it for free.  If not, hit me up.

I don't talk about my work too much here, but if you're interested you can read more about what I do on my more professional website.