My name is Ben and I’m a self-taught programmer with no formal computer science training. A few years ago I gained the painful self-awareness that my scientific programming was shitty. I’m not saying it was wrong (I hope not) but it was just bad. I confused familiarity with my language of choice with proficiency. I had […]
Posterior predictive checks The toolbox now calculates 2 measures of “goodness of fit” of the models. This is a useful quantitative reassurance that the models describe the participant discounting behaviour better than chance. In turn, this is important when we come to deciding which (if any) data files we should exclude. You can go and […]
I am happy to announce my 3rd paper of the year, accepted for publication in Behavior Research Methods. Following my initial foray into writing review papers (2 earlier this year), this is my first methods paper, and also my first contribution to higher-level decision making.
One of the key things we must avoid is mess and confusion. In the last post I briefly covered one possible template for a research project. One of the reasons why cognitive modelling projects might be a little tricky is because you are not just using an off the shelf software package. For example, if […]
What we definitely want to do is avoid confusion and mess. Having a clear project structure and workflow has many advantages. While there is no one single correct way to organise a project, putting a bit of thought into it, and learning from past projects can help a lot. This is the workflow that works for […]
Vincent, B. T. (2015) A tutorial on Bayesian models of perception, Journal of Mathematical Psychology, 66:103–114.
This is the first post in a series exploring programming practice in cognitive modelling. While I have over a decade of experience in cognitive modelling, I am in no way an expert and have no formal computer science training. I am not an authority on this, I am feeling my way. Comments welcome. This post may […]
I am very happy to announce my new tutorial review paper. Vincent, B. T. (2015) Bayesian accounts of covert selective attention: a tutorial review, Attention, Perception, & Psychophysics, 77(4), 1013-1032. If you do not have an institutional subscription to Attention, Perception, & Psychophysics, Springer allow me to self-archive my author-accepted manuscript (legal). Get the preprints here: [manuscript pdf], [supplementary pdf]. The final publication […]
GitHub is a great online repository and version control platform for your code. I’ve only started using it recently and I really like it so far. The only downside is that their free account does not allow for private repositories. This is a bit not good if you want to work on code for a research […]
There seem to be many ways to get up and running with Python, and these fall into a few main categories: Don’t install anything. You can actually get up and running with Python with no install at all by using Wakari, which is basically computing in the cloud. Time to set up: ~2 mins. Install a […]
In the last few months I’ve decided to break off a ~15 year relationship with Matlab. We’ve been through many important times together and it’s not been an easy decision to make, but I think this is the best for both of us. Matlab saw me through my DPhil, helping me code up neural network […]
[UPDATE: February 2014] The files and instructions are now hosted on GitHub. Energy efficient receptive field code by Benjamin Vincent is licensed under a Creative Commons Attribution-Non-Commercial-Share Alike 3.0 Unported License. This minimal set of MATLAB functions will set up a simple neural network to learn receptive fields. These receptive fields minimise an energy function which involves a) […]