English: Extract from Raspberry Pi board at Tr...
The Raspberry Pi (photo credit: Wikipedia)

A few months ago, I suggested that Raspberry Pis could be used as a barebones experiment presentation machine. Since then I have got my hands on one and tinkered a little, only to be reminded yet again that my inability to do anything much in both Linux and python is a bit of a problem.

Fortunately, others with more technological nous have been busy exploring the capabilities of the Pi, with some exciting findings. On the Cognitive Science Stack Exchange, user appositive asked “Is the Raspberry Pi capable of operating as a stimulus presentation system for experiments?” and followed up at the end of January with a great answer to their own question, including this paragraph:

The RPi does not support OpenGL. I approached this system with the idea of using a python environment to create and present experiments. There are two good options for this that I know of, opensesame and psychopy. Psychopy requires an OpenGL python backend (pyglet), so it won’t run on the Rpi. Opensesame gives you the option of using the same backend as PsychoPy uses but has other options, one of which does not rely on openGL (based on pygames). This ‘legacy’ backend works just fine. But the absence of openGL means that graphics rely solely on the 700 mHz CPU, which quickly gets overloaded with any sort of rapidly changing visual stimuli (ie. flowing gabors, video, etc.).

Because of the lack of OpenGL support on the Pi, Psychopy is out (for now) leaving OpenSesame as the best cog psych-focused python environment for experiment presentation. The current situation seems to be that the Pi is suboptimal for graphics-intensive experiments, though this may improve as hardware acceleration is incorporated to take advantage of the Pi’s beefy graphics hardware. As things stand though, experiments with words and basic picture stimuli should be fine. It’s just a case of getting hold of one and brushing up on python.

UPDATE via Comments (1/4/2013) – Sebastiaan Mathôt has has published some nice Raspberry Pi graphics benchmarking data, which are well worth a look if you’re interested.
http://www.cogsci.nl/blog/miscellaneous/216-running-psychological-experiments-on-a-raspberry-pi-with-opensesame

A couple of months ago, the folks at codecademy were nice enough to respond to a complimentary e-mail I’d sent them by writing something nice back about me and publishing it on their codecademy.com/stories page.

cadecademic

It was great to get this sort of coverage on a site I think is fantastic (despite the picture of me with a rather supercilious looking one-year old on my back). The only problem was that I didn’t have a working example of code available for them to link to. The JavaScript experiments I had previously coded had run their course, garnering approximately 200 participants each, and had been taken offline, leaving the lab experiment page with nothing for people to try their hand at.

That changed today.  I have a very simple new experiment for people to try their hand at, which can be accessed via the experiments (online) link on the right, or directly, here: http://www.st-andrews.ac.uk/~oclab/memorywords/.

I’m afraid it doesn’t quite do justice to the “neuroscientist discovers javascript” headline on the codecademy stories page, but it’s something.

Points and badges

For the past week or so, I have been working my way through Codecademy’s JavaScript tutorials. I can’t recommend them highly enough.

As things stand, I have a full house of 480 points and 35 badges and, as the Codecademy creators would undoubtedly hope, I am rather satisfied with the JavaScript proficiency I have attained. ‘Attained’ is probably the wrong word to use though. Being a self-taught Matlab hacker, I have found most of my coding know-how has translated fairly well into Javascript. A few concepts (recursion in particular) have presented me with some difficulty, but the overall experience has been more like learning a new coding dialect  than a new language altogether. I haven’t attained a proficiency, so much as uncovered a hidden one.

Which brings me to why I sought out Codecademy in the first place (thanks to @m_wall for the twitter-solicited tip-off) – I am preparing to teach Psychology undergrads how to code. From 2012/2013 onwards, my academic life is going to be a little more ‘balanced’. As well as the research, admin and small-group teaching I currently enjoy, I’m also going to be doing some large-group teaching. Although I have plenty to say to undergraduates on cognitive neuroscience and cognitive psychology, I think giving them some coding skills will actually be much more useful to most. As my experience with Codecademy has recently reinforced to me, coding basics are the fundamental building-blocks of programming in any language. They will hold you in good stead whatever dialect you end up speaking to your computer in. What’s more, they will hold you in good stead whatever you end up doing, as long as it involves a computer: coding is the most versatile of transferable skills to be imparting to psychology graduates who (rightly) believe they are leaving university with the most versatile of degrees.

With all this in mind, one of Codecademy’s limitations is the difficulty with which its students can translate their new-found JavaScript skills into useful ‘stuff’ implemented outside the Codecademy editor. As Audrey Watters points out, there is barely any acknowledgement within the Codecademy tutorials that the goal of all of these points and badges is to encourage you to write interactive web contact in an IDE. Indeed, last night when I thought about how I would use JavaScript to administer online  memory experiments, I had to do a lot more reading. This could all be about to change though. If the latest Code Year class on HTML is anything to go by, the folks at Codecademy are mindful of this limitation, and are attempting to remedy it.

It’s just a shame that the html integration has come so late in the Code Year (yes, I say this with full awareness that we’re only on week 13).  If the HTML-Javascript confluence had come a little further upstream, I think there probably would have been a fledgling memory experiment linked to from this blogpost!

Below (indented) is a straightforward MATLAB/SPM/Marsbar script for generating separate Marsbar ROI and Nifti ROI spheres (user-defined radius) from a set of user-defined MNI coordinates stored in a text file (‘spherelist.txt’ saved in the same directory as the script).  ROI files are saved to mat and img directories that the script creates.
I use this script to generate *.mat files as seeds for resting connectivity analyses.  Once a *.mat ROI is generated, Marsbar can be used to extract raw timecourses from this region to feed into connectivity analysis as the regressor of interest.  Because MRIcron doesn’t read *.mat Marsbar ROI files, I render the equivalent *.img seed regions on a canonical brain when I need to present them graphically.

% This script loads MNI coordinates specified in a user-created file,
% spherelist.txt, and generates .mat and .img ROI files for use with
% Marsbar, MRIcron etc.  spherelist.txt should list the centres of
% desired spheres, one-per-row, with coordinates in the format:
% X1 Y1 Z1
% X2 Y2 Z2 etc
% .mat sphere ROIs will be saved in the script-created mat directory.
% .img sphere ROIs will be saved in the script-created img directory.
% SPM Toolbox Marsbar should be installed and started before running script.

% specify radius of spheres to build in mm
radiusmm = 4;

load(‘spherelist.txt’)
% Specify Output Folders for two sets of images (.img format and .mat format)
roi_dir_img = ‘img’;
roi_dir_mat = ‘mat’;
% Make an img and an mat directory to save resulting ROIs
mkdir(‘img’);
mkdir(‘mat’);
% Go through each set of coordinates from the specified file (line 2)
spherelistrows = length(spherelist(:,1));
for spherenumbers = 1:spherelistrows
% maximum is specified as the centre of the sphere in mm in MNI space
maximum = spherelist(spherenumbers,1:3);
sphere_centre = maximum;
sphere_radius = radiusmm;
sphere_roi = maroi_sphere(struct(‘centre’, sphere_centre, …
‘radius’, sphere_radius));

% Define sphere name using coordinates
coordsx = num2str(maximum(1));
coordsy = num2str(maximum(2));
coordsz = num2str(maximum(3));
spherelabel = sprintf(‘%s_%s_%s’, coordsx, coordsy, coordsz);
sphere_roi = label(sphere_roi, spherelabel);

% save ROI as MarsBaR ROI file
saveroi(sphere_roi, fullfile(roi_dir_mat, sprintf(‘%dmmsphere_%s_roi.mat’,…
radiusmm, spherelabel)));
% Save as image
save_as_image(sphere_roi, fullfile(roi_dir_img, sprintf(‘%dmmsphere_%s_roi.img’,…
radiusmm, spherelabel)));
end

UPDATE: WordPress messed with the characters in the above script, so here is a link to the script file and an example spherelist.txt file.