Monthly Archives: November 2013

How to hack conditional branching in the PsychoPy builder

Regular readers will know that I’m a big fan of PsychoPy, which (for non-regular readers; *tsk*) is a piece of free, open-source software for designing and programming experiments, built on the Python language. I’ve been using it a lot recently, and I’m happy to report my initial ardour for it is still lambently undimmed.

The PsychoPy ‘builder’ interface (a generally brilliant, friendly, GUI front-end) does have one pretty substantial drawback though; it doesn’t support conditional branching. In programming logic, a ‘branch’ is a point in a program which causes the computer to start executing a different set of instructions. A ‘conditional branch’ is where the computer decides what to do out of two of more alternatives (i.e. which branch to follow) based on some value or ‘condition’. Essentially the program says, ‘if A is true: do X, otherwise (or ‘else’ in programming jargon) if B is true; do Y’. One common use of conditional branching in psychology experiments is to repeat trials that the subject got incorrect; for instance, one might want one’s subjects to achieve 90% correct on a block of trials before they continue to the next one, so the program would have something in it which said ‘if (correct trials > 90%); then continue to the next block, else if (correct trials < 90%); repeat the incorrect trials’.

At the bottom of the PsychoPy builder is a time-line graphic (the ‘flow panel’) which shows the parts of the experiment:

PsychoPy_builderThe experiment proceeds from left to right, and each part of the flow panel is executed in turn. The loops around parts of the flow panel indicate that the bits inside the loops are run multiple times (i.e. they’re the trial blocks). This is an extremely powerful interface, but there’s no option to ‘skip’ part of the flow diagram – everything is run in the order in which it appears from left-to-right.

This is a slight issue for programming fMRI experiments that use block-designs. In block-design experiments, typically two (or more) blocks of about 15-20 seconds are alternated. They might be a ‘rest’ block (no stimuli) alternated with a visual stimulus, or two different kinds of stimuli, say, household objects vs. faces. For a simple two-condition-alternating experiment one could just produce routines for two conditions, and throw a loop around them for as many repeats as needed. The problem arises when there are more than two block-types in your experiment, and you want to randomise them (i.e. have a sequence which goes ABCBCACAB…etc.). There’s no easy way of doing this in the builder. In an experiment lasting 10 minutes one might have 40 15-second blocks, and the only way to produce the (psuedo-random) sequence you want is with 40 separate elements in the flow panel that all executed one-by-one (with no loops). Building such a task would be very tedious, and more importantly, crashingly inelegant. Furthermore, you probably wouldn’t want to use the same sequence for every participant, so you’d have to laboriously build different versions with different sequences of the blocks. There’s a good reason for why this kind of functionality hasn’t been implemented; it would make the builder interface much more complicated and the PsychoPy developers are (rightly) concerned with keeping the builder as clean and simple as possible.

Fortunately, there’s an easy little hack which was actually suggested by Jon Peirce (and others) on the PsychoPy users forum. You can in fact get PsychoPy to ‘skip’ routines in the flow panel, by the use of loops, and a tiny bit of coding magic. I thought it was worth elaborating the solution on here somewhat, and I even created a simple little demo program which you can download and peruse/modify.

So, this is how it works. I’ve set up my flow panel like this:

flow

So, there are two blocks, each of which have their own loop, a ‘blockSelect’ routine, and a ‘blockSelectLoop’ enclosing the whole thing. The two blocks can contain any kind of (different) stimulus element; one could have pictures, and one could have sounds, for instance – I’ve just put some simple text in each one for demo purposes. The two block-level loops have no condition files associated with them, but in the ‘nReps’ field of their properties box I’ve put a variable ‘nRepsblock1’ for block1 and ‘nRepsblock2’ for block2. This tells the program how many times to go around that loop. The values of these variables are set by the blockSelect routine which contains a code element, which looks like this:

Screen Shot 2013-11-12 at 09.58.02

The full code in the ‘Begin Routine’ box above is this:

if selectBlock==1:
 nRepsblock1=1
 nRepsblock2=0
elif selectBlock==2:
 nRepsblock1=0
 nRepsblock2=1

This is a conditional branching statement which says ‘if selectBlock=1, do X, else if selectBlock=2, do Y’. The variable ‘selectBlock’ is derived from the conditions file (an excel workbook) for the blockSelectLoop, which is very simple and looks like this:

Screen Shot 2013-11-12 at 10.06.36

So, at the beginning of the experiment I define the two variables for the number of repetitions for the two blocks, then on every go around the big blockSelectLoop, the code in the blockSelect routine sets one of the number of repetitions of each of the small block-level loops to 0, and the other to 1. Setting the number of repetitions for a loop to 0 basically means ‘skip that loop’, so one is always skipped, and the other one is always executed. The blockSelectLoop sequentially executes the conditions in the excel file, so the upshot is that this program runs block1, then block2, then block1 again, then block2 again. Now all I have to do if I want to create a different sequence of blocks is to edit the column in the conditions excel file, to produce any kind of sequence I want.

Hopefully it should be clear how to extend this very simple example to use three (or more) block/trial types. I’ve actually used this technique to program a rapid event-related experiment based on this paper, that includes about 10 different trial types, randomly presented, and it works well. I also hope that this little program is a good example of what can be achieved by using code-snippets in the builder interface; this is a tremendously powerful feature, and really extends the capabilities of the builder well beyond what’s achievable through the GUI. It’s a really good halfway step between relying completely on the builder GUI and the scaryness of working with ‘raw’ python code in the coder interface too.

If you want to download this code, run it yourself and poke it with a stick a little bit, I’ve made it available to download as a zip file with everything you need here. Annoyingly, WordPress doesn’t allow the upload of zip files to its blogs, so I had to change the file extension to .pdf; just download (right-click the link and ‘Save link as…’) and then rename the .pdf bit to .zip and it should work fine. Of course, you’ll also need to have PsychoPy installed as well. Your mileage may vary, any disasters that occur as a result of you using this program are your own fault, etc. etc. blah blah.

Happy coding! TTFN.

3D printed response box. The future. It’s here.

photo

 

This may not look like much, but it’s actually pretty cool. It’s a new five-button response-box being built for our MRI scanner by one of the technicians where I work. The cool thing is that the main chassis has been custom-designed, and then fabricated using a polyethylene-extruding 3D printer. The micro-switches for the four fingers and thumb and the wired connections for each have obviously been added afterwards.

3D printing in plastic is a great way of creating hardware for use in the MRI environment, as, well… it’s plastic, and it can create almost any kind of structure you can think of. We sometimes need to build custom bits of hardware for use in some of our experiments, and previously we’d usually build things by cutting plastic sheets or blocks to the required shape, and holding them together with plastic screws. Using a 3D-printer means we can produce solid objects which are much stronger and more robust, and they can be produced much more quickly and easily too. I love living in the future.