Manipulating the probability of events creates a host of behavioural changes. In Jabar & Anderson (2015), we highlight that probable orientations are robustly linked to better perceptual precision. We also advanced a hypothesis: Perhaps the result of probability learning is to change the neural tuning of visual processing neurons, leading to these precision changes.

Electrophysiologically, probability has traditionally been linked to the P300 component. This late-occurring component, among other things, is linked to ideas of ‘surprise’ and ‘attention’, and is not thought to stem from visual processing regions. Using the paradigm from Jabar & Anderson (2015) though, where the feature made probable (orientation) is a very simple one, can we find an earlier, more occipital, modulatory effect of probability? With that hypothesis in mind, we have taken our first steps into EEG!

Research questions aside, embarking on this project has been a great learning opportunity thus far: Among other things, this project has led me to learn how to use Python to control individual pins in a parallel port, testing the parallel port pins with a multimeter to see that pulses are sent correctly when the code is injected into the experiment, and using this setup to output event markers on the EEG recording. Hands-on experience with placing the EEG cap on participants (without damaging the wires) was eye-opening. Of course, then comes the part where we have to figure out how to analyse the EEG signals, how to look at power spectrums, how to find and reject artifacts, and how to make plots like these:

That image is the the average waveform (time-locked to the stimulus onset) across trials for the 72 recorded channels. Does probability modulate the occipital activity that seemingly occurs 200ms in? What will we find? To find out more, stay ‘tuned’ …