In our recent study we asked how waves that the brain produces by itself – alpha rhythms – relate to waves triggered by viewing a flickering screen. Both can be of similar frequency (~10Hz, or ten cycles per second) and are easily recorded from the scalp with electrodes (EEG). To recap, we did not find much evidence for a strong link between the two types of brain waves (more info).
However, there are many ways to produce a flicker, and virtually any rhythmic change in a stimulus will likely drive a measurable brain wave. In experiments we typically use rhythmic changes in brightness (light on/off) or contrast (imagine flipping a checkerboard with its mirror image). Less frequently we use changes along other dimensions of visual properties (e.g. colour, motion). But even within a given property dimension there is a lot of wiggle room in the choice of stimulation parameters – some experiments employ low intensity/low contrast stimuli (as we did) others use intense, full contrast checkerboards.
We know that the properties of the flicker can have a profound influence on the shape of the brain waves they are driving. In brief, waves can look more and less sinusoidal depending on stimulation. The best way to visualise this is to look at EEG spectra (- basically a ledger of the sinusoidal oscillations that make up the EEG-recorded waves). If you only see a peak at the flicker rate (say 10 Hz) then the brain wave elicited by the stimulation will be nearly sinusoidal. If other peaks show up at 20, 30 Hz and so on (multiples of 10), then chances are high your waveform looks more rugged.
With all that in mind it is worth considering that different waveforms, produced by different flickers while keeping the frequency constant, may influence the results of an experiment. Looking at our data, is there a possibility that we would have arrived at different conclusions with an alternative flicker approach?
In our experiment we used a relatively unique approach of smooth contrast changes. Put briefly, we presented a slightly changed version of the stimulus on each frame (= one picture of a movie) of the stimulation. A more typical approach is to switch a stimulus on and off repeatedly to arrive at a similar presentation rate. Would this type of flicker produce a similar pattern of results?
I was able to check this in data from an older study. This experiment had a similar set up with flickering stimuli presented on the left (rate = 10.6 Hz) and right (14.2 Hz). Crucially, here stimuli were simply switched on & off to produce the flicker (more info can be found in the original paper). Suffice it to say that (N = 14) participants were shown a cue (left/right) telling them to focus their attention towards the left or right stimulus for the rest of the trial (~3sec). As in our recent study, I tested effects of attention on the power of the intrinsic alpha rhythm and flicker-driven brain waves. To do so I used the scripts available on osf.io/apsyf.
Above, we see a very typical pattern in the scalp map: the power of the alpha rhythm lateralises according to the focus of attention. Focusing on the left stimulus reduces alpha power over the right hemisphere and vice versa (- although the effect seems to be relatively weak for the left hemisphere). Looking at the spectra shows higher alpha power in the 8 – 13 Hz alpha frequency band when participants ignored the contralateral stimulus position. Interestingly, we also see that the stimulation is intense enough to produce power peaks visible in the spectra of what we have called ‘ongoing’ power. Note that these peaks do not necessarily carry the alpha suppression effect (10.6 Hz peak, right hemisphere, purple spectra) and may even show a reversed pattern (14.2 Hz peak, left hemisphere, orange spectra).
Also, the results for the stimulus-driven waves look very similar to our first report: A measure of how well the brain repeatedly tracks the flicker on each side shows clear peaks at the stimulation frequencies 10.6 & 14.2 Hz (and a Harmonic). Both responses increase when participants focus on the respective driving stimulus. Scalp maps give an impression of this effect* across recording electrodes.
To cut it short, despite the differences in stimulation, patterns of results of both experiments are very similar. Thus, different stimulation approaches may produce different waveforms while the effects the experimenter intends to measure on the waveforms can remain comparable (at least in our case, for visuo-spatial attention).
Thanks to Matt Davidson for prompting this re-analysis on twitter.
* Note that these maps look different from the ones published here. This highlights the influence of factors such as stimulus intensity, location and frequency on the variability of how attention effects project to the scalp.