Teaching at the Brain’s Tempo

How researchers flashed lights at people to improve learning

CORRECTION 1/29/26 As "Lightcone” points out in the comments below, I misunderstood some of the research methods of this study in a way that made me mischaracterize the results in the blog post below. Please read his post below here, as well as our following conversation:

Every now and then, I will attempt to write an explanation of something that I am wholly unqualified to explain. This is one of those attempts. Please do not rely solely on my explanation for an understanding of the facts. I am writing this to attempt to increase my own understanding of the study in question, which means that, while I am doing my best to be accurate and comprehensive, there will still be gaps in my knowledge that I may not be aware of. Still, I hope this helps you get at least an introductory understanding of the work being done by these researchers. Massive thanks to the researchers and Fred Lewsey’s excellent coverage of their work.

 

In November 2022, Zoe Kourtzi—Professor of Experimental Psychology at the University of Cambridge—was the senior author of an article published in Cerebral Cortex, entitled “Learning at your brain’s rhythm: individualized entrainment boosts learning for perceptual decisions”. I took notice of this study because it has potentially large implications for future applications of both adult training and childhood education (both fields I have worked in as a teacher, professor, and instructional designer).

 

One of my frustrations in my early years of teaching and providing training was how little the education field provided me with insight into the biology of learning. Namely, the scientific examination of the learning process, both broadly and for individuals.

 

I have attempted to self-teach on some of this biology (to mixed success, I’m sure). Namely, I’ve tried to understand how human beings can reliably remember information they’ve learned. To sum it all up far too quickly (and yet still overly verbose), the key ingredient is focus. Think of focus like your brain pressing record. Even if you focus, of course, you’ll still need to figure out how to properly store that recording for effective usage later, but the first step to learning is to pay attention.

 

This is harder than it sounds and is often unconscious (though knowing how important it is can help you to try to create more conscious preparations and mindsets to help you focus). Further, there are time limits on how long humans can focus on any one particular task while “recording”. This varies for different people on different topics, but the limit seems to hover around 20 minutes.

 

This doesn’t mean you can’t perform tasks for longer than 20 minutes (think of various work binges you’ve had while completing a task), but it does mean that you will not remember much more than 20 minutes of that task if asked to recall it in detail later. This doesn’t apply to tasks that have multiple different kinds of tasks in them. Just the same kind of thing repeated over and over again (thus why delivering lectures in a classroom for longer than 20 minutes is so ineffective, for example).

 

As for the storing of this information, it tends to stay in short-term memory for a bit and then decay rapidly if it isn’t “retrieved” again in the very near future (think, informally, about a week’s time). Repeated “retrievals” of the information from storage will help the recording stick. Further, retrievals done with sleep in between them and the initial “recording” are much more powerful (same-day retrievals fade pretty quickly from memory). And retrievals done in different contexts also help the recording stick in the memory better. So practicing new knowledge that was learned in a classroom at home, with family, with strangers in a grocery store, and so on will make that recording more likely to be remembered long-term.

 

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Now that that mostly unnecessary preamble is out of the way, the reason I’m talking about this at all is because of the new learning method identified in this study which is attempting to hijack the brain’s rhythms to get it to better focus on the material to be learned. That increased focus from the study’s training session then paid off later as the participants’ learning rate for future, related material proved to be much stronger than the peers who did not receive this specialized training.

 

To give some background, Zoe Kourtzi and her co-authors noticed previous studies that showed significant enhancements of performance in perception-based activities if study subjects received a tempo calibration to their brain’s alpha frequency (“Each brain has its own natural rhythm, generated by the oscillation of neurons working together,” says Prof Zoe Kourtzi).

 

In those previous studies (Busch et al. 2009; Mathewson et al. 2011, 2010; Fakche et al. 2022), it had been demonstrated that creating an optical pulse in time with the lowest point (the “trough”) of an individual’s brain’s alpha frequency improves focus and performance (“excitability”) for a period of time. A temporary increase in performance is exciting, but still not necessarily applicable to those of us in the education field.

 

However, in Kourtzi et al.’s study, scientists wanted to see if the gains in performance during one session of testing would carry over to another few rounds of the test activity (the next day) without any additional tempo-alignment on the subsequent day. In other words, they wanted to know if this tempo-alignment enhanced not only performance, but also longer-term learning. To test this, the researchers took and used EEG readings of each participants’ alpha frequency to

 

“create an optical ‘pulse’: a white square flickering on a dark background at the same tempo as each person’s individual alpha wave. Participants got a 1.5-second dose of personalized pulse to set their brain working at its natural rhythm – a technique called “entrainment” – before being presented with a tricky quick-fire cognitive task: trying to identify specific shapes within a barrage of visual clutter.

 

“A brainwave cycle consists of a peak and trough. Some participants received pulses matching the peak of their waves, some the trough, while some got rhythms that were either random or at the wrong rate (a little faster or slower). Each participant repeated over 800 variations of the cognitive task, and the neuroscientists measured how quickly people improved.

 

“The learning rate for those locked into the right rhythm was at least three times faster than for all the other groups. When participants returned the next day to complete another round of tasks, those who learned much faster under entrainment had maintained their higher performance level.”

 

This is a pretty astounding finding, partially because of its relative simplicity. Sure, the researchers used advance EEG machines to measure and monitor the brain waves of the participants, but much more affordable headbands are available to purchase ($200-$500). Imagine, for example, a headband that enabled educators to determine each student’s alpha frequency trough so they could create and implement time-customized flashes on screens or in VR for each of them before administering a lesson.

 

As first author Dr Elizabeth Michael says, “the intervention itself is very simple, just a brief flicker on a screen, but when we hit the right frequency plus the right phase alignment, it seems to have a strong and lasting effect.”

 

Co-author Professor Victoria Leong explains that “we are tapping into a mechanism that allows our brain to align to temporal stimuli in our environment, especially communicative cues like speech, gaze and gesture that are naturally exchanged during interactions between parents and babies,” said Leong.

 

A mechanism that basically says to the brain: enter your natural rhythm and focus.

 

Not everyone in the study received the specially-timed training. Or rather, one group received random flashes while a third group received flashes that were specially-timed to the peak of their alpha waves (as opposed to the trough).

 

Mean learning rate (i.e. slope of logarithmic fit) across participants per group. Bars show mean learning rate per group (T-Match=Trough-Matched Training, T-nonMatch=alternate timings or no specific timings, and P-Match=Peak-Matched Training), as estimated from fitting the individual accuracy data. Error bars show ±1 SEM.

 

And according to the article, the large differences in learning rate weren’t achieved through “a speed–accuracy trade-off.” The researchers found that the participants’ reaction times decreased similarly across all groups. Further, they found that “the results could not be attributed to individual variability in performance, as there were no significant differences across groups for starting performance accuracy.”

 

And finally, a reminder that the improvement in performance over the second session on the next day was not due to another round of entrainment; they only performed the synchronized flashes on the first day, before the first session.

 

In other words, this kind of brainwave-matching activity isn’t just a one-time performance boost. Instead, it has the possibility of improving future performances on related tasks. As co-author Professor Victoria Leong explains, “by matching information delivery to the optimal phase of a brainwave, we maximize information capture because this is when our neurons are at the height of excitability.”

 

For the sake of adding to my own heuristic about learning, I buy into their possible hypothesis that this “height of excitability” has to do with the comfort of the learner and their ability to focus. As stated in the article, “It is possible that individualized alpha entrainment increases attentional resources available for stimulus processing, resulting in faster learning, consistent with the role of alpha rhythms in the attentional selection of sensory information (Foxe and Snyder 2011; Klimesch 2012; Peylo et al. 2021) and temporal prediction (Hanslmayr et al. 2011; Rohenkohl and Nobre 2011).” [emphasis mine]

 

There is likely, of course, to be other elements at play here that I don’t understand or haven’t previously reckoned with.

 

But even more interesting, in an interview with the University of Cambridge, the researchers asserted “that, while the new study tested visual perception, these mechanisms are likely to be ‘domain general’: applying to a wide range of tasks and situations, including auditory learning.”

 

The idea of these mechanisms applying to non-visual tasks as well as these visual ones which have been tested is very exciting. It might provide accelerated learning in demanding careers, help students struggling in a normal classroom, or perhaps even make late-life declines in learning rates less steep (easier retraining or new-skill-acquisition later in life).

 

The question becomes, how do educators start to imagine the implementation of these tools? This kind of tech might improve the efficiency and effectiveness of digital and distance learning in particular, where focus is usually an enormous problem.

 

In much the same way that we have been monitoring alternate reality/VR training and education for hands-on learning opportunities (waiting for costs to come down and—primarily—programming tools to become easier and more widespread), this research should make us perk up and start paying attention to another potential tool in teaching and training (should further research back up this study and indicate that more general applications would work).

 

It’s difficult for me in times like these to not get ahead of the program and start making plans for when such tech might be widely available. It may be quite some time before this starts to get implemented anywhere, but I’d like to see my colleagues start wrapping their heads around the possibilities of this tool now, to track the strengths and limitations that get uncovered in upcoming research in the hope that we’ll be ready to create learning applications that improve our students’ lives when it is ready.

 

References:

https://academic.oup.com/cercor/advance-article/doi/10.1093/cercor/bhac426/6814397

https://www.cam.ac.uk/stories/brainwavelearning