The curious effect of a musical rhythm on us

Do you know the feeling of a musical piece moving you? What is this feeling? One common answer by psychological researchers is that what you feel is your attention moving in sync with the music. In a new paper I show that this explanation is mistaken.

Watch the start of the following video and observe carefully what is happening in the first minute or so (you may stop it after that).

Noticed something? Nearly everyone in the audience moved to the rhythm, clapping, moving the head etc. And you? Did you move? I guess not. You probably looked carefully at what people were doing instead. Your reaction illustrates nicely how musical rhythms affect people according to psychological researchers. One very influential theory claims that your attention moves up and down in sync with the rhythm. It treats the rhythm like you treated it. It simply ignores the fact that most people love moving to the rhythm.

The theory: a rhythm moves your attention

Sometimes we have gaps of attention. Sometimes we manage to concentrate really well for a brief moment. A very influential theory, which has been supported in various experiments, claims that these fluctuations in attention are synced to the rhythm when hearing music. Attention is up at rhythmically salient moments, e.g., the first beat in each bar. And attention is down during rhythmically unimportant moments, e.g., off-beat moments.

This makes intuitive sense. Important tones, e.g., those determining the harmonic key of a music piece, tend to occur at rhythmically salient moments. Looking at language rhythm reveals a similar picture. Stressed syllables are important for understanding language and signal moments of rhythmic salience. It makes sense to attend well during moments which include important information.

The test: faster decisions and better learning?

I, together with Suzanne Jongman, asked whether attention really is up at rhythmically salient moments. If so, people should make decisions faster when a background rhythm has a moment of rhythmic importance. As if people briefly concentrated better at that moment. This is indeed what we found. People are faster at judging whether a few letters on the screen are a real word or not, if the letters are shown near a salient moment of a background rhythm, compared to another moment.

However, we went further. People should also learn new words better if they are shown near a rhythmically salient moment. This turned out not to be the case. Whether people have to memorise a new word at a moment when their attention is allegedly up or down (according to a background rhythm) does not matter. Learning is just as good.

What is more, even those people who react really strongly to the background rhythm in terms of speeding up a decision at a rhythmically salient moment (red square in Figure below), even those people do not learn new words better at the same time as they speed up.

It’s as if the speed-up of decisions is unrelated to the learning of new words. That’s weird because both tasks are known to be affected by attention. This makes us doubt that a rhythm affects attention. What could it affect instead?

Figure 1. Every dot is one of 60 participants. How much a background rhythm sped up responses is shown horizontally. How much the same rhythm, at the same time, facilitated pseudoword memorisation is shown on the vertical axis. The red square singles out the people who were most affected by the rhythm in terms of their decision speed. Notice that, at the same time, their learning is unaffected by the rhythm.

The conclusion: a rhythm does not move your attention, it moves your muscles

To our own surprise, a musical rhythm appears not to affect how your attention moves up and down, when your attentional lapses happen, or when you can concentrate well. Instead, it simply appears to affect how fast you can press a button, e.g., when indicating a decision whether a few letters form a word or not.

Thinking back to the video at the start, I guess this just means that people love moving to the rhythm because the urge to do so is a direct consequence of understanding a rhythm. Somewhere in the auditory and motor parts of the brain, rhythm processing happens. However, this has nothing to do with attention. This is why learning a new word shown on the screen – a task without an auditory or motor component – is not affected by a background rhythm.

The paper: the high point of my career

You may read all of this yourself in the paper (here). I will have to admit that in many ways this paper is how I like to see science done and, so, I will shamelessly tell you of its merits. The paper is not too long (7,500 words) but includes no less than 4 experiments with no less than 60 participants each. Each experiment tests the research question individually. However, the experiments build on each other in such a way that their combination makes the overall paper stronger than any experiment individually ever could.

In terms of analyses, we put in everything we could think of. All analyses are Bayesian (subjective Bayes factor) and frequentist (p-values). We report hypothesis testing analyses (Bayes factor, p-values) and parameter estimation analyses (effect sizes, Confidence intervals, Credible intervals). If you can think of yet another analysis, go for it. We publish the raw data and analysis code alongside the article.

The most important reason why this paper represents my favoured approach to science, though, is because it actually tests a theory. A theory I and my co-author truly believed in. A theory with a more than 30-year history. With a varied supporting literature. With a computational model implementation. With more than 800 citations for two key papers. With, in short, everything you could wish to see in a good theory.

And we falsified it! Instead of thinking of the learning task as ‘insensitive’ or as ‘a failed experiment’, we dug deeper and couldn’t help but concluding that the attention theory of rhythm perception is probably wrong. We actually learned something from our data!

PS: no-one is perfect and neither is this paper. I wish we had pre-registered at least one of the experiments. I also wish the paper was open access (see a free copy here). There is room for improvement, as always.

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Kunert R, & Jongman SR (2017). Entrainment to an auditory signal: Is attention involved? Journal of experimental psychology. General, 146 (1), 77-88 PMID: 28054814

Dyslexia: trouble reading ‘four’

Dyslexia affects about every tenth reader. It shows up when trying to read, especially when reading fast. But it is still not fully clear what words dyslexic readers find particularly hard. So, I did some research to find out, and I published the article today.

The bookworm (presumably non-dyslexic)

Imagine seeing a new word ‘bour’. How would you pronounce it? Similar to ‘four’, similar to ‘flour’ or similar to ‘tour’? It is impossible to know. Therefore, words such as ‘four’, ‘flour’ and ‘tour’ are said to be inconsistent – one doesn’t know how to pronounce them when encountering them for the very first time. Given this pronunciation challenge, I, together with my co-author Christoph Scheepers, hypothesised that such words would be more difficult for readers generally, and for dyslexic readers especially.

Finding evidence for a dyslexia specific problem is challenging because dyslexic participants tend to be slower than non-dyslexic people in most tasks that they do. So, if you force them to be as quick as typical readers they will seem bad readers even though they might be merely slow readers. Therefore, we adopted a new task that gave people a very long time to judge whether a bunch of letters are a word or not.

It turns out that inconsistent words like ‘four’ slow down both dyslexic and typical readers. But on top of that dyslexic readers never quite reach the same accuracy as typical readers with these words. It is as if the additional challenge these words pose can, with time, be surmounted in normal readers while dyslexic readers have trouble no matter how much time you give them. In other words, dyslexic people aren’t just slow. At least for some words they have trouble no matter how long they look at them.

This is my very first publication based on work I did more than four years ago. You should check out whether the waiting was worth it. The article is free to access here. I hope it will convince you that dyslexia is a real challenge to investigate. Still, the pay-off to fully understanding it is enormous: helping dyslexic readers cope in a literate society.

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Kunert, R., & Scheepers, C. (2014). Speed and accuracy of dyslexic versus typical word recognition: an eye-movement investigation Frontiers in Psychology, 5 DOI: 10.3389/fpsyg.2014.01129
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Picture: Carl Spitzweg [Public domain or Public domain], via Wikimedia Commons

How to turn an ‘afores’ into an ‘adorer’ – text messaging needs subtitles

How come my Nokia text messaging programme prefers to turn my pressing of 782 into ‘rub’ first and only then offers me ‘pub’? Surely, the dictionaries which predictive texting programmes use can be improved. The only question is how. Psycholinguistics may have found the answer on the television screen.

The basis on which the initial texting dictionaries are compiled has not been disclosed. Still, the order in which alternatives are offered suggests that it is out of date. Below is an indication of why ‘rub’ is offered first and ‘pub’ thereafter: that’s how their respective frequencies (vertical axis) used to be ordered. Google’s ngram viewer, however, suggests that by 1980 (time is on the horizontal axis) ‘pub’ overtook ‘rub’. Other such word pairs also switched order of use during the twentieth century: ‘boy’/‘box’ (1990), ‘rope’/‘pose’ (1983), ‘lord’/‘lose’ (1904), ‘Ford’/‘dose’ (1951).

Still, predictive texting does not only face the challenge of how to order suggestions. It also has to limit the choices it offers for memory and usability reasons. For example, for 236737 my mobile phone does know ‘afores’ but not ‘adorer’. The challenge of which words to include is faced by all dictionaries. The Oxford Dictionary (LINK) uses a huge collection of texts called the Oxford English Corpus and includes new words if there is evidence that they are significant or important. I suspect that the most crucial criterion is simply how many times a word is used.

But which corpus is the best to determine that? Surely, for text messaging one would prefer a corpus made up only of text messages. In the absence of such corpora for all the languages text messaging is used in, one may turn to big corpora under the assumption that size matters or one may turn to corpora of sources users are likely to read, e.g. the internet. But how do you arbitrate between these options? Ideally, one would like to simply try out different approaches in real world text messaging and see how they perform. For the moment, however, it is easier to turn to what we already know from psycholinguistic research about word frequencies.

Psycholinguists have been interested in word frequencies for a long time because they account for up to 40% of the reading speed, as measured by how long it takes people to judge whether a letter string is a word or not (Brysbaert et al., 2011). Given that reading speed is often taken as a proxy for how words a represented in the mental lexicon, controlling for frequency is now standard practice in Psycholinguistics. Recently, Brysbaert and colleagues (2011) pitted different corpora against each other in order to see which one accounts best for reading speed. Google’s scanning of words resulted in the biggest corpus in the study but it did not perform the best. Even limiting the google corpus to more recent books did not improve its performance enough to outperform its unlikely rival which is 99.9% smaller: subtitles.

Whether in English, French, German or Chinese, word frequencies based on subtitles outperform their rivals based on books. They account for more variance in word judgement times in both typical, young research participants as well as old people in their seventies (Brysbaert et al., 2011). Furthermore, corpora based on subtitles have the added benefit of being easy to compile as well as update and they could be made available in all televised languages.

Too many people waste too much time correcting predicted words to ignore the need for better dictionaries. Given the strong psycholinguistic support for subtitle based word frequencies, it would be worth trying them out in predictive texting programmes. Perhaps this way ‘rub’ and ‘pub’ will be offered in the right order and 236737 will no longer be an ‘afores’ but instead an ‘adorer’.

Brysbaert, M., Keuleers, E., & New, B. (2011). Assessing the usefulness of Google Books’ word frequencies for psycholinguistic research on word processing. Frontiers in Psychology, 2, 1-8. doi: 10.3389/fpsyg.2011.00027
LINK