IRA FLATOW: This is Science Friday. I’m Ira Flatow.

[MUSIC – DAVID BOWIE, “LET’S DANCE”] Let’s dance. Put on your red shoes and dance the blues.

IRA FLATOW: What makes a good dance song? Even if you don’t know the song– of course, it’s “Let’s Dance,” by David Bowie– you could recognize it as a dance song, right? Something you get up and it gets you up and moving, and you know it’s a dance song. But cultures all around the world have their own dance songs.

But would you be able to recognize them as you did that David Bowie song? In other words, is there something universally true about music or how our brain recognizes music that connects all these dance type songs? And are we able to pick up on that? That’s exactly the question that my next guests and their team wanted to find out.

They took different types of songs from all over the world and played them for people to see what they recognized. People in 60 countries listened to songs from 86 mostly small-scale societies. And their study was published this week in the journal Current Biology.

Let me introduce my guest. Samuel Mehr is a Research Associate in the Department of Psychology and Principal Investigator of the Music Lab at Harvard University. Welcome to Science Friday.

SAMUEL MEHR: Hi, thanks for having us.

IRA FLATOW: You’re welcome. Manvir Singh is a PhD candidate in Human Evolutionary Biology, also at Harvard. Welcome to Science Friday.

MANVIR SINGH: Yeah, thank you. Hello.

IRA FLATOW: Manvir, let me ask you first. In this study, you were interested in seeing if listeners were able to match up the form of a song to its function. Can you explain what you mean and what you were looking for? Why were you interested in this?

MANVIR SINGH: Yeah, so what we mean is we were kind of asking, do songs that share social functions around the world– share functions like being used to make people to dance or being used to calm fussy infants, heal illness– do they have convergent features? And we were thinking both about the contextual features– so stuff like whether instruments are used or the gender of the singers. But also very importantly, the musical features– so the melodic complexity, the rhythmic complexity, the tempo, et cetera. SAMUEL MEHR:

IRA FLATOW: And Samuel, for the first part of the study you used the internet to play clips to people online to see if they could pick out these types of songs, correct?

SAMUEL MEHR: Yeah, that’s right. So we had a pretty large collection of songs from all over the world as part of the natural history of song discography, which is a project that Manvir and I co-direct with Luke Glowacki. We took little snippets of each song, 14 seconds a piece, and played them to listeners in 60 different countries all over the world.

The experiment is really simple. Basically people all over the world listened to each snippet, and then answer a series of questions about each of them about what they think the singers are doing. We ask them, do you think the singers are using the song for dancing? Do you think they’re using the song to soothe an infant, to heal illness, and so on.

IRA FLATOW: All right, let’s let our listeners in on the fun. We’re going to play the songs for them. Let’s listen to one form. There are three different dance songs in this one clip.

[MUSIC PLAYING]

IRA FLATOW: Those were dance samples from the Yolngu of Australia, the Mentawai of Southeast Asia, and the Hopi of Arizona, correct?

SAMUEL MEHR: Yeah, that’s right.

IRA FLATOW: And how well were listeners able to identify these as dance songs, Samuel?

SAMUEL MEHR: Oh, so the really striking finding, especially for dance songs, is that not only are people around the world very accurate at identifying when a song is being used for dancing– they rate it quite highly on this dimension used for dancing– but they’re also really confident in their ratings.

They rate it super high on the scale relative to other songs. And they rate them highly consistently with other listeners around the world. So it doesn’t matter if I’m sitting here in Cambridge listening to this dance song or Manvir’s doing it from Mentawai. We agree with each other.

IRA FLATOW: All right, let me listen to another form. I’m going to give out three more songs. I’m not going to tell you– I’m not going to reveal what type it is. So listeners, trying to guess what type of songs these are.

[MUSIC PLAYING]

IRA FLATOW: Yeah, what do you think? What kind of songs were they? Time’s up. I’m going to tell you. They were lullaby samples from the Saami of Scandinavia, the Nyangatom of East Africa, and the Ainu of East Asia. Does identifying the type of song have to do with the elements of the song? You would think that a lullaby would be right quieter, have less singers, Sam or Manvir?

MANVIR SINGH: Yeah, so what we actually found in a follow-up experiment was that listeners do seem to be using the features of the songs to make their rating decisions. And lullabies, in particular, are defined– seemed to be different on all of the features that we examined.

So they have slower tempos. They are less melodically and rhythmically complex. They are less happy sounding, kind of less exciting. And we saw that listeners use both these musical features, as well as the contextual features, like, is there an instrument or the gender of the person singing. So, yeah, it seems like they are using those features.

IRA FLATOW: Samuel, you’re a cognitive scientist. Do you think that our brains form to pick up these type of songs for some reason?

SAMUEL MEHR: I think that’s one of the sort of interesting questions that’s still open, that research like this paper helps us to begin to answer. So theories from biological evolutionary work and cultural evolutionary work make different predictions about what we should find in the world when we study music across different cultures. And those theories are testable in these data sets.

So two theories are out there about where dance music might come from, from a biological perspective, and where lullabies might come from, from a biological perspective. And both of those make predictions, not only that dance songs and lullabies should share features across cultures, which is what we find in this paper, but also that those features should be shaped by their adaptive function. And those are really interesting biological questions that we’re going to be able to test as more work like this is done.

IRA FLATOW: Interesting. Manvir, is there an evolutionary hypothesis to why some of these sounds develop for a particular function?

MANVIR SINGH: Yeah, so like Sam is mentioning, there are some people who hypothesize, for example, that music has evolved so that we can dance and we can kind of be a more socially cohesive group, or that we can dance together and signal to other people that we are a very formidable group. Alternatively, there are other evolutionary theories that say that lullabies, for example– the singing of lullabies and the listening of lullabies– evolved for parents to signal their attention.

So these are a body of theories that we call adaptive theories. They all say that music making and music listening evolved for adaptive reasons.

IRA FLATOW: Interesting.

MANVIR SINGH: And there are these more byproduct hypotheses that say that, actually, the human mind has evolved and our auditory capabilities have evolved for completely different reasons. And music has just kind of developed to really hack our psychology in a very gratifying way, kind of like a drug. That’s a byproduct hypothesis.

Our work can’t really discriminate among them. But it at least does show that the human mind does seem consistent across societies in how it responds to these different songs.

IRA FLATOW: Now I’m going to play one more group of songs. There was a type of song that people were not good– not as good at identifying. Let’s hear an example.

[MUSIC PLAYING]

IRA FLATOW: Listeners, any idea what type of song that was? That was a love song, a Rwandan love song from Central Africa. It’s a beautiful song.

MANVIR SINGH: I love that recording.

SAMUEL MEHR: Yeah, this is one of our favorites. So Manvir and I are smiling and kind of moving around in the studio here.

IRA FLATOW: Well, send us the rest of that one.

[LAUGHTER]

IRA FLATOW: Any theories on why love songs were so hard to identify for people?

SAMUEL MEHR: Well, so we don’t really know, but there are a few kind of interesting ways in which love songs could differ categorically from the other songs that we studied in this paper.

The first is just sort of a simple explanation, which is just that maybe across cultures love songs are more ambiguously defined than something as straightforward as a lullaby, where I think if you asked a lot of people on the internet what counts as a lullaby, people would kind of converge to things that are soothing for kids and babies and that kind of thing. But love songs are a little harder to define. So maybe the sort of ambiguous results just reflect that.

It could also be that love songs are not defined so much or are not obvious to listeners so much from their musical features but are more obvious because of other things, like the words that are in them.

So there was a really interesting secondary finding in our first experiment where we asked listeners how much they thought songs were used to tell a story. None of the songs in the data set were explicitly that kind of storytelling song. But even so, this measure seemed to pick up love songs. So love songs were highly rated as used to tell a story, which suggests that maybe there’s something about the words of love songs that tell listeners, oh, this is more about love.

IRA FLATOW: There has been some pushback to this study in that these songs are all from small-scale societies, and you played them for online listeners. Do you think this skews the interpretation? Is this just what internet users think of these songs?

MANVIR SINGH: Well, that’s a really, really good point. So all of our listeners are people who have access to the internet and people who speak English. So one can make this response of, oh, so it might only be a very, very restricted population that shares these conceptions of what these songs should sound like. And we’ve taken that criticism seriously, and we are actually expanding our survey to 28 languages. So we’re translating it, for example, into Indonesian and Urdu and Amharic.

But then we’re also taking it to the field. So we’re taking it to, for example, Bolivia or Indonesia. And we have plans to take it to Vanuatu. And we want to play it for people who do not necessarily have access to this kind of globalized contemporary music culture, who will give us a better insight into whether these conceptions are shared by people who have little access to the internet.

IRA FLATOW: In the minute left I have, does anybody have songs about the blues? Do we have common songs about anybody singing the blues?

SAMUEL MEHR: Well, so we don’t have any in the natural history of song discography yet. But one of the other things that we’re doing now that this paper is out is we’re working on expanding the discography to cover more contexts of singing. And a pretty commonly found song type worldwide are laments, which is a fancier way to say the blues.

IRA FLATOW: Yes.

[LAUGHTER]

SAMUEL MEHR: So, yeah, it would be really cool to study those as we expand the data set.

IRA FLATOW: I’m thinking of that song where first they rehearsed it and then nursed it. OK, we’ll have you back when we talk more about the blues. I want to thank both of you for taking the time to talk with us. Samuel Mehr, Research Associate in the Department of Psychology at Music Lab at Harvard, and Manvir Singh, also at Harvard University. Thank you both for taking time.

MANVIR SINGH: Yeah, thanks a lot for having us.

SAMUEL MEHR: Thanks Ira.

IRA FLATOW: You’re welcome.

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