Our lab communicating our science to you.
This post was written by Sharome Bhatti, Rohan Arul and Katy Bourne, work experience students who have been at the ICN for the past week and a half.
Working at ICN isn’t like anything we imagined. All of our teachers warned us of dull, repetitive tasks that would have to be performed to the best of our ability, in order for us to have the opportunity to get on to the more noteworthy assignments. However, we soon discovered upon our arrival that this was not to be the case. Every day we had something new and fascinating to do, this ranged from doing wall sits with a comedian to grouping data about what makes people laugh and cry. This is what we found...
We asked a random sample of people to tell us what personally made them laugh and what made them cry. A large variety of answers were given, from laughing about funny cat videos to crying about KFC running out of food! After collecting this data, we grouped similar statements together, into groups such as social media and family. Then we used these groups to create wordles that clearly show what groups made people laugh or cry the most.
As we can see from the picture below, comedy mechanisms are by far the most common cause of laughter. This group included irony, sarcasm and puns. The odd thing about laughter is that every person has their own little thing that makes them laugh. Sometimes it’s something completely random that no one else finds funny, because of this we ended up with a lot of isolated groups.
The wordle for things that make people cry was a lot more interesting. The largest group here was a lot larger than the largest group in the laughter wordle. Therefore we can see that the suffering of others causes a greater number of people to cry. This group included problems such as world hunger, poverty and war.
These examples were all collected as part of a Live Science event that we ran at the Science Museum, London.
We're the Speech Communication Lab at the Institute of Cognitive Neuroscience, UCL and we're interested in how mastering a complex skill (like playing the guitar or beatboxing) changes the way brains respond to sound. Other groups have shown that dancers's brains react differently to non-dancers when they see dance. However, does the same apply to different forms of music? We're eager to find out!
So, if you're a professional guitarist or beatboxer based around London, we'd very much like to hear from you! Feel free to get in touch using the form below, reach out to us on Twitter, or email us. This project is being run by Dr. Saloni Krishnan (@salonikrishnan, firstname.lastname@example.org) and Prof. Sophie Scott (@sophiescott, email@example.com).
To design this project, we've collaborated with two incredible musicians, Reeps One and Darren Loveday. You can see some of Sophie's previous work with Reeps One here:
If you decide to help us and meet our safety criteria, we'll invite you to come and be scanned at our neuroimaging centre (Birkbeck-UCL Centre for Neuroimaging, 26 Bedford Way, London). The session takes about 2-3 hours. You'd be in the scanner for about an hour, during which time we play you some music and other sounds. We can pay reasonable expenses for your time (and maybe even give you a picture of your brain!).
We are recruiting for a study with people who stammer - please see here for more information!
It’s been a great year for neuroscientific investigations of domestic dogs. A study in April compared brain responses in dogs and humansusing fMRI (requiring the dogs to lie still I the scanner, to command). This showed that humans and dogs both activate the superior temporal sulcus when they hear emotional vocalizations from dogs and humans, though both species showed an enhanced neural response to calls from their own species. A study hasjust been published using human speech, showing that dogs will preferentially turn to present their right ear to the sounds if they are presented with speech with emphasized segmental (phoneme) information, and with their left ear if the speech has exaggerated pitch (intonation). This is interpreted as indicating that, as in humans, dogs process speech preferentially with the left side of the brain, and intonation in the left (there's an example here).
This kind of study – looking at head turning preferences as an index of hemispheric lateralization – is made possible because of the ways that nervous systems decussate – cross from one side of the body to the other. For example, when I look at the world, the information from the left hand side of both of my eyes (the left visual field) is all sent to the right side of the brain, and vice versa. Likewise in motor control, the left side of my brain controls my right hand and vice versa. Unlike the visual system, the incoming information from the auditory system does not completely decussate, but there is enough dominance of this left to right and right to left pathways that it can be used to find hemispheric asymmetries. Humans are better at listening to speech if it is presented to the right ear, for example, indicating that (for the majority of people) the speech is preferentially processed in the left side of the brain, a finding that is consistent with what we know from patient studies, functional imaging, and studies of which ear people like to hold a phone to. Head turning paradigms are exploiting the same relationship – the idea is that the participant will turn the preferred ear to the sound. So turning the right ear to speech indicates that there is preferential processing of speech in the left hemisphere.
The head turning paradigm is useful as it lets us look at lateralization in animals –such as dogs – whom we can’t ask to make overt responses (e.g. an test for an ear advantage), and this has formed an important tool in studies ofnon human hemispheric specializations.
It’s always good to test the extent that we can assume paradigms are testing what we think they are testing, and a study a few years ago investigated head turning preferences in humans. Their logic was that this is often used as a way of inferring hemispheric asymmetries, and given we know that humans do have lateralized brain responses, do they show a head turning preference? They went out and tested over two hundred German participants with both speech and non speech sounds, and they found that there was no evidence for a right ear dominance when people turned to listen to speech sounds. Indeed, there was a significant tendency to turn the left ear to all the sounds, suggesting that there is a right hemisphere dominance for listening to sounds, generally. Notably, another study in which people (I'm paraphrasing) went round noisy night clubs and muttered at people reported that participants most frequently presented their right ears in an attend to clarify what was being said. But this is not exactly the same as the straightforward head turn paradigm.
This doesn’t mean that the recent dog study isn’t revealing a truly lateralized response – but it does mean that we need to bear in mind that head turn preferences can reflect something more complex.
We have had three wonderful work experience students in our lab for the past two weeks, and they've written a great piece on the work they've been doing for some of our laughter research:
Figure 1- Participants’ answers to the question ‘what makes you laugh?’ The bigger the word, the more frequently mentioned it was.
When we secured a work experience placement at UCL, we expected to receive menial tasks, for example having to make tea or coffee and photocopying. Yet on the very first day of our placement we were handed 2 carrier bags, full of pieces of paper with the word poo (alongside creative doodles) on them. This was the data collected by the laughter lab, who have been investigating over the last few years what made people laugh.
The results were gathered in July 2012 and March 2013, which essentially gave us a snapshot of that period. The high frequency of Miranda [Hart] could possibly be due to the peaked interest in 2012 after the 3rd series of her self-titled show was released . Similarly, the Harlem Shake  went viral in early February 2013, which could explain why quite a few people submitted the dance meme as a suggestion. Another unexpected answer was Mr Bean; which we initially thought was due to the young age of our demographic. We later realised that in July 2012, he performed in the Opening Ceremony of the London 2012 Olympics , viewed by 27 million UK viewers. It is fair to assume that our results are somewhat dependent on popular culture events of the time.
Figure 2- Percentage of categories once the answers had been classified.
Our transcriptions were put into various categories depending on what they entailed. Each transcription was tagged with a maximum of 3 key words. For example ‘Dad falling over’ was categorised as ‘friends/family’ and ‘schadenfreude’. Others were harder to categorise such as people just writing “everything” – we classed these as anomalous results and ignored them, excluding them from our final results. After our initial classification, we refined our data by reducing the amount of categories we had. For example we originally had ‘injury’ and ‘violence’ as two separate categories and we later decided to merge them into ‘schadenfreude’.
We have sorted through data ranging from ‘flowers and snowflakes under a microscope’ to ‘Sachin’s coconut head’. These suggestions and others lacked sense and so were harder to classify; we assumed they were private jokes thus tagging them as ‘jokes’ and a number were censored due to inappropriate content. Several participants also wrote down what they liked rather than what triggered laughter within them i.e ‘I love One Direction’. A handful of answers referred to other answers such as an arrow pointing upwards or ‘this’. Due to not having the original layout of the boards, these answers could not be used in our final data.
If you look at figure 3, common answers included celebrities such as actors, Youtubers and comedians. 38% of celebrities mentioned were comedians, with the jolly Miranda Hart dominating this category. One of the most interesting findings was the significant number of people whose laughter was provoked by social interaction. For example it is quite clear from the figure 1 that ‘friends’ and ‘people’ appeared as the majority. This is further reinforced by the high percentage (24%) of answers that were categorised into ‘friends/family’.
Lucy Kent, Haafizah Khodabocus and George Ponniah Work experience students from Graveney School
 Miranda Hart http://www.youtube.com/watch?v=HFUj5GqTArU
 Harlem Shake http://www.youtube.com/watch?v=iGCy2zp4XuA
 Mr Bean Olympic Cameo http://www.youtube.com/watch?v=BSg_AvqF0qU
Check out Sophie's piece about the difficulty of studying laughter, featured on the Guardian website!
Videos from the article:
Here are some recent (and not-so-recent) videos of Sophie Scott's talks and stand-up comedy routines about Laughter!
2010 UCL mini-lecture about the neuroscience of laughter
2012 TEDxImperialCollege talk
2012 UCL mini-lecture about learning to laugh
2012 Sophie on James May's "Things You Need to Know - The Brain" (S02E02)
2013 Sophie on "Some Boffins with Jokes" - BBC Four
2013 UCL Lunch Hour Lecture - LOLZ! The science of laughter
here is the Random Acts film about our work with Reeps One
the behind the scenes footage is here
the film was made by I Owe Youth which makes the Speech Communication Lab happy as we like puns.
We recently helped with the filming of a Channel 4 Random Acts film with beatboxer Reeps One - there is a shot behind the scenes film here. We'll post a link to the final film shortly!