Chimps stick grass in their ears to be cool: notes on cultural transmission

grass in ear

1. In 2010, a female chimpanzee named Julie began repeatedly stuffing a stiff blade of grass into her ear. This Grass-in-ear behavior has affectionately been dubbed “GIEB” by the scientists who observed it.

2. Out of a group of twelve chimpanzees, eight engaged in GIEB. In three other groups of chimpanzees found in other locations in the same forest, only one was ever seen to GIEB.

3. The more that an individual associated with Julie, the more likely they were to GIEB.

4. After the inventor of GIEB died – if one could be said to invent a thing like putting grass in one’s ear – two chimpanzees continued to engage in the activity. They were never seen to do it together, let alone put grass in the other one’s ear.

5. A young monkey named Imo once noticed that her sweet potatoes were covered in sand and that if she dunked them in the water they would become clean. Within a few years, every monkey on her island was dunking sweet potatoes. She later learned that if she dunked them in the ocean instead, plunging them in after every bite, they would taste even better. The lesson? Monkeys love seasoned potatoes.

Japanese macaque stone handling

6. Some Japanese macaques like to play with stones, clicking and clacking them, rolling them along their hands, cuddling or pushing or throwing them. This was first invented by a young female monkey named Glance in 1979. Her playmates learned it first, followed by theirs. What began as transmission among friends has transformed into transmission among generations: now babies learn it from their mothers.

7. There are at least 11 mutations of this stone handling behavior, including “Rub With Hands”, “Grasp Walk”, and “Flinting”. These variations appear to be transmitted between tribes of monkeys when males migrate from one to another. Additionally, each generation appears to add complexity as each individual inadvertently contributes some new idea.

8. Monkeys are not the only animals with social transmission of ideas; many other animals do, though it may not necessarily be for the best. When young guppies are learning where to eat, they follow an older fellow to a source of food. Slowly, they learn from the older guppy which route to take to their food. As time goes on, one guppy learns from another and a route is set. However, this can be maladaptive when there is a faster route available: follow the group even if they know there is a quicker way.

9. One can digitize animals and ask how their theoretical equivalents toss around cultural traits. What causes these electronic cultures to die out? Simple: small groups, high mortality, poor transmission, and costly traits. Prestigious traits, or traits with group consensus, die out just as quickly as any other. In other words, a culture held in high esteem is just as mortal as any other.

10. The connections between members of a group aren’t uniformly random. Instead, they tend to form small worlds, where any two members are just a few steps away from each other. Thank you, Kevin Bacon. In any random network, as the set of connections reaches half the number of members, a “percolation” process causes many small groups to begin congealing into one large group. Much can be learned about sociality and culture using these ideas.

11. It is possible to classify social learning mechanisms in ten distinct ways: stimulus enhancement, local enhancement, observational conditioning, social enhancement of food preferences, response facilitation, social facilitation, contextual imitation, production imitation, observational response-stimulus learning, and emulation.

12. A computer tournament revealed that even indiscriminate copying is often better than trial and error learning. Copied individuals will often perform the best available behavior, and the better the behavior the more likely they were to survive. Thus, survival itself made behavior a non-random sample of the best behavior. Individuals were themselves highly useful filters of information waiting to be copied.


Huffman, M., Nahallage, C., & Leca, J. (2008). Cultured Monkeys: Social Learning Cast in Stones Current Directions in Psychological Science, 17 (6), 410-414 DOI: 10.1111/j.1467-8721.2008.00616.x

van Leeuwen, E., Cronin, K., & Haun, D. (2014). A group-specific arbitrary tradition in chimpanzees (Pan troglodytes) Animal Cognition DOI: 10.1007/s10071-014-0766-8

Laland, K., & Williams, K. (1998). Social transmission of maladaptive information in the guppy Behavioral Ecology, 9 (5), 493-499 DOI: 10.1093/beheco/9.5.493

Nunn, C., Thrall, P., Bartz, K., Dasgupta, T., & Boesch, C. (2009). Do transmission mechanisms or social systems drive cultural dynamics in socially structured populations? Animal Behaviour, 77 (6), 1515-1524 DOI: 10.1016/j.anbehav.2009.02.023

Stocker R, Green DG, & Newth D (2001). Consensus and cohesion in simulated social networks Journal of Artificial Societies and Social Simulation, 4 (4)

Rendell L, Fogarty L, Hoppitt WJ, Morgan TJ, Webster MM, & Laland KN (2011). Cognitive culture: theoretical and empirical insights into social learning strategies. Trends in cognitive sciences, 15 (2), 68-76 PMID: 21215677

Round 1: FIGHT

I don’t know about you, but when I was in High School, I was treated to a close-up of more than a few fights (none including me, of course).  If you’d asked me, if those fights were totally random I probably would have said no: the two guys – and it was almost always guys – had something between them which festered for a while before they eventually went at it.

Just like humans, macaques live in extremely social environments.  Also just like people, macaques engage in fights which can be one-on-one or just be a straight-up gang war.  Since we can’t just sit the macaques down and ask them what it was that made them throw down, we can turn to statistics to figure out: what makes a monkey fight?

Jessica Flack studies the patterns and dynamics of social systems.  In a paper from her lab, Daniels et al. examined the statistics of monkey fights.  There are a few ways to analyze this, so the group examined three different possible strategies that the monkeys could be using.  First, they could just go at it willy-nilly; this was encoded in the form of a maximum entropy model – a model that basically assumes there are no correlations unless absolutely required.  This model assumed the only thing important to a fight was how often that particular individual fought.  On the other hand, a monkey could get in a fight because it hated the guts of some other guy, or because it had an ally it needed to defend; this was also examined with a maximum entropy model, albeit one that included the direct interactions between two individuals.  Finally, it’s possible that there are other more complex interactions – your buddy really wants you to go fight for that third guy, even though you don’t really know him.  This was tested with a ‘sparse coding’ model, the specifics of which aren’t actually important here.

What they find is that, just like people, it’s the direct connections that matter.  On virtually every metric, the model that includes the interactions between individuals is better than the one that just assumes random acts of violence.  But not only that, the direct interactions between individuals is mostly what’s important – when you include more than that, the only thing that you can do a better job of predicting is how many individuals there are in a fight in general, though not how big a fight is given a specific individual is in it.  In other words, you recruit your allies, they don’t do recruiting for you.

One of the advantages of using these models is that they can be used to estimate how complex the socialization is.  If one of these chimps wanted to remember the details of every fight with perfect fidelity, it would take 23,500 bits – roughly equivalent to a note written using only 3000 total letters (kind of; letters in words aren’t actually uncertain so it would probably take many more than this).  But if you only need to take into account these correlations, you can compress it to 1000 bits, or only 125 letters, and still do almost as well.  Which means that maybe social interactions aren’t as complicated as you might have thought – there is a lot of structure to them.

Of course, this raises the point that the ‘good’ predictions are only right 15% of the time.  Should we call that a good prediction?  For the complexity of what we’re trying to predict, maybe, but clearly it means that there is a lot more going on than the models let on.  Social interactions happen more than just because of general feelings between individuals; they are likely triggered by specific – or spontaneous – events.  But if a simple model can explain 15% of all of a social behavior in a large group of individuals?  And give an estimate of how complex those interactions actually are?  Well I’d say that’s pretty interesting.


Daniels BC, Krakauer DC, & Flack JC (2012). Sparse code of conflict in a primate society PNAS DOI: 10.1073/pnas.1203021109

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