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The Future of Animal Behavior Research? How an Automated Device Can Address Questions in Cognition

Julie Morand-Ferron tells me about some of her recent discoveries in bird behavior using an automated device

This article was published in Scientific American’s former blog network and reflects the views of the author, not necessarily those of Scientific American


As part of my series of interviews with female animal behaviour researchers, in this post I’ll be interviewing Julie Morand-Ferron. Dr Morand-Ferron is an assistant professor at the University of Ottawa in Canada, who works on how cognition is shaped by the animal’s environment. Dr Morand-Ferron did her PhD at the McGill University in Canada and since then has worked both in Canada and in the UK on a range of topics, from innovation to social learning and culture, in both captive and wild birds.

One problem that animal cognition researchers face is how to test wild animals in a controlled in a way that informs us about their behaviour. It’s generally much easier to study cognition in captive animals, which is perhaps why the vast majority of studies on cognition are in the lab. However, looking at cognition in animals reared in captivity, or even testing animals that are caught in the wild and brought into the lab, does not necessarily reveal how an animal behaves under natural circumstances. If we wish to gain a true understanding of how wild animals behave and vary to each other, it is important to test wild individuals. However, this can carry its own suite of problems: wild animals can be difficult to track down, or become stressed if captured temporarily for testing. Therefore, researchers who wish to study animal behaviour and cognition in the wild have to come up with clever techniques to get at specific questions. One recent publication by Julie Morand-Ferron showcases a novel technique of addressing associative learning in great tits. Here I ask Dr Morand-Ferron some questions about this novel technique and what she found using it.

How does your device work?


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The basic principle is that of a Skinner box – an operant device that comprises buttons that can be pushed to register a response by an animal upon display of coloured lights. However with our device, instead of placing the animal inside the box in the lab, we place the box in the natural habitat and leave animals to interact with it.

The box is interfaced with a Radio-Frequency Identification (RFID) reader which detects the unique ID of birds visiting the device via a passive integrated transponder (PIT tag) embedded in a plastic leg band. This allows for individuals to go through the successive stages of a user-defined learning program at their own pace, with data on failed and successful trials being recorded automatically by the portable, battery-operated device.

What kind of information were you able to collect in this study using your device?

The first dataset we collected examined individual predictors of learning rate in a very simple test: 3 colours were displayed simultaneously on 3 buttons, with the spatial location of each being randomly chosen at every trial. Pecking the red-lit button gave access to a mealworm from a rotating feeding wheel, but pecking yellow or green resulted in no reward and a 15s delay until the next opportunity to register a choice. At first, individuals had to explore the device and performed at chance level (see video 1). However over repeated visits to the box, birds became more and more accurate in their choices, with some of them eventually mastering the program quite efficiently (see video 2).

Video 1:

Video 2:

Interestingly, juvenile birds were much more likely than adults to visit and use the device, and tended to learned faster too. Whether this is due to higher plasticity in foraging strategy, or more investment in learning due to the fact that juveniles can be excluded from more traditional resources by adults (who are dominant over them), or have a longer time horizon to use learned skills, remains to be investigated. Individuals who were previously successful in a novel foraging problem in captivity were also faster learners in the wild compared with those who didn’t solve the captive task, suggesting these individuals may have been better able and/or more motivated to learn new foraging tasks in a range of ecological contexts.

Why is the ability to learn associations important for wild birds?

All animals, including invertebrates, are able to associatively learn – this suggests it is a very important ability for most species. In songbirds, learning is important, for instance, in recognising and avoiding predators, responding adequately to mates and competitors, and deciding whether to look for food or scrounge from other foragers (which was the topic of my postdoc at The Université du Québec à Montréal). While the principles of learning have been heavily studied for several decades by psychologists, much remains to be done to understand when learning abilities are naturally or sexually selected in the wild. I hope that the development of modern technologies will provide new avenues of research to further our understanding of the adaptive value of learning.

Do you think similar devices could be used to look at learning in other species?

I certainly hope so! I expect that species exhibiting low neophobia or high curiosity towards new objects in the wild, and which can be marked to allow automated individual identification by the device would be potential subjects. One useful concept from our device that could be applied to other study systems is that the buttons on the front panel are made up of clear plastic containers. These containers can be opened to insert food rewards that act as attractants for wild animals, but that can never be eaten and depleted, thereby providing the same appealing stimulus for all visitors.

What kinds of questions would you like to ask in the future using this technology you developed?

For the moment I’m mainly interested in investigating causes and consequences of variation in learning performance in natural populations, so as to understand why individuals differ in how and how well they learn, and when higher or lower learning abilities lead to fitness benefits. This is quite challenging, due to the necessity of collecting data not only on learning performance, but also on other individual characteristics that can affect learning or fitness (e.g. personality), as well as life-history traits… I thus expect it will keep us busy for several years to come. I’m also interested in the impact of the social (e.g. group size and composition) and ecological (e.g. habitat, predation risk) context on learning, and in the decision to go ahead and collect new information that may lead to learning or innovation vs. relying on usual, already known behaviours.

What are some of the problems and pitfalls you’ve encountered working with birds in the wild?

One of the issue with voluntary learning trials in the field is that some birds are very good learners and tend to use the box a lot, leaving little opportunity for others to use it. It is thus important when working with social species to use several replica at a given site, but this still results in only a portion of individuals taking part in an experiment. In a new dataset collected in France (Cauchoix et al. in prep.), we have found that participation rates in field and captive trials using these learning boxes are very similar, and thus what I was seeing as a drawback of field trials may in fact be an inescapable reality of cognitive testing, i.e. not all individuals are willing to participate.

What advice would you have for someone just starting a career in science?

In my opinion it is important to choose research topics that are of interest, that spontaneously appeal to us. For me that meant moving to a new university at every step of my career, so that I could join a lab where I would learn new skills necessary for me to address the questions for which I really wanted an answer. That way, even when experiments failed or results were disappointing, I could find the energy to start anew, or write up the results so as to communicate as effectively as possible with my peers, and keep going. I am also never afraid to ask a lot of questions, to contact other researchers for advice when I’m not able to find a solution myself. Doing so I discovered that most scientists are extremely nice, passionate people who are willing to take time to help others, which makes me proud to be part of this community. If you are not able to reach for your dream project at some point in time, write it up and keep it handy for the future, as the right opportunity may arise sooner or later… I was a PhD student when I realised there were still no measurements of selection on any cognitive trait, and that this needed to be addressed but couldn’t see how. Five years later I was moving to Oxford University to try and address this gap, and am still pursuing this aim with my students and collaborators now that I have established my own lab at the University of Ottawa. Strong interests tend not to fade with time!

Reference

Morand-Ferron, J., Hamblin, S., Cole, E. F., Aplin, L. M., & Quinn, J. L. (2015). Taking the operant paradigm into the field: associative learning in wild great tits. PloS one, e0133821.