Some members of my family probably still don’t believe that, but well: you can now make livng out of studying animal behavior. There is a non-zero chance that you will get funding for your research on social behavior of mice, song development of songbirds or decision making in sponges.
But before you will pack your instruments and go to Australia to study neurobiology of koala’s sleep, please take a while to recall the harsh history of our trade. Józef Piłsudski, one of the fathers of Polish independence and a grandfather of its fall, said once that the nation that forgets about its history is doomed. And the history of our field is full of misery.
Take Wallace Craig as an example. If your knowledge of ethology is limited to some textbook cliches, you might think that the first person who ever attemted to study instincts was a friendly – looking Nazi that liked to be followed by geese. This is obviously not true; and Craig was one of the persons who came before. He was a student of Charles Otis Williams, another important guy that you most probably don’t know. Craig started his career as a zoologist, yet soon observed that his manual skills were too deficient for a work that required a lot of manual operations. He proceeded to study behavior of pigeons in it’s entirety – from sexual behavior to vocalizations.
He authored a famous paper in which he made an important distinction between apetitive and consumative behavior and criticized tha claim according to which instinctive behaviors are composed of series of chain reflexs. His theories were an important influence for Lorenz.
But his career was a harsh one. At some point he was unable to get a funding for his research; he had to devise a strategy that would allow him to satisfy his research interests and not to die of hunger. Idea was simply – animals whose behavior is intreresting are sometimes also edible. As he wrote to his friend:
“We must keep hens; while I watch their behavior we can eat their eggs, and later we can put the specimens themselves in the pot. I must keep large pigeons as well as doves; we can eat the squabs.”
If you ever played Stardew Valley during your PhD, you know that farming and research are very hard to combine. After a short time Craig wrote again:
“Probably I could maintain a bird farm and make it pay, but it would take every minute of my time […] and I am, after all, more in need of time than I am of money.”
William Craig to C. Adams (Burkhardt, 2005)
He was very unlucky. At some point his main occupations were teaching and studying pigeon vocalizations. Both of them turned out to be impossible to conduct after he started to become deaf. He left the University of Maine in 1922 and died in obscurity in 1954.
His work was immortalized by its incorporation in Lorenz’s theory. What is interesting, Craig himself managed to immortalize an object of his study, a passenger pigeon. This bird, whose population is estimated to reach billions of specimens (historical accounts depict flocks of passenger pigeons so big that their flight over the town was taking a week) got extinct in 1914; the reason being an excessive hunting that should be most accurately described as a massacre. Craig was studying its calls and produced a note transcription of a pigeon’s vocalizations that you might use to recreate the voice of something that do not exist anymore, a feeling similar to one you might have during listening to those reconstructions of ancient greek music that are so unpleasant to listen.
Well, it seems that we are now in a much better position, right? No need to eat your rats; grant agencies will be happy to ensure your survival while you spend your precious time doing research. You are no longer a part of obscure community; neuroscience needs you.
You can now pack your neuropixels, openEphys boxes, hard drives full of open software and go to study your koalas in the wild. Or can you?
Well, it is definitely worth it. You will probably join Wallace Craig and the growing group of scientists whose object of studies became extinct. But in one hundred years your recording of koala’s brain activity might be for next generation just like the notes above: a proof that something you know only from drawings or museum specimens was someday alive and behaving.
Burghardt, G. M., & Burkhardt, R. W. (2018). Wallace Craig’s Appetites and Aversions as Constituents of Instincts: A Centennial appreciation. Journal of Comparative Psychology, 132(4), 361–372. https://doi.org/10.1037/com0000155
Burkhardt, R. W., Jr. (2005). Patterns of behavior: Konrad Lorenz, Niko Tinbergen, and the founding of ethology. Chicago, IL: University of Chicago Press.
The concept of instinct lays exactly in the center of my scientific interests.
It lays here largely because I was naively assuming that is dead for quite a long time – and is there a bigger pleasure than a dissection of dead ideas? Instinct was declared dead many times and for many reasons – that it lacks a clear definition or doesn’t explain anything. But it always reappears, this way or another, just like a monster from a horror movie. And it happened again, this time in debates on AI.
As you may know, AI is achieving amazing things nowadays – it composes some mediocre pseudo-Baroque music, probably outperforms pigeons in detecting breast cancer and is paving a way towards antyutopian, totalitarian hell where everybody is tracked and controlled, just like in some Orwell’s books that I loved when I was a teenager, before I have fortunately grown up*.
AI achieves all these wonders by learning. You show it thousands of pics, train for a few days, emitting more CO2 than Baltic republics in a year, and it will learn how to recognize a potato. The efficiency of those algorithms has led some people to believe that is just enough to let algorithms learn to achieve the Artificial Intelligence at some point. This hope – or threat – is being criticised with the use of none other, but the instinct, the the zombie of concepts, the undead nightmare of behavioral sciences.
The charge is simple – as Antonhy Zador Anthony Zador wrote recently, there are many things that animals do not need to learn. Examples follow:
A squirrel can jump from tree to tree within months of birth, a colt can walk within hours, and spiders are born ready to hunt. Examples like these suggest that the challenge may exceed the capacities of even the cleverest unsupervised algorithms.
His point is clear – we probably should add some innate constraints to our algorithms to achieve the level of intelligence of a mouse, for example, or just to make them more efficient. Animals are not blank slates, maybe neither should our artificial intelligencies. If it is right or wrong I cannot tell, for the last time I used the neural network the result was the rear part of the mouse got recognized as its head.
But what is interesting for me, a simple-minded behavioral scientist, are terms used in the paper. To be fair, Zador does not use the term instinct. What he does is to mention behaviors that are innate. And as innate he will assume behaviors that are created by innate mechanisms that are encoded in te genome; behaviors that are not learned (colt’s walking); behaviors that are present from birth (spider’s hunting), behaviors that develop without tutoring and that are species-specific (making different burrows different Peromyscus species). All those behaviors are described in ethological literature as instinctive – and, as you will see, this richness of meanings will turn out to be problematic.
A Twitter debate that happened a propos a similar discussion on AI by Gary Marcus and Yoshua Bengio was actually also a debate about the instincts and the role of genes, experiences and learning in the forming of animal behavior. Yes, nature – nurture debate is back, my dears. The existence of instincts is now an argument for developing our algorithms in a specific way.
We understand the concept of instinct almost instinctively, and we usually just assume that it is clear and well defined. But what does it really mean that the behavior is instinctive? Does it really have a clear meaning? And should we use it in our scientific debates, either on animal behavior or AI?
The concept of instinct – in this or another form – is very ancient. I am not a historian of ideas, so I will not naively try to trace its beginnings – but let me just say that the modern concept of instinct was formulated in the XX century by Konrad Lorenz. In his 1932 paper, Methods of Identification of Species-Specific Drive Activities in Birds, he says that the behavior is instinctive if it satisfies one or more of five criteria: 1) if it appears in an animal reared in isolation, without any tutoring, 2) if it is performed in a stereotyped way by all individuals of a specie, 3) if there is a striking mismatch between the typical intellectual abilities of an animal and the abilities that it wouldhave to posses to solve a given problem by insight (e.g. relatively stupid bees are able to show their companions where flowers are by dancing), 4) if the behavior can be elicited in an innapropriate context, suggesting that is not performed consciously, 5) if the behavior is performed in a stereotypical way even in context that is dfferent from the one in which it originally evolved. Niko Tinbergen, who together with Lorenz whole field of ethology, described instinct also as highly stereotyped, coordinated movements, the neuromotor apparatus of which belongs […] to the hereditary constitution of the animal.
Yes, we have seen those different meanings of instinct in Zador’s paper and in the Twitter discussion. And Lorenz’ and Tinbergen’s definitions are not the only ones. Patrick Bateson in his critique of Steven Pinker’s book on innateness lists additional meanings:
“Apart from its colloquial uses, the term instinct has at least nine scientific meanings: present at birth (or at a particular stage of development), not learned, developed before it can be used, unchanged once developed, shared by all members of the species (or at least of the same sex and age), organized into a distinct behavioral system (such as foraging), served by a distinct neural module, adapted during evolution, and differences among individuals that are due to their possession of different gene”
I think we can add a few others. People often say that instinctive behaviors are genetically preprogrammed; that they are somehow hardwired in the brain. Sometimes scientists also automatically assume that behaviors crucial to survival – foraging, mating and fear – are instinctive by definition. Instinctive behaviors are sometimes told to be biological, as contrasted with psychological; some people would also probably say that ancient behaviors, ones present in so called lower animals, are also instinctive.
At this point, you might say: well, and so what? Behaviors that are genetically determined do not require learning and are hardwired; they are also species specific and fulfill other criteria as well. So it is absolutely normal that we have different meanings: instinctive behaviors just have many characteristics! And indeed, people very often use different meanings of instinct almost interchangeably; Steven Pinker, for example, does not define it at any point in his whole book on innateness – he just assumes that we knowwhat he means.
But is it true? Do so called instinctive behaviors posess all those characeristics? Are different definitions compatible with each other? Let’s have a look at a few examples.
Let’s start with an easy example and take two meanings of instinct:present from birth and not learned. The two features seem to fit each other perfectly – but is it so? Can animals learn anything before they are born?
All those behaviors are present at birth – and yet all of them are learned! It seems that not all meanings of instinct always peacefully coexist. But let’s take another example – drinking waterwhen thirsty. It is behavior that is crucial to survival; it is obviously present in all individuals of a given specie and is clearly adaptive. But well, it is apparently learned, at least in rats. Rats must learn the association between dehydration and the relief from dehydration achieved thanks to drinking water – without this experience, they will not seek water when thirsty. If you feed them with a liquid food that does not allow them to develop dehydration and then – at some point – dehydrate them artificially by the injection of salt, they will not increase their consumption of water.
As Bateson mentioned, one of the meanings assumes that in case of instincts differences among individuals are due to their possession of different genes. What is interesting, there are behaviors that differ between animals that are otherwise clones, having an identical set of genes. Among identical genetically pea aphids, you can observe differences in they startle behavior – when presented with a loming stimulus simulating a predator, some of them will jump out of the leaf, while others remain feeding. Similarly, individual fruit flies may differ in their thermal preferences. Those differences are stable within individuals. It is true also for bacteria – they exhibit surprisng phenotypic variability even without variability in genotypes.
What is the source of those differences if they cannot be explained by genes? It can be caused by different experiences, but It seems that the development of an organism is stochastic – it is not an execution of a program and even with a smilar starting condition can give variable results; levels of gene expressions in cells may differ due to purely random processes. Positive feedback – e.g. when a gene’s product might enhance gene’s expression – can amplify those random fluctuations, leading to different outcomes. What do we have here are behaviors that are present from birth, not learned, unchanged once developed – but differences between individuals cannot be explained by the difference in genes, though they are for sure biological in origin.
Aforementioned variability brings us to another set of definitions that may not be always compatible – hardwired and highly stereotyped.
I am never entirely sure what does it mean when it comes to neural circuits, but the hardwired circuit is probably circuit that is not variable, that is set very precisely during development by some genetic instructions and that controls behavior. The problem is that neural circuits that produce invariant, highly stereotyped outcome are very often themselves variable. The trength of connections between neurons that control heartbeat in leech vary between individuals, even though the outcome is identical. As authors write in the introduction, each animal arrives at a unique solution for how the network produces functional output.
What shouldn’t be surprising. Individuals are different: they differ in size, strength; they may develop in different environments. The nervous system cannot have one pre-specified, rigid solutions to all problems; it must find a solution that will work in specific circumstances: it must be robust. It reacts to what happens during the development: if you artificially enhance spike production in a neuron in a developing embryo, the cell will respond by decreasing the expression of excitatory and increasing the expression of inhibitory transmitters to keep the proper level of excitation. The resulting variability in connections or ion channel expression is probably a way to achieve consistency in behavior. You can read more about the topic in a paper that Robin Hiesinger and Bassem Hassam wrote on variability and robustness.
Another example will show us that behaviors that are fundamental to survival, ancient and controlled by highly conserved brain region may show unexpected plasticity at the neural level.
In a 2017 article by Ryan Remedios and Ann Kennedy authors imaged neurons in the ventrolateral subdivision of the hypothalamus (VMHvl), a structure that is related to mating and fighting, behaviors expected to be instinctive, at least by the authors of the paper. But they show an interesting thing: when an experienced male mouse interacts with an intruder that is either male or female, separate neuronal populations are activated depending on the sex of the intruder. But in case of an inexperienced male, those populations are overlapping and separate only gradually with sexual and social experience. As the claim at the end of their summary:
More generally, [these observations] reveal plasticity and dynamic coding in an evolutionarily ancient deep subcortical structure that is traditionally viewed as a “hard-wired” system.
Finally, let’s look at behaviors that are present in all individuals – so called universals. The universality of a given behavior is often taken as an indication of its innateness; they are viewed as genetically determined and not learned – how can you expect all animals to develop a behavior if its development would depend on experiences that may differ?
Well, there are experiences that are universal, things that happen to all individual of specie which can be reliably used as a source of information that will guide the development of a behavior that is also universal.
Small mallard ducks follow the calls of their mothers just after hatching – they seem to have an innate recognition of a species – typical call, as they prefer it over calls of other species. But it turns out thet it is learned. Before hatching, when a duck breaks into an air bubble within an egg, it starts to produce its own vocalisations. Gilbet Gottlieb has shown that they learn to recognize calls typical for their species’ mothers by listening to their own vocalisations that share some similarities. If you devocalize ducklings hile they are still in an egg, they will be unable to recognize it.
Listening to one’s own voice is also an experience, experience that is universal and will reliably occur in an every generation – just like a possession of a certain gene.
As you may see at this point, different meanings of instinct may not really compatible with each other; closer inspection shows that it is an incoherent whole. And this incoherence may lead us astray, it may make us surprised by discoveries that are not at all surprising.
This is exactly what happened to the authors of the aforementioned hypothalamus paper. They start with a sentence: all animals possess a repertoire of innate (or instinctive) behaviors, which can be performed without training. And a moment later they write: here we report that hypothalamic neural ensemble representations underlying innate social behaviors are shaped by social experience, just to finish their summary with already quoted fragment, that their results reveal plasticity and dynamic coding in an evolutionarily ancient deep subcortical structure that is traditionally viewed as a “hard-wired” system.
Authors seem to be puzzled by those inconsistencies – we have aninstinctive behavior that is not learned by definition, and yet an ancient structure that controls this behavior is shaped by experience! They openly ask: how can these findings be reconciled with the “innate” nature of mating and aggression?
They try to give some answers – maybe here are downstream areas that are truly hardwired! We just need to find them!
But maybe we don’t really need to? Maybe this whole result is shocking just because we never thought about our hidden assumptions? That an innate behavior must be unlearned and hardwired? Well, in light of what I wanted to show youit absolutely doesn’t need to. We are again misled by our concepts, by labels that have huge historical luggage of meaning and that are not really useful now.
But what should we do? Is really the concept of instinct not clear enough to be useful? Should we drop it? I think yes – it was around for too long, acquiring too many meanings on the way through centuries. Even if we would cleary define it whenever we use it, other meanings may appear anyway in the minds of our readers. When we say unlearned, they will read inborn or universal, what may not be a case.
Should we then coin a new term? New terms can be fun, but they are rarely adopted by people. Biology and other science are full of terms that nobody uses, or uses them in a way completely diferent from intended, just like Dawkins’ memes.
Fortunately, don’t need to do it. We have a term that already exists and is often used to describe many of behaviors we mentioned here. What is more important, this term is free of all assumptions that we associate with instinct – this term is robust behavior. People use it when speaking of behaviors that are stable, occur reliably in a laboratory environment, that may not require too much learning to develop.
If I would like to specify the meaning a little bit more, I would say that robust behaviors are the ones that you can find in most of the individuals of a given specie. They develop in spite of developmental perturbancies; they are usually highly stereotyped. But they can be shaped by experience; they are controlled by specific neural circuits, that can anyway vary between individuals (and sometimes, who knows, might be even controlled by different circuits in different individuals!). Robust behavior does not need to fulfill all those definitions that we attach to the concept of instinct. This concept is just a nice, open and tolerant guy who does not exclude anyone just because they do not obey some artbitrary rules. It gives us freedom, and frees us from artificial surprises that instinct generates, whenever we find unlearned beavior that is not hardwired or vice versa.
This way of thinking is absolutely not new – the whole developmental sytems theory goes more or less on similar lines, although for me it is still slightly too eclectic. There is a wonderful book on the critique of instinct by Mark Blumberg. But as I said at the beginning – instinct is very hard to kill. It will be still hanging around, whatever we do, just because it’s ancient, and this post will of course not change that.
But don’t tell me I didn’t try!
* in fact it was only my wife who convinced me that they are so bad, thanks!
** Wait, wait – you may say. But the world is full of examples of neural circuits that are very invariable! And that’s true – fly eye is an example of a very precise and repeatable wiring. The same for Caenorhabitis elegans , when development seem just like a very precise execution of a program, with all hermaphroditic worms having exactly 302 neurons. But even in those cases invariable outcome is a result of a stochastic process – in both cases during the development cells are going trough a selection process; some will become neurons, some will die – but you cannot predict which ones will survive (look here and here).
When I look through the window of my flat in Warsaw I see a shop. The shop is called Organic; it is full of overpriced linen seeds, nuts and, most interestingly, different kinds of salt. I am not sure in what sense salt can be organic, but I think I know what are the benefits of calling it that way. Organic means biological. Biological, loosely, means natural. And natural means good.
Organic salt is, thereafter, good salt.
Organic salt is just one of the examples of the infamous appeal to nature. For some reason, at least in Western culture, things that are thought to be natural seem automatically good; better than unnatural ones. That belief is the root of natural medicine, some non-vege people arguments (buthumans are carnivores!) and the existence of the Organic shop on the other side of my street.
Things that are natural are also true – that’s why many philosophers believed that only a man in the wild, primitive state is a true human. And that’s why many evolutionary anthropologists study people in tribes isolated from civilisation – because it might tell us something more about the true human nature, one not tainted with the culture that is supposed to run against many of our instincts.
This is also, in my opinion, one of the reasons why people in behavioral neuroscience, including myself, are nowadays becoming fascinated by ethological relevance.
Development of new methods – like miniscopes (for people outside of the field – these are miniaturized microscopes that allow you to image brain activity in a freely-moving animal) – and the constant development and improvement of others (e.g. ephys); methods that are very often open-source and thus cheap, are definitely the main motor of changes in the field. After decades of doing behavioral studies on immobilized, head-fixed animals people are developing paradigms in which the animal is free to move and explore the environment much more eagerly.
But this fascination goes further than just letting the animal go around with a miniature microscope on its head. More and more I hear neuroscientists claim that they are trying to make their paradigms more natural – or, as I said above, ethologically relevant.
Ethological relevance has many faces. It can be as simple a using stimulus that is supposed to mimic a natural one – e.g. a looming black circle that imitates an approaching aerial predator. It evokes an instant escape response in mice; and, even intuitively, reproduces something that probably occurs frequently in the life of wild mice, especially if you compare it to electric shocks that could at best imitate an attack by a very weak electric eel (see figure above).
It can be something more – instead of using a natural stimulus, you can try to create a whole natural environment. You want to study social behaviors? A few years ago you would put a mouse under the mesh cup and let the other one interact with it. If it does, it is social, if it prefers a non-social object (or an empty cup), it is probably not – and maybe even autistic!
Seems silly? Well, it probably is; but now you can do something much fancier – like putting mice for a few weeks in a large, automated cage composed of many chambers connected by tunnels imitating burrows, and study how they interact with each other without even a need of touching them, just like in a device that was developed in our lab.
Even those who are, for methodological reasons, forced to head-fix their animals are trying their best to make their studies a little bit closer to Mother Nature. Andrew Fink and Carl Shoonover developed a virtual burrow. The idea is simple: mice live in burrows and feel safe inside them. Why not put a head – fixed mouse inside of a burrow and do it in a way that will allow the animal to go outside to explore or hide when needed? It can be used to study curiosity, anxiety and who knows what else; and you can still do your two-photon imaging.
As you may have guessed from my title, this essay will be a critique of the ethologically relevant approach. But just to be clear, I want to stress: it certainly has many benefits.
First, there is the question of stress: in the two last examples animals are probably much less stressed than in traditional paradigms, which is always a good thing.
But there is more. Some people argue that paradigms that use unnatural stimuli may evoke unnatural responses in the brain. Mice are not prepared by the evolution to the presentation of white and black stripes on the screen while being immobilized. Their brains might not work as they would if the mice were watching something they usually see in their short lives – and it might be the case (similar problems can be found in fear studies, look here).
Furthermore, behaviors that are instinctive should be possible to see most clearly in natural circumstances in which they evolved. And if many instinctive behaviors are conserved from human to mice (if that order feels weird, read that wonderful paper), you might learn a lot about human behavior studying instinctive behaviors of mice in naturalistic paradigms. And people do that, obviously; all those studies on feeding, fleeing, fighting and mating are here also to help us understand our basic instincts.
These arguments seem to me to be reducible to one simple statement: that by studying more naturalistic behaviors we have bigger chances to study something real. But well, it might not be always true; and here we come to the critique.
We have a strong tendency to believe in a fixed nature of things. Ernst Mayr once claimed that people came up with an idea of evolution so late because of Platonic essentialism – a belief that things have their true essence. As Richard Dawkins put it, if you treat all flesh-and-blood rabbits as imperfect approximations to an ideal Platonic rabbit, it won’t occur to you that rabbits might have evolved from a non-rabbit ancestor, and might evolve into a non-rabbit descendant.
In my opinion, we show the same essentialistic thinking when we describe animal behavior. There is a defined set of behaviors, the natural repertoire, that is specific to mice. Anything outside of this set – like pulling a lever – is un-natural and artificial.; it’s untrue.
In this framework, animals are viewed a little bit like robots, endowed by a designer – in this case, natural selection – with some well-specified functions. If your robot was designed to wash your clothes and make you healthy dishes full of organic salt and linen seeds, you can expect that it will do those things well. You can try to slightly modify it to do some other stuff – like trolling flat Earth supporters on Twitter – but then you cannot expect it do perform perfectly. If it does it, you are lucky, if not – well, life. The most probable result, though, will be some variable, mediocre, unstable performance.
But animals are not robots. They live in an environment that changes, and usually changes quickly. Our beloved laboratory rodents are descendants of animals that adapted to a completely new environment of human settlements, that were itself changing fast. Obviously those animals were evolving; instincts were moulded by the new pressures. But animals also learn how to solve new problems and they are doing it well – just look on the corvids using cars to smash nuts, or blue tits learning how to open milk bottles, or a whole book of such examples. The nature of (many) animals is the lack of a fixed nature.
Animal’s brains are prepared to do new things; they are also prepared to learn how to pull a lever. You can even make a very controversial claim – if an animal is able to learn a task, it is able to learn this task, and it’s using its brain to do that. It means that you can use this task to study how the brain learns – even if at the end of the day you will only know how the brain learns very weird things. Learning very weird things, though, is the stuff that the human brain does most of the time nowadays.
Moreover, the big problem with studying natural behaviors of mice or rats is that we know relatively little about their natural behavior. We have a somewhat cliche image of a wild mouse: it’s small, it lives in burrows, it’s afraid of predators and well, that’s almost all we can say. There are very nice, but quite old books: Mice all over by Crowcroft and, for rats, Rat – a study in behavior by Barnett; we have also recently put some effort to bring together what is known about social behaviors of mice and rats, but we need much more studies on the rodent behavior in the wild to do a really naturalistic neuroscience.
As we discuss in the aforementioned paper, laboratory animals that we use are domesticated animals. And it poses yet another problem. Our lab animals differ in behavior from their wild counterparts. They are less aggressive; their sexual behavior, a supposed pinnacle of instinctiveness, is altered; the way they learn or flee might be also different – natural behaviors of a wild mouse might not be at all natural to a laboratory mouse. You will not learn much about wolf hunting behavior by observing your chihuahua, which is basically a wolf strain, the C57 of Canis lupus*.
Don’t get me wrong: I am a great fan of ethologically relevant studies; moreover, I am trying to do them as well. What I am arguing against is making a dogma of it. I have recently talked with a person who claimed that people doing head-fixed task on rodents are reductionist. They want to reduce en extremely complex phenomenon of learning to the passive process of watching sequences of colorful dots for thousands of times by a poor, immobile mouse.
Nicole C. Nelson in her wonderful book made an interesting point of calling this approach reproductionistic instead of reductionistic. She studied scientists working on mice models of alcohol addiction. According to her observations, they are fully aware of the complexity of the human condition; and they do not want to reduce the socio-psycho-bio-who-know-what-else phenomenon of alcohol addiction to C57 mice drinking ethanol from the bottle. Instead, they want to reproduce some aspects of this phenomenon in mice just to make it open to a scientific investigations. Mouse models of alcoholism have innumerable problems and they will never allow us to study how poverty can make us addicted to alcohol. But they can be to some extent helpful when put in a bigger context of discoveries from other fields.
Those of us who work with immobilized mice watching dots do not usually claim that they will solve the problem of perception. They just reproducing some aspects of perception to make it tractable.
Gustav Flaubert composed a beautiful list of slogans and cliches popular among people of his time. According to it, THE PRESENT AGE should be always denounced vigorously; when somebody talks about ANIMALS, usually mentions that some of them are more intelligent than humans; if you mention PAGANINI, you are supposed to say that his fingers were enormously long.
Flaubert despised cliches. According to him, they are automatic expressions that we say when our thought is lazy; they could have been original or creative when they were said for the first time, but now are dead, they are meaningless. We can have impression that we said something funny, interesting or deep, but it is just a zombie of thought.
An idea of doing ethologically relevant neuroscience, although not new, is still fresh and viable. I am a little bit afraid that by not thinking deeper about what does it mean to be ethologically relevant, when it is advantageous and when not, by designing studies that are naturalistic only superficially, and by dismissing too easily studies that are not, we will turn it into a cliche. Naturalistic could become a mindless label that we will use to easily judge the study. Absolutely absurd paradigm could be then perceived as interesting just because somebody used hiperrealistic robot model of a buzzard instead of an electric shock.
Let’s not go there, let’s think; let’s keep ethological relevance alive as long as possible.
* That’s an obvious overexaggeration; C57 was developed in 1921; dog strains have much longer history. But see Byelayev research on siberian foxes – in this case their behavior and morphology changed very quickly under domestication, so you do not really need many generations to change an animal (but there is some recent criticism of this study, a criticism that made me less eager to tell the story of doglike foxes as my favourite lunch anegdote – look here)