At the beginning there was learning – Part I

The great chain of beings, according to  Didacus Valades (Wiki)

Some stories we tell about the world are just untrue.

Others, much more dangerous ones, are untrue, but well-told. They resonate with our intuitions and preconceptions, and they tend to stick with us like mischievous ghosts.

We do all we can to get rid of them. We ritually distance ourselves from them in the introductions to our papers and books, just to blindly fall prey to them a few paragraphs later. They hide in the language – in metaphors, analogies, and cliche phrases that we use without much thinking.

Let’s take one of the most common ghosts of this type in biology: scala naturae, an ancient concept, according to which all beings can be arranged in a hierarchical structure. God is at the top, of course; then come angels, then humans. Animals (non-human animals, as we would say today) are one level lower, themselves arranged in a hierarchy: lions higher than goats, goats higher than fishes, that are above insects and sea invertebrates, and snakes – this sneaky, malicious creature that cheated first humans – at the bottom. And lower still, plants, with minerals at the absolute bottom.

The development of the theory of evolution in the XIX century (and later changes in our view of life) has put this concept to rest*. The tree of life is no longer hierarchical: it’s circular, and all beings are arranged at the top branches. There are no higher beings, nor lower ones. Everybody knows that, it’s a textbook truism: scala naturae is dead.

Only it isn’t, as Paul Katz observed recently. Every time you see someone mentioning a gene or a mechanism that is conserved from flies to humans – you see a well-hidden example of a scala naturae ghost lurking from behind the words. Lower and higher animals can be still spotted in scientific papers. But it also survives in our theorizing about brain evolution.

As you might have noticed from my previous notes, I’m preoccupied with the topic of instinct. My focus of interest changes with time, though: years ago I was interested in the neural implementations of instinctive behaviours; then I moved to various critiques of the concept itself. Now, as I realized recently, I am mostly interested in why this concept is so sticky, and despite being shown to be empty, it is still haunting papers, books and folk wisdom about behaviour in neuroscience.

What I would like to blame is exactly our scala naturae view of nature, and deeply rooted preconceptions about the progressive nature of evolution in general, and the evolution of learning and behavioural plasticity in particular. In this series of posts, I hope to show you how this concept lies at the core of our thinking about instincts and innate behaviour, and how it makes us blind to facts discovered multiple times – and how we can replace it.

And the main message of my posts will be: there is no hierarchy of behaviours, going from primitive and instinctive to complex, learned, and flexible, that hierarchically evolved one after another. Rather, learning is an intrinsic property of nervous systems that were there from the beginning, and instincts – or, as I prefer to call them, robust behaviours – are rather a specific exception from the rule, an exception that can be achieved in multiple ways, and not – as it is widely believed – by hardwiring those behaviours in the brain.

In this first post, I will set the stage for the deconstruction – I will characterize the old view, discuss its assumption and show that it is indeed still influencing the way we think about behaviour.

Scala naturae, brain and behaviourthe hierarchical view of brain evolution

There is probably no better example of scala naturae thinking about the brain and behaviour than Paul MacLean’s triune concept of brain evolution. As you all probably know, MacLean divided the vertebrate brain into three parts. At the bottom, we can find so-called reptilian brain (Biblical snake winks) – a set of structures responsible for governing basic behaviours necessary for survival – mating, foraging, fleeing, and fighting. Those behaviours are supposed to be ones that evolved early, and – as they are crucial – are supposed to be instinctive and hardwired. Then, on the top of the reptilian brain there lies the mammalian brain, a set of structures that introduced feelings to mammalian successors of emotionless, automatic reptiles – feelings related to parental care and social behaviours, for example. At the top of the tops resides the neocortex, that equipped higher mammals with the ability to learn a complex task, think and develop language in the human branch of evolution.

MacLean’s theory is of course a debunked myth. And yet it is pervasive – 86% of textbook descriptions of brain evolutions contain some aspects of this myth! One (textbook) example that the authors give is quite telling:

The brain’s increasing complexity arises from new brain systems built on top of the old, much as the Earth’s landscape covers the old with the new. Digging down, one discovers the fossil remnants of the past.

Myers and Deval, 2018, Psychology textbook

But it also easy to spot in research papers. As Luiz Pessoa recently noted:

[…] most frameworks of brain organization are heavily centred on the cortex. These descriptions view ‘newer’ cortex as controlling subcortical regions, which are assumed to be (relatively) unchanged throughout evolution.

Pessoa, Medina and Desfilis, 2021

Ghost of MacLean’s theory is hauntingmany recent studies in psychology and neuroscience: in studies on social behaviors, attention, personality, decision making and many more. To give another example (from 2018):

 In the realm of personality psychology, it has been hypothesized that individual differences in primary emotions represent ancient evolutionary foundations of human personality with primary emotions being anchored in the subcortical mammalian brain. These primary emotions drive our behavior in a bottom-up fashion 

Montag And Davis, 2018

MacLean’s theory assumes not only the existence of the hierarchy of brain structures. According to this view, we can create also a hierarchy of behaviours – from evolutionary primitive ones – ones that are crucial for survival, e.g. fighting or feeding, and which are hardwired into lower parts of the brain, through more complex ones (e.g. social behaviors or maternal care) that may be partially learned, up to complex behaviours of humans – the use of language, for example.

This view is so much uncontested that it is sometimes barely perceptible, but you can easily find it in papers especially clearly in the moments of surprise when people’s findings do not align well with this view. Here’s an example of a study that discovered experience-related plasticity in the ventrolateral subdivision of the hypothalamus (VMHvl), a region engaged in behaviors such as fighting and mate recognition. As the authors write:

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.

Remedios and Kennedy, 2017

Another great example is a recent paper on social behaviours; and even the title is telling – Neural circuits of social behaviors: Innate yet flexible. The abstract starts with a claim:

Social behaviors, such as mating, fighting, and parenting, are fundamental for survival of any vertebrate species. All members of a species express social behaviors in a stereotypical and species-specific way without training because of developmentally hardwired neural circuits dedicated to these behaviors.

Wei, Talwar and Lin, 2021

Interestingly, the next sentence is Despite being innate, social behaviors are flexible. We will come back to this interesting contradiction in the next post of this series, for now, it is just important to notice this automatic assumption that behaviours crucial to survival must be innate, hardwired in lower brain regions.

MacLean’s theory focuses on the vertebrate brain. But the hierarchical view of evolution is evident in thinking about the brains of animals in general. There is often an assumption expressed directly or indirectly by many scholars that learned and flexible behaviours are the domain of higher, or more complex animals. Up to the seventies (and the seminal 1976 study of William Quinn, who has show learning ability in Drosophila) insects were viewed as unable to learn; Seymour Benzer was known to display during a lecture a photo from an article in the Washington Post with a face of the fly and a caption Can’t learn anything.

And yet twenty years later, in the late nineteens, and after many papers on learning ability in insects, we still find quotes like this:

Insects have rather a small number of constituent neurons of the central nervous system (CNS) [..] and eventually display rather simple patterned movements; a so-called ‘instinctive behavior’, which principally does occur without memory and learning

Kanzaki, 1996

Yet another twenty years later, with an overwhelming amount of data that shows the richness of learned and flexible behaviours in invertebrates, we can encounter claims in a similar spirit (2019!):

Indeed, most of the behavioral repertoire of insects and other short-lived animals is innate.

Zador, 2019

(Strangely, the author forgot to give us a single reference to support this claim!)

My strawman

Of course, every single neuroscientist asked directly about this scala naturae view of brain and behaviour would not admit adherence to it – and yet it still haunts us in the words and metaphors that are used in textbooks and papers.

Let me create a strawman – I will call it the hierarchical view of brain evolution. Itc combines different aspects of scala naturae-based viewing of the evolution of brain and behaviour as a gradual increase of complexity, which started with simple, hardwired behaviours and then, with an emergence of more complex nervous systems, allowed for learned and flexible behaviours. There are four claims that I would like to ascribe to this view:

  1. Learned and plastic behaviours are costly and require complex neural structures, and thus appeared only later in evolutionary history
  2. Behaviours of “evolutionary primitive” animals are largely innate, and genetically determined.
  3. “Ancient” behaviours” crucial for survival retain their innate nature even in more “complex” animals
  4. This hierarchy is reflected in the brain architecture

To prove the fact that those claims are shared by at least some scientists, I conducted a small survey on neuro Twitter, asking if they agree with three of points cited above. It turns out that around 30% of respondents agree with points 1 and 2, and as much as 64% of my respondents agree with claim number 3!

The results of my cheesy Twitter survey

Surveys on Twitter are of course not a valid experimental philosophy method, yet in my opinion this list captures an idealized summary of ideas permeating our thinking. And they are hard to get rid of, as they adhere nicely to our deeply-held belief about the nature of nature – but don’t able us to reshape our thinking about the brain and behaviour, so that it may fit much better to the knowledge we gathered during last few decades. My aim in this post series is to prove that all those points are not viable – this will be the deconstructive part of my story. But I would also like – constructively – to propose to you another view if evolution, that I call the parallel view of behavioural evolution. The claims of this view are:

  1. Plasticity is an intrinsic property of the nervous system
  2. Learning and other forms of plasticity are ubiquitous, even in the case of “instinctive” behaviours
  3. Behaviours can be canalized, and canalization can be achieved in many different ways
  4. Learning is not more costly than canalization (at least not by default)
  5. The environment is a reliable source of information

In the next post, I will debunk the first three claims of the hierarchical view. Then I will proceed to the last one (especially interesting); just to finish with my attempt at developing the aforementioned parallel view, describing its experimental predictions and implications for our study of behaviour. Stay tuned!


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