A bridge too far? Inference and extrapolation from model organisms in neuroscience
David Michael Kaplan
Macquarie University
1. Introduction
Like many other biological sciences, research in modern experimental neuroscience is
heavily reliant on a range of model organisms including but not limited to rats, mice,
monkeys, birds, fish, and insects. The model organism approach is extremely well established
in contemporary neuroscience as a means to investigate the nature of mind and brain.
According to one recent estimate, studies involving non-human animals account for more
than half of all the research undertaken (Manger et al. 2008). Even more strikingly,
approximately forty percent of all studies focus on just two model organisms that are quite
evolutionarily distant from humans – the rat and the mouse (primarily the species Rattus
norvegicus and Mus musculus) (Manger et al. 2008; Keifer and Summers 2016). Given that
two central goals of neuroscience are arguably to: understand the distinctive structure and
function of the human brain; and develop therapies for human brain diseases such as
Alzheimer’s, Huntington’s, and amyotrophic lateral sclerosis, among others, a fundamental
question naturally arises concerning what can be learned indirectly about humans by studying
the brains and nervous systems of non-human animals.
Neuroscientists frequently make inferences about the human brain indirectly by
studying the nervous systems of non-human species (Schaffner 2001). In each case, empirical
findings about some causal process or mechanism in the model organism are used to draw
conclusions about that same process or mechanism in another species (typically humans) or
set of species. This kind of inference is often called extrapolation (Steel 2008). Although the
label is not intended in the strict mathematical sense – of estimating the value (or set of
values) of a variable beyond its observed range – both involve a degree of inferential
uncertainty. But why is extrapolation inherently risky? As others have noted (Burian 1993;
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Steel 2008), extrapolation would be trivial if the model organism and target species were
perfectly similar. Yet it is inevitable that there will be some differences between different
species, especially when separated by millions of years of evolution. Therefore, the challenge
is to articulate how it is possible to extrapolate reliably from model to target even when
differences are known to be present (Steel 2008).
In this chapter, I address the widespread use and justification of model organisms in
neuroscience with a focus on the problem of extrapolation. The model organism approach
promises to provide specific insights into the workings of the human brain and reveal general
principles of neural organization and function. Yet the ability to deliver on these promises
depends on the extent to which the model organisms studied are representative of humans
and other species or taxa beyond themselves. If model organisms are carefully selected and
the assumption of representativeness holds, the approach provides a suitable platform for
generalizing or extrapolating findings to humans and other organisms. In other words, there is
a real but bridgeable inferential gap. As will be discussed in detail in this chapter, the criteria
by which neuroscientists select model organisms are not typically optimized for
representativeness and instead reflect biases of convenience and convention. Consequently,
many studies do not automatically provide a strong basis for extrapolation to humans or other
organisms – it is an inferential bridge too far. After highlighting the main features and
limitations of the model organism approach in contemporary neuroscience, I describe a
different approach – an evolutionary-comparative approach – which, although less
widespread, does provide a sound basis for extrapolating research findings from model
organisms.
2. What is a model organism?
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A model organism may be defined as any species primarily investigated to yield specific
insights into the workings of another species or general mechanisms common to many or all
living things (Ankeny and Leonelli 2011). Importantly, for model organisms to play their
intended role they must be representative of other species beyond themselves. This is what
makes them appropriate and effective experimental surrogates or proxies for the target
species (or target set of species). The fact that model organisms serve in this kind of stand-in
role is also what justifies the label ‘model’, since theoretical models in science are commonly
understood to do precisely that (Ankeny and Leonelli 2011; Frigg and Hartmann 2012;
Weisberg 2013). But this is a matter of ongoing debate as others reject this identification
(e.g., Levy and Currie 2014).
Model organisms can vary along two dimensions (Ankeny and Leonelli 2011). First,
model organisms can vary in terms of the specific phenomenon they are used to investigate
(the “representational target”). For example, the squid was used as a model organism to study
the phenomenon of action potential generation (Hodgkin and Huxley 1952) and the rabbit
was selected to study long-term potentiation (Lømo 2003). The second dimension
characterizes how widely the research findings derived from a given model organism can be
projected or extrapolated to a wider group of organisms (the “representational scope”). The
ability to generalize findings to other organisms is the ultimate motivation behind work with
model organisms, and representational scope captures the extent to which model organisms
are, in fact, representative of other taxa. At one end of the spectrum, representational scope
can be maximally narrow such that findings extend only to a single species such as humans
(e.g., rat models of human neurodegenerative diseases such as Parkinson’s). At the other end
of the spectrum, representational scope can be maximally wide, so that findings from the
model organism extend to all biological organisms. Although it is difficult to identify
examples that are known to be perfectly universal, there are many that approximate this limit.
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For example, the bacteria Streptomyces lividans was used to investigate the structure of the
potassium channel underlying selective potassium conduction (Doyle et al. 1998). In a
parallel study, the same potassium channel was shown to be structurally conserved across
prokaryote and eukaryote domains, demonstrating its wide representational scope
(MacKinnon et al. 1998). Finally, scope can be intermediate such that findings cover some
but not all living things such as all and only mammals or all and only vertebrates.
Although Ankeny and Leonelli (2011) do not highlight the point, these two
dimensions are interdependent. Specifically, one’s choice of representational target
automatically constrains representational scope. For example, if the representational target
for a study is an evolutionarily “late” phenomenon such as vocal learning, this restricts how
widely any subsequent findings will generalize from the model organism because many
species will simply lack the behavioral capacity in question. By contrast, if the
representational target is a phenomenon such as ionic selectivity in potassium channels,
which appears to be highly conserved across organisms, then representational scope will be
relatively wide.
3. Why study model organisms in neuroscience?
Model organisms are studied for two main reasons. First, many of the central experimental
methods in neuroscience involve highly invasive or terminal procedures and therefore cannot
ethically be employed on humans. Indeed, some have argued that this makes them equally
impermissible when used in non-human animals (Levy 2012; LaFollette and Shanks 1997).
But this is a highly controversial debate that is outside the scope of the present discussion.
Second, many model organisms have simpler nervous systems that are more experimentally
tractable than the human brain (Marder 2002; Olsen and Wilson 2008; Haberkern and
Jayaraman 2016). The human brain presents serious scientific and technical challenges due to
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the sheer number of neurons (~86 billion) and synaptic connections involved (~100 trillion).
In light of this daunting complexity, researchers often retreat to the study of simpler nervous
systems such as those of invertebrates with far more tractable and stereotyped circuitry in the
hopes that these investigations will yield highly general principles of neural organization and
function, which can then be applied to more complex nervous systems including those of
humans.
4. Model organism selection in biology: Some initial lessons
It is illuminating to consider first how model organisms are selected in other more established
areas of biology such as genetics and developmental biology. In these fields, model
organisms are often chosen based on convenience, cost, experimental tractability, or some
combination of these. For example, Thomas Morgan Hunt and other founders of modern
genetics selected the fruit fly (Drosophila melanogaster) primarily because it is cheap to raise
in the lab and has short generation times (Allen 1975). It was also desirable to early
geneticists because of its experimental tractability, since it possesses relatively few
chromosomes (four pairs) and observable mutations could easily be induced with the
methods available at the time (Kohler 1994). Importantly, the degree to which a given
organism is experimentally tractable reflects the methods and state of theoretical knowledge
available at a given time. For example, what counts as a model organism with experimentally
tractable genetics has changed considerably with the genomic revolution and the emergence
of sequencing and other tools.
Similar considerations drove the selection of the roundworm (Caenorhabditis
elegans) as the model organism of choice in molecular and developmental biology. Nobel
prize-winning molecular biologist Sydney Brenner recounts searching through zoology
textbooks to identify candidate model organisms satisfying a checklist of explicit criteria
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including having a rapid life cycle; a tractable reproductive cycle and genome; and a small
body size so that structures of interest would fit under an electron microscope objective
(Ankeny 2001). Analogous considerations underlie the introduction of inbred mouse lines in
genetics (Rader 2004).
This basic pattern of selecting model organisms based on their convenience and
experimental tractability has been elevated into something of a guiding principle in
experimental biology (Krebs 1975). Named after August Krogh, the Nobel-winning
physiologist who expressed the idea in a lecture many decades ago, Krogh’s principle states
that “for a large number of problems there will be some animal of choice, or a few such
animals, on which it can be most conveniently studied” (Krogh 1929: 202). Importantly, as
the principle implies, precisely which organisms will turn out to be “most convenient”
depends both on the specific research question being asked or phenomenon being
investigated (the representational target) and the experimental methods available to carry out
the study (Burian 1993). As the above examples indicate, this principle codifies a basic
working assumption in contemporary experimental biology.
5. Model organism selection in neuroscience
Unsurprisingly, the adoption of particular species as model organisms in experimental
neuroscience also reflects similar considerations. For example, the squid (Loligo forbese) was
selected as an ideal experimental preparation to investigate action potential generation and
propagation (Hodgkin and Huxley 1952). Tissue from Loligo axons remains physiologically
responsive for many hours, making it highly convenient for extensive experimentation. But
the main reason the squid axon was chosen was because of its size, which is among the
largest known in the animal kingdom (Hodgkin 1976). This made it tractable to perform
critical intracellular recordings of the membrane potential without damaging the cell. Given
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the state of intracellular recording techniques available at the time, this goal would have been
out of reach in smaller experimental systems.
For similar reasons, early groundbreaking work on neural excitation and inhibition
was carried out in the lobster and crayfish, and the choice of organisms was firmly grounded
in considerations of experimental tractability. In the introduction to an early paper, Kuffler
writes: “[t]he greatest advantage of the present preparation lies in its accessibility, since all
cellular components can be isolated and visually observed” (Eyzaguirre and Kuffler 1955:
87). Kuffler chose the invertebrate preparation because it was well suited to investigate the
experimental questions about neural signalling he was addressing.
Many other studies involving different invertebrates have yielded major insights in
neuroscience largely because these organisms have tractable nervous systems that are readily
functionally and structurally dissected (Marder 2002).
Although vertebrates and especially mammals are generally less convenient to work
with than invertebrates – having longer generation times, more demanding housing
requirements, higher costs to maintain, increased ethical concerns, etc. – sometimes the
phenomena neuroscientists seek to understand are simply absent or difficult to discern in
lower-order taxa. As described above, there is no invertebrate model for vocalization
learning. Therefore, vertebrates and especially other mammals with more broadly similar
nervous systems to humans and similar behavioral and cognitive capacities are necessary for
many of the research questions neuroscientists are trying to answer (e.g., what is the neural
basis of language, semantic memory, etc.).
As a general rule, for any given phenomenon, neuroscientists will try to study it in the
simplest organism known to exhibit that phenomenon. Indeed, this is likely why most
neuroscience research involving mammals uses the mouse or rat model whenever possible
(Manger et al. 2008), and only rarely involves non-human primates. Indeed, this is
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demonstrated by the current trend towards using mice and rats to study complex phenomena
traditionally investigated in primates primarily because they have smaller more
experimentally tractable nervous systems. In addition, powerful new methods including
optogenetic are currently available in rodents, but these methods (at least so far) have proven
less reliable in primates (Diester et al. 2011).
6. Assessing the prospects for extrapolation
Given this haphazard manner in which model organisms are typically selected in
neuroscience, what are the prospects for extrapolating findings to other organisms including
humans? One worrisome fact is that major failures of extrapolation routinely occur (e.g.,
Schnabel 2008). Yet many researchers working with model organisms have failed to take
notice, leaving a broad consensus about the representativeness of model organisms largely
unshaken. Neuroscientists frequently assume that research involving model organisms can
reveal highly general even universal insights into the structure and function of all nervous
systems. For example, neurobiologist Eve Marder claims that invertebrates such as
crustaceans “provide ideal platforms for the study of fundamental problems in
neuroscience…[and] to uncover principles that are general to all nervous systems.” (2002:
318). Surprisingly, she provides no evidence in support of this claim, but instead seems to
assume a degree of similarity between the model organism and the intended target of the
extrapolation that ensures the extrapolation will go through and general principles can be
revealed. These assumptions appear to be widely embraced (e.g., Churchland and Lisberger
2015; Ahrens and Engert 2015; Nussbaum and Beenhakker 2002). For instance, many
researchers studying mammalian model organisms (e.g., rodents or non-human primates)
often simply assume that all mammalian brains are highly similar and that the cerebral cortex
in particular is essentially invariant in its internal organization across species (Rockel et al.
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1980; Preuss 1995, 2000; 2010). This assumption that brain evolution was highly
conservative across mammals justifies the liberal investigation of any particular mammalian
species as broadly representative of the class including humans. Indeed, Logan (2002) argues
that the presumption “that nature might not be so diverse after all” combined with an “a priori
expectation of generality” are hallmark commitments of the model organism approach in
biology more generally. So it should come as little surprise that neuroscientists also
frequently accept these assumptions.
Importantly, this way of thinking was not always prevalent. For example, even though
the use of Drosophila soon came to dominate research, early investigations of the
mechanisms of inheritance in classical genetics involved a large variety of organisms (Davis
2004). And it was only in virtue of the appreciating how the rules of inheritance were
observed across many organisms that the generality of the findings from any particular
experimental organism were established (Davis 2004). Accordingly, generality is an
empirical conclusion to be reached by examining data from many species, and the
appropriateness of a given model organism for extrapolation is an empirical hypothesis that
must be supported by evidence (Logan 2002; Steel 2008) According to this strategy, a causal
relationship or mechanism found in a given model organism is inferred to hold approximately
in the target system in proportion to the available empirical evidence (Steel 2008).
In treating the representational scope of model organisms as a default or a priori
assumption rather than an empirically supported conclusion, these researchers adopt what
Steel (2008) refers to as the strategy of “simple induction”: infer that a causal relationship or
mechanism found in the model organism holds more or less approximately in other related
systems unless there is some reason to suppose otherwise. Simple induction is problematic
because it can frequently lead to mistaken extrapolations and provides no guidance when
there is reason to suspect the extrapolation might be incorrect (Steel 2008). But why think
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this is inferentially precarious in neuroscience? The general worry lies in the diversifying
nature of evolutionary change, which poses a challenge for freely extrapolating findings from
one species to the next. This concern is well expressed by Burian (1993): “Evolution is a
branching process in which each organism (each lineage, each species) has distinct
characters, differing in some ways at least from the organisms (lineages, species) from which
it stemmed…At (virtually?) all levels of the biological world - including the biochemical - it
is an open question how general the findings produced by the use of a particular organism
are.” (1993: 365)
In light of considerations of this sort, a growing number of scientists and philosophers
have started to emphasize the importance of evolutionary considerations when choosing
model organisms and extrapolating from them.
7. Towards an evolutionary-comparative approach in neuroscience
Given its proximity to other areas of biology, the lack of a role for information about
evolution in shaping model organism choice in neuroscience is puzzling. If the goal of
studying model organisms is to provide a platform for generalizing to other organisms
including humans, then surely information about the phylogenetic relationship between the
model organism and the target species must guide selection (Preuss 1995, 2000, 2004;
Hedges 2002). Strikingly, neuroscience is not alone in this regard; evolution is also neglected
in many areas of biology (Bolker 1995, 2012). Discussing the situation in developmental
biology, Bolker argues that “[p]hylogeny is rarely or never a factor in the choice of model
systems” (1995: 453), and she highlights how biologists will sometimes even actively avoid
species known to occupy critical branch points or nodes in the phylogenetic tree if they are
difficult to work with experimentally (Bolker 1995: 453).
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Adopting an evolutionary-comparative approach offers a unifying framework in
which to understand the similarities and differences among organisms. Information about
interspecies similarities reflecting the phylogenetic relationship between model organism and
target species (i.e., homologies) can help to empirically ground extrapolation. Similarities are
required because if the two species differed in every respect, nothing could be learned about
one by studying the other. And common evolutionary descent is a major source of similarities
between species that can underwrite the reliability of extrapolation. As Marcel Weber puts it:
“[t]he usefulness of model organisms crucially depends on the extent to which the
mechanisms in question are phylogenetically conserved. Any extrapolations from model
organisms are only reliable to the extent that the mechanisms under study have the same
evolutionary origin in the model organism and in humans” (Weber 2004: 181; author’s
emphasis). Consequently, information about its evolutionary history and phylogenetic
relationship to other species can provide crucial guidance to help ensure the
representativeness of a model organism.
The evolutionary-comparative approach also offers a useful perspective on, and
appreciation of, interspecies differences. Whereas the model organism approach presumes
similarities between the brains of different species (and minimizes differences), the
evolutionary-comparative approach embraces the diversity among species produced through
evolutionary change. Specifically, the nervous system of every potential model organism is
understood as reflecting its own unique evolutionary history, which makes it likely to vary in
important respects from the human brain.
From this perspective, is neuroscience investigating the right model organisms? First,
let us reconsider the widespread rodent model. As indicated above, the last common ancestor
between rats and mice and humans was approximately 90 million years ago (Figure 1). This
is a considerable amount of time for independent brain evolution to occur. Given that the
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structural (molecular, cellular, and regional) organization of mammalian brains provide a rich
platform of variation on which natural selection can operate, it is probable that changes in
brain organization have independently accumulated in human and rodent lineages. Although
there are many known similarities in brain organization (including cortical organization)
between rats and mice and other mammals including humans, many important differences are
also known (Preuss 2000). This presents an obvious challenge for extrapolation and raises
important questions about whether the heavy focus on the rat and mouse is justified. It also
elicits more general concerns about whether the model organism approach in neuroscience
offers a promising way to gain insights into the workings of the human brain and discover
general principles of nervous system structure and function.
[FIGURE 1 ABOUT HERE]
Next consider the use of non-human primates as model organisms. Humans and
macaques (the dominant primate species studied in neuroscience) diverged over 20 million
years ago, and therefore have about 40 million years of cumulative independent evolution
between them (Figure 1). The standard view in neuroscience is that findings derived from the
macaques readily transfer to humans since their brains are largely the same and share the
same general design. But the macaque brain cannot simply be viewed as a scaled-down,
ancestral version of the human brain (Herculano-Houzel 2012; Rilling 2006), since both
humans and macaques have evolved in response to different selective environments in the
time since they shared a common ancestor. This implies that caution should be exercised in
extrapolating from monkeys to humans. Similar cautionary notes can be sounded for many
other model organisms widely used in neuroscience today.
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The evolutionary-comparative approach does more than raise critical challenges for
many standard model organisms; it also helps refine the selection of model organisms. This is
best illustrated by example. As mentioned earlier, long-term potentiation (LTP) and its role in
memory was initially discovered in rabbits and then extensively studied in rodents (Lømo
2003). Of course, the ultimate goal of these studies was to infer something about the role of
LTP in human memory. Yet these model organisms were selected for study largely because
of their convenience and availability, without any detailed examination of their phylogenetic
relationships to humans, and any conclusions drawn about humans were based on the
presumed similarity between rabbit, rodent, and human brains (Section 6). But if the goal is
to extrapolate these findings to humans, close attention must be paid to phylogeny, and a
critical gap to fill is therefore to demonstrate LTP in a closely related non-human primate
species such as the macaque. Eventually such studies were carried out in area CA3 of the
macaque hippocampus, and LTP was confirmed to be similar to what was previously
reported in rodents (Urban et al. 1996).
If, by contrast, the objective is to establish LTP as a general principle of memory
storage that extends beyond mammalian brains, demonstrating its evolutionarily conserved
role across a wide range of animal lineages is critical (Figure 1). Along these lines, LTP has
recently been demonstrated in invertebrates like Aplysia (Lin and Glanzman 1994). Generally
speaking, understanding which characteristics of model organisms are common to other
species, and determining exactly how widespread any particular characteristic is (i.e.,
whether it is shared by all mammals, all vertebrates, or all animals) requires detailed
comparative evidence from a number of other carefully selected species and can never be
established by investigating the model organism alone. The broader lesson here is that since
neuroscientists cannot study every single species, model organism selection must be
optimized by paying close attention to evolutionary history. Doing so promises to improve
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the representativeness of the model organisms that are chosen in neuroscience, which in turn
stands to improve the reliability of extrapolating findings to humans and other species.
8. Conclusion
The model organism approach affords a potentially promising way to gain insights into the
workings of the human brain and discover general principles of nervous system structure and
function. Yet the power of this approach to reveal such insights and principles depends on the
extent to which the selected model organisms are representative of other taxa beyond
themselves. Therefore, when the goal is to generalize or extrapolate findings based on model
organisms to other species including humans, the choice of model organisms must be guided
by more than mere convenience and convention. The evolutionary-comparative approach
provides additional phylogenetic criteria for selecting model organisms that are optimized for
representativeness. Consequently, it provides a more solid foundation for extrapolating from
model organisms than the traditional convenience- and experimental tractability-based
approach to model organism selection which remains widespread in neuroscience. With the
increasing availability of genomic data and sophisticated tools for comparative analysis and
phylogenetic reconstruction, the time is right to reconnect neuroscience with its evolutionary
biological roots. One natural place to start this process is with the choice of model organisms.
Careful consideration of a candidate model organism’s evolutionary history – especially its
phylogenetic relationships to humans and a range of other species – can improve its overall
representativeness, which can in turn improve the reliability of extrapolation. Channeling the
famous words of the eminent biologist Theodosius Dobzhansky (1973): Nothing in
neuroscience – including how findings are extrapolated from one species to another – makes
sense except in the light of evolution.
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Figure 1. Phylogeny of animals based on genomic data. Relationships and divergence
times (millions of years ago (MYA) ± one standard error) for a selection of model
organisms are shown. (Source: Hedges 2002)
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