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Convergent evolution of complex brains
and high intelligence
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Gerhard Roth
Brain Research Institute, University of Bremen, 28334 Bremen, Germany
Review
Cite this article: Roth G. 2015 Convergent
evolution of complex brains and high
intelligence. Phil. Trans. R. Soc. B 370:
20150049.
http://dx.doi.org/10.1098/rstb.2015.0049
Accepted: 31 July 2015
One contribution of 16 to a discussion meeting
issue ‘Origin and evolution of the nervous
system’.
Subject Areas:
neuroscience, evolution, cognition
Keywords:
brain evolution, intelligence, mushroom
bodies, vertical lobe, mesonidopallium,
cerebral cortex
Author for correspondence:
Gerhard Roth
e-mail: [email protected]
Within the animal kingdom, complex brains and high intelligence have
evolved several to many times independently, e.g. among ecdysozoans in
some groups of insects (e.g. blattoid, dipteran, hymenopteran taxa), among
lophotrochozoans in octopodid molluscs, among vertebrates in teleosts (e.g.
cichlids), corvid and psittacid birds, and cetaceans, elephants and primates.
High levels of intelligence are invariantly bound to multimodal centres such
as the mushroom bodies in insects, the vertical lobe in octopodids, the pallium
in birds and the cerebral cortex in primates, all of which contain highly ordered
associative neuronal networks. The driving forces for high intelligence may
vary among the mentioned taxa, e.g. needs for spatial learning and foraging
strategies in insects and cephalopods, for social learning in cichlids, instrumental learning and spatial orientation in birds and social as well as instrumental
learning in primates.
1. Introduction
Neuroscientists hold that higher cognitive functions, also called ‘intelligence’ or
‘mind’ (as defined in the next paragraph), are bound to brain properties, and
that degrees in cognitive functions and intelligence correlate well with degrees
of brain complexity. For a long time, the common view even among biologists
was that the joint evolution of brains and minds started with diffuse nerve nets
and very simple behaviours like those found in acoelans and culminated in
a straightforward fashion in the human brain as basis for the superior mental
abilities that make humans ‘unique’ [1]. However, despite their indisputable complexity, the human brain and mind are the result of just one out of many lines of
evolution. Complex brains are supposed to have evolved at least several times
independently, often in distantly related taxa, although presumably from an
ancestral tripartite brain [2], and with them high intelligence. A detailed presentation of the content of this article can be found in my book ‘The long evolution of
brains and minds’ [3].
2. What is intelligence?
In humans, intelligence is commonly defined as the sum of mental capacities such
as abstract thinking, understanding, communication, problem-solving, reasoning,
learning and memory formation and action planning. Usually, human intelligence
is measured by intelligence tests and expressed in intelligence quotient values
expressing different contents (e.g. visual–spatial, verbal, numerical). Evidently,
such a definition and measurement of intelligence cannot be applied directly to
non-human animals. A number of comparative and evolutionary psychologists
and cognitive ecologists converge on the view that, across all species studied,
mental or behavioural flexibility or the ability of an organism to solve problems occurring
in its natural and social environment are good measures of intelligence culminating in
the appearance of novel solutions not part of the animal’s normal repertoire [3–5].
This includes forms of associative learning, innovation rate as well as abilities
requiring abstract thinking, focused attention, concept formation and insight.
3. Brain complexity
With respect to bilaterian animals, the term ‘brain’ is used for a condensation of
nerve cells around the oesophagus giving rise to nerve cords [2]. There is no
& 2015 The Author(s) Published by the Royal Society. All rights reserved.
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The origin of the first brains and their structures is disputed.
Cnidarians as the assumed sister group of bilaterian animals
have no brains, although local concentrations of nerve cells
can be found. Among the Acoelomorpha, the Acoela, but not
the Nemertodermatida and Xenoturbella, are assumed to possess a brain-like rostral concentration of nerve cells plus
subepidermal nerve chords. Brains are believed to be present
in the last common ancestor of protostomes (Lochotrophozoa,
Ecdysozoa) and deuterostomes (Ambulacraria, Chordata),
which may already have had a tripartite organization [2]. This
would imply that the ambulacrarians (echinoderms, hemichordates) have lost a brain. Alternatively, brains have evolved
independently in protostomes and chordates from diffuse
nerve nets like those found in acoelans, leaving the status of
ambulacrarian nervous systems unsettled.
A combination of complex brains and intelligence in the
above-defined sense of higher cognitive abilities are found
among ecdysozoan invertebrates in some orders of insects
(e.g. in blattoids, dipterans, hymenopterans) and among
lophotrochozoans in octopodid molluscs (cf. [6]), among vertebrates in some teleost taxa (e.g. cichlids), in corvid and
psittacid birds, and among mammals in cetaceans, elephants
and primates [3]. Accepting the idea that the last common
ancestor of protostomes and deuterostomes already possessed a tripartite brain of modest complexity, these brains
have undergone a strong further increase in brain complexity
and intelligent behaviour independently, because each of the
major animal taxa mentioned had ancestors that revealed
neither complex brains nor intelligent behaviour.
5. Insect brains and intelligent behaviour
As promostome taxa in general, most ecdysozoan taxa possess relatively simple nervous systems consisting of a nerve
ring surrounding the oesophagus and often exhibiting lobes
or ganglia, and a varying number of nerve cords, often
with local ganglia. Many endoparasitic taxa show signs of
strong secondary simplification [7]. More complex brains
are found in pan-arthropods (onychophorans, chelicerates,
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Phil. Trans. R. Soc. B 370: 20150049
4. How many times did complex brains and
‘high intelligence’ evolve?
crustaceans, insects) as the result of the fusion of the first
three ganglia [8].
The insect nervous system consists of a brain and ventral
nerve cords with ganglia (cf. [2]). The brain is composed of a
large protocerebrum, a smaller deutocerebrum and a very
small tritocerebrum. Owing to the loss of antennae, chelicerates have no deutocerebrum. The protocerebrum consists
of two hemispheres, which are continuous with the lateral
optic lobes processing the input from the compound eyes.
In the median protocerebrum, the corpora pedunculata or
‘mushroom bodies’ (MB) are found [9].
MBs have been demonstrated to be the substrate of developed cognitive and social functions found in insects as well as
in other arthropods. Among insects, complex MBs have evolved
apparently independently in taxa of butterflies (Lepidoptera),
dragonflies (Odonata, Anisoptera), cockroaches (Blattoidea)
and hymenopterans (Hymenoptera, i.e. wasps, bees, ants,
etc.). In cockroaches, flies, bees and wasps, among others, the
MBs are very large and composed of two calyces, and a peduncle consisting of two lobes, the a and the b lobe. In the
honeybee, the MBs occupy about half of the volume of the
brain [9,10]. The somata of neurons, the ‘Kenyon cells’
(KCs)—which in the honeybee number about 300 000
(R. Menzel 2010, personal communication) and whose axons
(‘Kenyon fibres’) form the peduncle—are the smallest ones
found among insects, and their packing density is 15 times
higher than the highest ones found in the vertebrate brain. In
the bee, the KCs receive visual, olfactory and somatosensory
input from about 800 projection neurons via about 1 million presynaptic contacts, plus about 10 postsynaptic contacts. Axons of
KC divide into the peduncle, and one collateral enters the a, and
another one the b lobe. The calyces exhibit three regions, the lip
ring region processing olfactory input, the collar ring region processing visual input and the basal ring region processing mixed
olfactory and mechanosensory input. In hymenopterans as well
as in some other insect taxa, the MB represents a highly complex
multimodal centre that forms the neural basis of processing and
integrating olfactory, somatosensory and visual information and
enables complex cognitive functions and complex behaviour.
A large variety of insects including honeybees possessing
complex mushrooms exhibit an impressive repertoire of behaviour in the domain of feeding, spatial orientation (‘navigation’),
social and communicative behaviour, and can learn very
quickly, especially the association between the colour and
odour of flowers (for an overview, see [6,11,12]). This indicates a high degree of behavioural flexibility. This includes
configural learning, contextual learning, i.e. to exert different
kinds of behaviour depending on the site and the conditions,
and categorical learning. Bees are able to learn the category
‘same–different’ and to transfer this concept to novel stimulus
arrangements (cf. [13]). They master so-called delayed
match-to-sample or its opposite, the delayed-non-match-to-sample.
The existence of such cognitive maps for spatial orientation
has been debated for years (cf. [14]). Bees appear to possess
‘map-like’ information about the ground structure and use
this map for return. In general, they appear to use spatial
memories ‘opportunistically’ in three different contexts, i.e.
(i) a general landscape memory acquired via initial orienting
flights, (ii) route memory while flying repeatedly from and to
a specific field location, and (iii) the dance memory while
following dances [12].
The evolution of large and complex mushrooms has been
interpreted as a consequence of the demands of increased
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universally accepted definition of brain complexity. However,
most concepts depart from the idea that—besides absolute
brain size or (uncorrected or corrected) brain size relative to
body size (cf. [3])—the number of neuronal and non-neuronal
cells inside the brain, the number and pattern of shortand long-term connections, the number of anatomically and
functionally different cell types and the degree of compartmentalization (major parts of the brain, nuclei, modules,
layers, etc.) are basic neuroanatomical criteria for brain complexity. At a functional level, one can take into account the
number and diversity of neuroactive substances (neurotransmitters, neuropeptides, neurohormones), differences in
axonal conduction velocity, modes of synaptic and extrasynaptic transmission, etc. However, because of the lack of a
both formalized and empirically founded theory of brain complexity, we have to restrict ourselves to relatively informal
comparisons regarding brain complexity, especially when
comparing distantly related taxa.
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As in ecdysozoans, in lophotrochozoans most taxa possess
simple to moderately complex brains [7]. Within endoparasitic platyhelminths (cestodes, nematodes), there is massive
secondary simplification of the nervous system. In contrast,
some predatory annelid polychaetes have multilobed cerebral
ganglia with a protocerebrum containing mushroom-like
structures. Among molluscs, gastropods have relatively
simple cerebral ganglia, and bivalves show clear signs of secondary simplification. In contrast, cephalopods possess
complex to very complex brains, which may have evolved
several times independently [18]. The most complex brains
are found in squids (Theutidae) and octopods (Octopoda) [7].
The nervous system and brain of Octopus is the largest and
most complex one among invertebrates [19,20]. It contains
about 550 million neurons, 350 of which are located inside the
eight arms, about 160 million neurons in the giant optic lobes
and 42 million neurons inside the brain. The brain is divided
into 16 lobes [19]. It has a ventral motor portion consisting of
several lobes that are involved in the control of feeding, locomotion and colour change, and a dorsal portion exerting
sensory information processing and higher cognitive functions
[21–23]. The brain receives visual afferents from the eyes and
the subsequent optic lobes as well as tactile–chemosensory
information from touch and taste receptors of the arms.
The vertical lobe is considered the most complex part of the
Octopus brain [19,22,23]. It contains about 26 million neurons—
more than half of the neurons inside the brain. It consists only of
two major types of neurons, i.e. little more than 26 million tiny
interneurons, the smallest inside the Octopus brain, and 65 000
large projection neurons, and the former converge on the latter.
The vertical lobe receives visual afferents predominantly from
the median superior frontal lobe. These afferents form a distinct
tract composed of 1.8 million fibres, which terminate in the rind
of the vertical lobe [22]. Processes of the 26 million interneurons
located there penetrate that tract in a rectangular fashion and
form ‘en passant’ contacts with them. As major centre for
‘higher’ cognitive abilities of Octopus, the vertical lobe is closely
connected, via the projection neurons, to the subvertical lobe,
which contains about 800 000 neurons. The interaction of
both lobes is based on the work of an impressively regular
network of millions of crossing fibres.
The large and complicated brains found in squids and octopods correlate well with their cognitive abilities—presumably
in the context of their predatory lifestyle [22,24]. Octopus not
only remembers well where tasty food can be found, but
after travelling far from home, it often returns home via the
shortest route which it had never taken before. Such behaviour
demonstrates that Octopus has a good spatial memory, but it is
7. Deuterostomes, chordates and vertebrates
Among deuterostomes, echinoderms have two decentralized
nervous systems: an ectoneural system with sensory functions
and a hyponeural system with motor functions. Hemichordates posses a ventral and dorsal nerve cord connected by
nerve rings in the head lobe and around the gut. It is debated
whether these types of nervous systems found in ambulacrarians represent an ancestral or secondarily simplified state. The
simple nervous system of urochordates may likewise be
the result of secondary simplification. The cerebral vesicle
of the cephalochordate Branchiostoma, containing 20 000
neurons, possesses all developmental genes required for the
formation of the craniate–vertebrate brain [27].
Myxinoids and vertebrates generally have pentapartite
brains consisting of a medulla oblongata, metencephalon,
mesencephalon, diencephalon and telencephalon. The brains
of galeomorph sharks, myliobatid rays, some teleost taxa
(e.g. cichlids), corvid and psittacid birds and a number of mammals, particularly elephants, cetaceans and primates, represent
the most complex ones.
(a) Hagfish and lamprey
Among chordates, hagfish (Myxinoidea) and lampreys (Petromyzontida) have the smallest relative brain size [28]. Nothing
is known about higher cognitive abilities in these groups.
(b) Cartilaginous fishes
Among cartilaginous fishes, i.e. sharks, rays and chimaeras,
galeomorph sharks and myliobatid rays independently evolved
large and complex brains, especially with respect to the size and
anatomical organization of the telencephalon reaching relative
proportions found in mammals. The so-called central nucleus
appears to be the most important sensory convergence centre
[29]. Unfortunately, no systematic studies on cognition and
intelligence of sharks and rays are available to date.
(c) Actinopterygians-teleost
The structural and functional organization of the telencephalon of the actinopterygian bony fishes and possible
homologies of its pallial regions with those of the other vertebrates is a matter of debate. At first glance, the dorsal
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6. Brain and intelligence in molluscs
unclear whether it possesses a ‘mental map’, because some
experts argue that the animal simply applies path integration.
Other observations and experiments demonstrate that Octopus
uses its siphon for cleaning its cave and its surroundings from
sand and garbage. Also, it could be observed that the animal
collects little stones and piles them in front of the entrance to
their cave for protection against predators. Some Octopus
specialists interpret this as evidence for tool use. Finally,
these animals became famous for playing with plastic bottles
and being able to unscrew lids from jars filled with prawn.
It has been reported that Octopus is capable of learning by
pure observation of the behaviour of its conspecifics [25].
While other experts were unable to reproduce these results,
Fiorito & Chichery [26] published that removal of the vertical
lobe abolished the ability for ‘learning by observation’ in
Octopus. Until today, it is unclear how the findings by Fiorito
& Scotto [25] should be interpreted, i.e. whether or not they
give clear evidence for observational learning.
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sociality in the sense of the well-known ‘social brain hypothesis’ developed in the context of primate –human brain
evolution [15]. However, a recent comparative study by
Farris & Schulmeister [16] demonstrated that complex MBs
are likewise found among non-social insects, including solitary and parasitoid hymenopterans as well as cockroaches,
dragonflies and butterflies, all of which exhibit highly developed abilities of spatial learning (cf. [17], for cockroaches).
The authors conclude that need for improved navigation
and spatial learning rather than sociality was the major
driving force for the evolution of complicated MBs.
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Amphibians generally have small brains in absolute as well as
relative terms. Their relative brain weight overlaps with that of
agnathans, bony fishes and reptiles [3,28]. Brain anatomy exhibits the signs of secondary simplification, most probably as a
(e) Reptiles
‘Reptiles’, i.e. a paraphyletic group consisting of turtles, tuataras, squamates and crocodiles, likewise have absolutely and
relatively small brains, whereas the anatomy of their brains is
distinctly more complex than that of amphibians in the sense
of formation of distinct nuclei and degree of lamination, e.g.
in the optic tectum and pallium [29]. Like in amphibians,
‘higher’ intelligence has not yet been convincingly demonstrated in ‘reptiles’. Leal & Powell [40] reported that the
tropical lizard Anolis evermanni exhibits behavioural flexibility
across multiple cognitive tasks, including solving a novel
motor task using multiple strategies and reversal learning, as
well as rapid associative learning. The authors stated that this
degree of behavioural flexibility found in Anolis is comparable
with that commonly associated with bird or mammal species
(see below). However, Vasconcelos et al. [41], in their critical
review, argue that in the study of Leal and Powell [40], rather
than reversal learning or other kinds of behavioural flexibility,
the lizards exhibit simple instrumental conditioning.
(f ) Birds
In birds and mammals, the telencephalon including the pallium turns out to be the neurobiological substrate of high
intelligence [42]. However, at first glance, there are striking
differences in the anatomy of the dorsal telencephalon of
mammals and birds in the sense that in mammals there is a
clear-cut distinction between a six-layered cortical region
and a compact region of the striatopallidum as the telencephalic part of the basal ganglia, whereas the avian dorsal
telencephalon gives the appearance of a compact cell mass
without obvious lamination or other substructures. In previous times, this made neurobiologists believe that most of
the avian dorsal telencephalon is a hypertrophied striatopallidum. On the basis of the pioneering work by Karten [43],
the mentioned differences are explained today in the way
that the avian dorsal telencephalon does not, indeed, form
a six-layered cortex, but is composed from dorsal to ventral
of compact layers consisting of a superficial hyperpallium
(H), an intercalated hyperpallium (IH), a dorsal and ventral
mesopallium (MD, MV), a nidopallium (N) including a central entopallium (E) and a ‘posterior field L’ as termination
fields of visual and auditory afferents, respectively, an intercalated nidopallium (IN) and an arcopallium (AP) found at
the caudoventral part of the nidopallium. Both nidopallium
and arcopallium surround the striatopallidum.
According to the ‘nuclear-to-cortex theory’ of the bird pallium, IN and IH correspond to layer 4 neurons of the primary
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(d) Amphibians
consequence of increased genome and cell size as well as consequent decrease of metabolic and developmental rates [33,34].
These phenomena are strongest in salamanders (Caudata)
and caecilians (Gymnophiona) and weakest in frogs (Anura),
as revealed by reduction or even absence of cell migration,
nucleization and lamination (e.g. in the optic tectum and
telencephalic pallium) [35].
While traditionally amphibians were regarded as being
highly instinct-bounded or even mere ‘reflex machines’ [36],
extended studies in our laboratory demonstrated associative
learning based on reward, punishment and omission of
reward in frogs [37]. In salamanders, behavioural and electrophysiological studies revealed a control system for visual
attention resembling that of mammals [38,39].
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telencephalon of the actinopterygians does not reveal any
similarity with that of other vertebrates. The striking differences are explained by some authors by the fact that the
telencephalon of the actinopterygians is an everted pallium,
whereas the telencephala of the other vertebrate groups
have an evaginated pallium. (cf. [29]). In the evagination
type, the walls of the embryonic telencephalon thicken and
bulge outwards encircling the lateral ventricle and divide
into the mentioned pallial and subpallial parts. In the eversion type, the subpallial parts remain in a medial position
along the midline of the telencephalon, whereas the pallial
parts bend outwards and then downwards. As a consequence, the medial pallium of this everted telencephalon
now occupies a lateral and increasingly ventral position.
Accordingly, there is a new ‘medial zone Dm’, continued laterally by a ‘central zone Dc’ and a ‘lateral zone Dl’ and finally
in a caudal position a ‘dorsoposterior zone Dp’. According to
Wullmann & Vernier [30], this latter ’dorsoposterior zone’
receives olfactory input and therefore corresponds to the
lateral olfactory pallium of the other vertebrates.
Thus, all these zones appear to represent standard parts of
the pallium. Unclear is the homology of the ‘central zone Dc’ of
the pallium. It gives rise to numerous pathways to the olfactory
bulb and descending to various diencephalic and mesencephalic nuclear regions and, in some teleosts, via both the medial
and lateral forebrain bundle, to the torus semicircularis and
the cerebellum and valvula. Thus, the central zone is the
main efferent station of the actinopterygian pallium.
Experts state that some teleost taxa, above all cichlids, exhibit cognitive abilities, which—in the eyes of the authors—are
comparable to those of primates [31]. Cichlids represent one
of the behaviourally and ecologically most diverse groups of
vertebrates. They are well known for having evolved rapidly
within large lakes, especially the Great African Lakes, and
many species evolved only 100 000 years ago [32].
According to Bshary et al. [31], in many cichlid species,
there is individual recognition not only on visual, but also on
purely auditory cues in the context of brood care behaviour.
In some cichlid species with ranking orders, subordinate individuals often exhibit submissive or appeasement behaviour
towards high-ranking group members in order to reduce
aggression, and such appeasement behaviour is also shown
during courtship. As in mammals and particularly in primates,
cheating is answered by exclusion and punishment of the
cheater, which means that the individuals are capable of
remembering their partners’ behaviour during past interactions. Also, teleosts (e.g. guppies) collect socially important
information by observing the interactions between conspecifics. There are many reports about social learning by
observation in the context of site preferences, food sources,
anti-predator behaviour (e.g. mobbing an Octopus) and learning of young fish what to eat and what to avoid by observing
adults. There are likewise many examples for cooperative hunting. Thus, it seems that in cichlids, the need for ‘social’ rather
than for spatial or instrumental intelligence favoured the
evolution of complex brains.
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(g) Primates
High intelligence that characterizes monkeys and apes,
including humans, is closely linked to the size and neuronal
complexity of the isocortex [28,55], which—with the exception
of insectivores and cetaceans—is six-layered (as opposed to
most of the limbic cortex, which is three- to five-layered) [29].
Among cortical areas, the dorso- and ventrolateral prefrontal
cortex (PFC) appear to be the neurobiological basis of socalled general intelligence in mammals [56,57]. It is involved
in the comprehension and processing of the temporal–spatial
structure of sensory information and cognitive mental events
such as thinking and imagining, predominantly in the context
of action planning and action preparation, but also problemsolving and decision-making. It is also an important
component of working memory.
The dorsolateral PFC of primates receives input mainly
from the posterior parietal cortex regarding position and movement of head, neck, face and hands, as well as information
about spatial orientation and spatial aspects of action planning.
The ventrolateral PFC, in contrast, receives input mainly from
the temporal lobe carrying complex visual and auditory information, e.g. in the context of the meaning and relevance of
objects and scenes, as well as language-related information
from the left temporal lobe (mostly from the Wernicke
language centre). In the ventrolateral PFC, we find the Broca
language centre, which is involved in grammatical and
syntactical aspects of language [57].
In the following, I will discuss a number of cognitive
abilities commonly cited as evidence for high primate intelligence, i.e. tool use, quantity representation, extended
working memory, imitation, mirror self-recognition, theory of
mind and conscious attention (cf. [4]).
(i) Tool use
Tool use is commonly found among primates. Ring-tailed
lemurs (Lemur catta) have been reported to successfully manipulate a puzzle feeder in the wild [58], which is the only known
case of lemur tool use in the wild. In captivity, however, manipulatory skills of lemurs with novel objects are roughly
comparable with those of some New and Old world monkeys.
The gray mouse lemur (Microcebus) mastered opening boxes in
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The ability for mind-reading was reported for birds in a food
caching experiment. A raven was able to take into account what
an other raven has seen or not seen, while a human experimenter was hiding food in a cache. Ravens were quicker at
pilfering the human-made caches when facing a fully informed
raven competitor compared with a partially or non-informed
one [53]. The author interprets his finding as a ‘precursor
step to a human-like understanding of the others’ mind’.
A widely known example of avian high intelligence is Alex,
an African gray parrot trained and studied by Pepperberg [54].
According to Pepperberg, Alex could identify 50 different
objects and recognize quantities up to six, he could distinguish
seven colours and five shapes and understand the concepts of
‘bigger’, ‘smaller’, ‘same’ and ‘different’, and that he was learning ‘over’ and ‘under’. He had a vocabulary beyond 100 words
and gave the impression of understanding what he said. He
could form concepts of form, colour, objects and to a limited
degree had an understanding of syntax in language. He had
the ability to count objects up to six even verbally, chose certain
objects on command and had an understanding of ‘zero’.
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sensory cortex of mammals (see below), N and H to layers 2
and 3 of the secondary mammalian cortex, MV and MD to
layers 3 and 6 of the tertiary cortex and AP to layer 5 of the
motor cortex and of other cortices [42,44–46].
A special region of the pallium is the ‘nidopallium caudolaterale’. According to Güntürkün, functionally it strongly
resembles the mammalian dorsolateral prefrontal cortex
(dlPFC—see below), because it is involved in working memory,
action planning, behavioural flexibility and creativity—in
essence in ‘intelligence’ [47]. Like the mammalian dlPFC, it is
a multimodal convergence centre and receives a strong dopaminergic input from the ventral tegmental area and nucleus
accumbens.
During the past two decades, it has become evident that
some bird taxa, above all corvids and psittacids, possess cognitive abilities many of which appear comparable to those of
primates. In nature as well as in captivity, corvids are shown
to use natural objects as tools or to modify them until they
have the right length or pass through an opening [48,49].
New Caledonian crows (Corvus moneduloides) spontaneously
make tools out of screw pine (Pandanus) leaves. In that context, they fabricate strips of different size and shape for
different purposes [50]. According to Hunt et al. [50], crows
occasionally make hooks in the wild, too, and the famous
New Caledonian crow Betty had seen a hooked wire
before, but this type of intentional tool-making is regarded
as unique. Crows use short sticks to retrieve longer ones
from a box, which was then used to retrieve food from a
box (metatool)—a behaviour that otherwise has been
observed in primates only [50].
In that context, the question arises whether corvid (or other)
birds exhibit a causal understanding of tool use. Recent experiments by Taylor et al. [51] cast some doubts on such an
assumption. The authors conducted standard string-pulling
experiments with New Caledonian crows comparing experienced and naive animals. The animals had to pull up strings
with meat at one end. When the animals had full sight of the
string and the meat while pulling, naive ones solved the problem spontaneously in most cases. But when visual control
of string-pulling was restricted, naive animals could no
longer solve the problem spontaneously and only after
extended trial and error learning, and the performance drastically dropped even in the experienced ones. According to the
authors, this demonstrates that in the string-pulling experiment problem-solving is based primarily on reinforcement
learning. Thus, the question of truly insightful problem-solving
in corvids remains open.
Mirror self-recognition is considered a highly cognitive ability that has been found in apes, elephants and dolphins (see
below). Recently, a team led by Güntürkün and co-workers
[52] demonstrated that at least the common magpie (Pica
pica), a corvid, passes the mark test. When the plumage of
the magpies was marked below the beak, i.e. at a site that
could not be inspected without the mirror, the animals started
cleaning themselves and trying to touch the spot. They did not
respond to pictures, padded or alive, marked or unmarked
magpies behind a glass pane, i.e. they did not confound their
own mirror image with that of conspecifics. Magpies are likewise highly social animals and exhibit an unusual ability to
recognize and relocate cached objects (food, but also glittering
objects). They are capable of recognizing conspecifics and other
animals individually. This adds another case to the unusual
cognitive abilities of corvid birds.
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Lemurs are capable of controlling their impulsive gesture
towards a larger option, when selection of a smaller quantity of
food is rewarded with a larger one. They also learned to associate
a graphic representation of the reward with the corresponding
quantity, even though only one subject consistently selected the
representation of the smaller quantity to be rewarded with
the larger quantity of food [67]. The fundamentals of abstraction
appear to be present in prosimians. Nevertheless, numerical
discrimination is superior in monkeys and apes. Capuchin monkeys are able to judge larger quantities of two sets contrasting up
to five items in food-choice experiments [68]. Quantity-based
judgements for two sets with up to 10 items were tested in
rhesus monkeys (Macaca mulatta), gorillas, chimpanzees and
bonobos. Rhesus monkeys selected the larger of the two sequentially presented sets reliably when one set had fewer or more than
four items, whereas great apes did so, even when the quantities
were large and the numerical distance between them was
small [69].
(iii) Working memory
One much-used task for testing working-memory abilities
is the delayed-matching-to-sample task (DMTS) or the complementary form of delayed-non-matching-to-sample. In
DMTS, the subject is shown a rewarded stimulus and has to
keep it in mind for a variable period of time during which
the stimulus is not visible anymore, and then identify it out
of a pair of stimuli. Macaques master a delay of 2–9 min after
long training. Dolphins reach a maximum of 4 min. In
humans, the capacity of working memory is substantially
increased by the ‘phonological loop’ [70,71], but when
human subjects are prevented from talking to themselves by
inner speech or loudly, then they are no better than dolphins
and macaques.
Some years ago, Inoue & Matsuzawa [72] reported the
astonishing capacity for numerical recollection in chimpanzees
(three mother–offspring pairs). In a numerical sequence task,
the animals had to learn the sequence of Arabic numerals
from 1 to 9, which appeared in different on-screen positions.
Then the numerals were replaced by white squares. The subjects had to remember which numeral appeared in which
location, and then touch the white squares in the correct
sequence. All naive animals mastered this task, but the
(iv) Imitation
Imitation was long considered an inferior kind of learning in
the sense of meaningless copying of a certain behaviour.
Only in recent years has it become clear that imitation is a
higher-order cognitive ability. However, to date, there is no
universally accepted definition of imitation, and some kinds
of behaviour previously seen as imitation are now interpreted
differently. One of these kinds of imitation-like behaviour is
response facilitation or emulation found in a wide range of animals, which means that seeing an action ‘primes’ the
individual to do the same, and the individual, by trial and
error, finds the same or a very similar solution of the
problem [4].
Of importance is the social component in emulation. For
example, young baboons (Papio) quickly learn which kinds
of fruit are edible after one group member has tasted a
fruit. Vervet monkeys (Chlorocebus), likewise Old World monkeys, learn this task more slowly, although they live in the
same environment as baboons. The explanation for the difference may be that young baboons have a close social life and
show great interest in each other, whereas this is not the case
for the Vervet monkeys.
Imitation of human behaviour is frequently found among
apes, e.g. in orangutans (Pongo pygmaeus). In the Indonesian
Tanhung Putting National Park, orangutans were observed
imitating everyday actions of the human park personnel [73].
In some cases, the animals seemed to understand the sense
of the copied action, in other cases, they carried out the actions
‘just for fun’. This included the decanting of fuel from a barrel
into a canister, sweeping trails, making fire, using a saw,
mixing ingredients for a pancake or dish-washing.
Chimpanzees and other great apes show imitative abilities
beyond those of other primates. The recent view is that great
apes are capable of mentalizing about others and have some
understanding of intentionality and causality. Chimpanzees
are able to distinguish between an experimenter who is
either unwilling or unable to give them food. Hence, they do
not simply perceive the behaviour of others, but also interpret
it [74]. Capuchin monkeys were shown to distinguish between
intentional agents and unintentional objects [75].
(v) Mirror self-recognition
Gordon Gallup was the first to demonstrate that—besides
humans—at least some chimpanzees and orangutans are
capable of recognizing themselves in the mirror, but only in
less than half of animals tested and not always in those that
pass the test. It is mostly the young animals that display
mirror self-recognition, and even they rapidly lose interest
in such experiments [76].
(vi) Theory of mind: understanding the others
The question whether or not non-human animals possess a
theory of mind (ToM), i.e. the ability to understand another
individual’s mental –emotional state, is hotly debated, as is
the related ability to ascribe to a conspecific a certain knowledge or false knowledge (or false belief ) and to take both into
account in the planning of own behaviour: in the 1980s and
6
Phil. Trans. R. Soc. B 370: 20150049
(ii) Quantity representation
performance of the three young chimpanzees was always
better than that of the three mothers. Humans were slower
than the three young chimpanzees. It would be interesting to
test young human children under the same conditions.
rstb.royalsocietypublishing.org
different ways, and aye-ayes (Daubentonia) demonstrated basic
understanding of features of tools by solving a can-pulling
task [59]. Systematic tool use including limited forms of
tool-making is found in the capuchin monkey (Cebus) [60,61].
Chimpanzees are known to fabricate and use a wide
range of complex tools, and have been shown to vary in
their tool use at many levels, for example preparing twigs
for ant and termite dipping [62]. Tool kits consist of about
20 types of tools for various functions. Only chimpanzees
appear to be able to use one type of raw material to make
different kinds of tools, or to make one kind of tool from
different raw materials. They use tool sets in a sequential
order, make use of composite tools and combine tools to a
single working unit [63,64]. In this context, chimpanzees as
well as orangutans exhibit insightful problem-solving
[65,66]. They are engaged in action planning, mentally preexperience an upcoming event and are able to select objects
needed for much-delayed future tool use.
Downloaded from http://rstb.royalsocietypublishing.org/ on June 18, 2017
(vii) Conscious attention
After Wolfgang Köhler’s pioneering work with chimpanzees
on Tenerife during the World War I, my academic teacher
Bernhard Rensch from the University of Münster, Germany,
was among the very first who carried out experiments to
assess the cognitive–mental abilities of chimpanzees, and
his favourite subject was Julia. In a typical experiment, Julia
had to draw an iron ring out of a wooden maze covered
with a glass plate using a magnet. She could choose between
two alternative paths, of which only one led out of the maze,
and she had only one move. Rensch & Döhl [81] started with
simple mazes, but eventually confronted Julia with rather
complex ones, which we humans can master only after carefully ‘wandering’ with our gaze through the maze. Julia did
exactly that and in most cases (86%) chose the right path.
Rensch [82] interpreted these finding as clear evidence that
at least chimpanzees possess conscious awareness and can
solve problems mentally.
8. Brains and intelligence in elephants and
cetaceans
Among mammals, Indian and African elephants, whales and
most dolphins have brains that are larger to much larger than
the human brain. Elephant brains may have weights of up to
6 kg, and the false killer whale (Pseudorca crassidens) up to
10 kg. Therefore, one would expect that their intelligence is
superior to that of humans. However, controlled experiments
on the alleged super-intelligence of the dolphins yielded
somewhat mixed and often disappointing results.
Elephants possess a magnificent spatial orientation that
enables them to head for water ponds as distant as 60 km.
Likewise, they can recognize human individuals after
decades, as Rensch & Altevogt [83] have demonstrated.
All this stands in sharp contrast to their rather unimpressive
cognitive abilities [84,85]. As to learning abilities, Rensch &
Altevogt [83] report the cumbersome procedure of carrying
out a simple operant conditioning experiment teaching an
elephant to distinguish between black and white or
small and large objects. After a number of failures,
Plotnik and co-workers [86] demonstrated mirror selfrecognition in at least one out of three Indian elephants,
Elephas maximus.
Although dolphins are able to distinguish between objects
differing in shape, they are incapable of categorization, for
9. Conclusion
I have tried to demonstrate that high intelligence, as defined
at the beginning, has evolved at least several times independently in some insect taxa, particularly in hymenopterans,
and in octopodids molluscs, as well as in some teleost taxa
(e.g. cichlids). The last common ancestor of both ecdysozoans
and lophotrochozoans, as well as the last common ancestor of
each group, may either have had a non-centralized nerve net
(or two of them, an epidermal and a hypodermal one) or a
tripartite, though simple brain, which then in very many
taxa underwent additional simplification. In any case, the
highly complex brains found in insects and in cephalopods
must have evolved independently, and with them high
intelligence.
Among craniates –vertebrates, the lowest levels of brain
complexity and intelligence are found in hagfish and lamprey, followed by amphibians. Likewise, ‘reptiles’ in the
traditional sense (i.e. turtles, snakes and lizards) are not
famous for superior intelligence, and their brains are definitely less complex than those of birds and mammals.
However, among teleosts, there are taxa like cichlids that
are believed to exhibit signs of ‘primate-like’ intelligence.
With respect to intelligence, among birds, parrots and
corvids stand out [90], which interestingly are all vocal learners [46], and among mammals primates stand out [3,55].
Within primates, prosimians exhibit manipulatory, perceptual and cognitive capacities, although often only as a basic
ability. New World monkeys possess moderate capacities in
various cognitive domains that partially overlap with those
of Old World monkeys. The behaviour of the latter shares
characteristics with apes, although great apes clearly outperform the other non-human primate taxa in most respects,
with humans on top. Despite their very large brains, elephants and cetaceans turn out to possess an intelligence
definitely inferior to monkeys and apes and also possibly to
corvid and psittacid birds.
There is much speculation about differences in the
‘driving forces’ with respect to increases in brain size and
complexity as well as cognitive abilities (cf. [3]). On the
basis of the data presented in this review, needs for spatial
learning and foraging strategies in insects and cephalopods,
for social learning in cichlids, for instrumental learning and
spatial orientation in birds and social as well as instrumental
learning in primates appear to be the major forces.
7
Phil. Trans. R. Soc. B 370: 20150049
example of distinguishing between ‘round’ and ‘triangular’
objects and assigning an unfamiliar round or triangular
object to one of these two categories—something that
pigeons, crows, parrots, dogs, any kind of primates and
even bees are capable of [87].
Reiss & Marino [88] succeeded in demonstrating that captive-born bottleneck dolphins (Tursiops truncatus) are capable
of mirror self-recognition. At the beginning, the dolphins
showed great interest in the marks attached to their bodies,
which they could not inspect without the help of the
mirror, but like the chimpanzees and unlike young (as well
as older) humans, they rapidly lost interest in the procedure.
Possible neurobiological reasons for the mentioned differences in cognitive abilities of elephants and dolphins
compared with primates are discussed in the twin article
by Dicke & Roth [89].
rstb.royalsocietypublishing.org
1990s, Povinelli et al. [77,78] conducted experiments showing
that at least some chimpanzees possessed the ability to attribute certain knowledge to other chimpanzees or humans and
to take into account that knowledge in their own behaviour.
Later, however, Povinelli and Vonk became sceptical and
could find no convincing evidence for the existence of a
ToM and knowledge attribution in chimpanzees or other animals, but argued that their own findings could be better
explained as the result of operant conditioning [79]. However, other primatologists strongly disagree and point to
substantial drawbacks in the method applied by Povinelli
and co-workers. Tomasello et al. [80] believe that chimpanzees possess at least some aspects of a ToM and knowledge
attribution comparable to that of human children at an age
of 3 to 4 years.
Downloaded from http://rstb.royalsocietypublishing.org/ on June 18, 2017
Competing interests. I have no competing interests.
Funding. I received no funding for this study.
Acknowledgements. I thank two anonymous reviewers for helpful com-
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