An examination of cetacean brain structure
with a novel hypothesis correlating
thermogenesis to the evolution of a big brain
Paul R. Manger*
School of Anatomical Sciences, Faculty of Health Sciences, University of the Witwatersrand, 7 York Road, Parktown, 2193, Johannesburg,
Republic of South Africa (E-mail: firstname.lastname@example.org)
(Received 5 October 2004; revised 3 January 2006; accepted 26 January 2006)
This review examines aspects of cetacean brain structure related to behaviour and evolution. Major considera-
tions include cetacean brain-body allometry, structure of the cerebral cortex, the hippocampal formation,
specialisations of the cetacean brain related to vocalisations and sleep phenomenology, paleoneurology, and
brain-body allometry during cetacean evolution. These data are assimilated to demonstrate that there is no neural
basis for the often-asserted high intellectual abilities of cetaceans. Despite this, the cetaceans do have volume-
trically large brains. A novel hypothesis regarding the evolution of large brain size in cetaceans is put forward. It is
shown that a combination of an unusually high number of glial cells and unihemispheric sleep phenomenology
make the cetacean brain an efficient thermogenetic organ, which is needed to counteract heat loss to the water. It
is demonstrated that water temperature is the major selection pressure driving an altered scaling of brain and
body size and an increased actual brain size in cetaceans. A point in the evolutionary history of cetaceans is
identified as the moment in which water temperature became a significant selection pressure in cetacean brain
evolution. This occured at the Archaeoceti – modern cetacean faunal transition. The size, structure and scaling of
the cetacean brain continues to be shaped by water temperature in extant cetaceans. The alterations in cetacean
brain structure, function and scaling, combined with the imperative of producing offspring that can withstand the
rate of heat loss experienced in water, within the genetic confines of eutherian mammal reproductive constraints,
provides an explanation for the evolution of the large size of the cetacean brain. These observations provide an
alternative to the widely held belief of a correlation between brain size and intelligence in cetaceans.
Key words: intelligence, allometry, brain size, cerebral cortex, glia, marine mammals.
I. Introduction .................................................................................................................................................
II. Allometry of the cetacean brain ................................................................................................................
(1) The brain-body mass relationship amongst mammals – interspecific and intraordinal
(2) The brain-body mass relationship within a single species – intraspecific comparisons ...............
(3) The encephalisation quotient ..............................................................................................................
III. The cetacean cerebral cortex .....................................................................................................................
(1) Lamination of the cetacean cerebral cortex ......................................................................................
(2) Parcellation of the cerebral cortex ......................................................................................................
(3) Columnar organisation of the cerebral cortex ..................................................................................
(4) Neuronal morphotypes within the cerebral cortex ..........................................................................
(5) Allometry of the cerebral cortex: the corticalisation index (CI) .....................................................
(6) Neuronal density, the glia:neuron index, and the composition of the neuropil ...........................
* Tel: +27 11 717 2497; Fax: +27 11 717 2422.
Biol. Rev.: Page 1 of 46.
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IV. The cetacean hippocampal formation ......................................................................................................
V. Specialisations of the cetacean brain ........................................................................................................
(1) Conspecific communication among cetaceans .................................................................................
(2) Sleep in cetaceans .................................................................................................................................
VI. Evolution of the cetacean brain .................................................................................................................
VII. The intellectual capacities of cetaceans ....................................................................................................
(1) Actual and relative brain size of cetaceans ........................................................................................
(2) Vocalisations of cetaceans: language or simple species-specific calls? ..........................................
(3) The cerebral cortex and the hippocampal formation ......................................................................
(4) Does acoustic specialisation account for the increase in cetacean brain size? .............................
(5) Can apparent convergences in cognitive behaviour explain the increase in cetacean brain size?
VIII. Water temperature and the large cetacean brain ...................................................................................
(1) Water temperature during the archaeocete/Oligocene cetacean transition ................................
(2) Neuroanatomical features of the cetacean brain related to thermogenesis ..................................
(3) Brain-body mass scaling in modern cetaceans and its relation to water temperature ................
(4) The size of the cetacean brain ............................................................................................................
(5) Evidence from other aquatic mammals .............................................................................................
(a) Pinnipedia ........................................................................................................................................
(b) Sirenia ...............................................................................................................................................
IX. Conclusions ..................................................................................................................................................
X. Acknowledgments ........................................................................................................................................
XI. References ....................................................................................................................................................
Many papers describing cetacean behaviour begin with a
generalised statement to the effect of: ‘Dolphins are re-
markably intelligent creatures …’ (e.g. Tyack, 2000).
Despite the high expectations placed upon the cetaceans as
the only possible ‘alien’ species with which man may have a
meaningful conversation of great intellectual depth (Lilly,
1962), scant evidence of this has been presented (Wu ¨rsig,
2002). The compulsively anthropomorphic plurality of an-
ecdotes provided in both the scientific and popular literature
cannot be considered data (Budiansky, 1998; Forestell,
The belief in the apparently undeniable high level of
intelligence is derived from two features of the cetaceans,
one morphological and the other behavioural. The mor-
phological rationale for exceptional intelligence is the large
size and gyrencephalic nature of the brain (Fig. 1). Indeed,
cetaceans have large brains, with some species having the
largest brain of all animals, weighing in excess of 8 kg (Pilleri
& Gihr, 1970). Humans also have large brains, which we
recognise to be the basis of our intellectual capacities. One
very influential view regarding the evolution of brain size
is the relationship forwarded by Jerison (1973), that residual
brain size (that remaining from a correction for body size) is
a determinant of biological intelligence. Thus, the general
conclusion is: large relative brain size equals great intelli-
gence. This hypothesis has been attached to the cetaceans as
proof of some form of extraordinary intelligence (Jerison,
1978). Perhaps unwittingly, Jerison has asserted that there
can be only one reason for the brain to increase in relative
size – an adaptive increase in its information-processing
capacity, i.e. increased intelligence.
This assertion, which has been selectively examined in the
case of cetaceans, and of which there is contradictory pub-
lished data (e.g. the baleen whales have some of the lowest
mammalian encephalisation quotients, so are they, despite
having brains weighing several kilograms, therefore some of
the most unintelligent mammals?), is the maxim for many
studies of cetacean brain and behaviour. However, it is
possible that increases in relative and actual brain size are
not always adaptive responses to a need for greater infor-
mation processing capacity but that brain size increases are
a response to an alternative selection pressure. The present
paper deals with this issue in regard to the evolution of brain
size in cetaceans.
The second feature commonly construed to provide evi-
dence of high intellectual capacities in the cetaceans is the
vocal proclivity of this mammalian order. Language, dia-
lects, conversations, grammatical competency, and several
other human linguistic terms are often used to describe the
vocalisations of cetaceans. All attempts to teach dolphins an
imposed language are based upon stimulus-response be-
havioural paradigms (or operant conditioning) (Herman &
Tavolga, 1980; Herman, 2002) – a basic form of learning
(Thomas, 1996). At best, dolphins have been shown to be
capable of learning approximately 40 symbolic associations
(or ‘words’) (Herman & Tavolga, 1980; Herman, 2002).
Other work has concentrated upon deciphering ‘dol-
phinese’, i.e. the vocalisations themselves. However, studies
of dolphin vocal repertoires have shown that they are limited
to approximately seven (range 5–20) different characteristic
sounds (Herman & Tavolga, 1980). The vocalisations are
munication of thoughts and feelings, and they do not exhibit
the higher order entropies typical of human language
Paul R. Manger
Fig. 1. (A) Photograph of the lateral surface of the killer whale (Orcinus orca) brain. Scale bar=1 cm. (B) Photograph of a coronal
slice through the brain of a piebald dolphin (Cephalorhynchus commersonii). Scale bar=1 cm. The deep and convoluted sulci are
characteristic of all cetacean brains. The sulci and gyri of the cetacean have the appearance of those found in human patients
suffering from micropolygyria (Welker, 1990). The brains photographed here are from the collection of Dr Sam H. Ridgway.
Cetacean brain evolution and thermogenesis
Table 1. Brain mass, body mass, encephalisation quotients, and water temperatures used in the analyses included in the
present study. Sources for brain and body masses are: (1) Gingerich (1998); (2) Schwerdtfeger et al. (1984);
(3) Ridgway & Brownson (1984); (4) Ridgway (1990); (5) Marino (1998); (6) Pilleri & Gihr (1970); (7) von Bonin (1936);
(8) Jacobs & Jensen (1964); (9) Jerison (1978); (10) Marino et al. (2004). Encephalisation quotients were calculated based on the
general mammalian regression (see Fig. 2), and water temperatures were derived from the data compiled in Fig. 16.
Species Brain mass (g)Body mass (g)
temp. (xC) Source
Agorophiidae Genus Y n.sp.
Eosqualodontidae n.gen. n.sp.
Patriocetidae n.gen. n.sp.
Lagenorhynchus n.sp. H
Kentriodon n.sp. W
Eurhinodelphis n.sp. M
Eurhinodelphis n.sp. V
Eurhinodelphis n.sp. V
Schizodelphis n.sp. B
Schizodelphis n.sp. B
Schizodelphis n.sp. H
Schizodelphis n.sp. H
Schizodelphis n.sp. H
Paul R. Manger
Table 1 (cont.)
SpeciesBrain mass (g) Body mass (g)
temp. (xC) Source
22034900 1.99 15–252
indet.=indetermined genus or species.
Cetacean brain evolution and thermogenesis
(McCowan, Hanser & Doyle, 1999). Rather, these seven
typical vocalisations appear to be seven different species-
specific calls, such as has been seen in many other animals,
some of which have far more calls than the seven typically
found for bottlenose dolphins. In summary, it appears that
the evidence in favour of significant intellectual capacities
of dolphins is tenuous, and based upon untested, unproven,
unquestioned, and anthropomorphic assumptions.
The present paper provides a critical review of cetacean
brain structure in comparison to the brain of other mam-
mals. No invasive experiments of the cetacean brain have
been undertaken in the modern era of neuroscience due
to the Marine Mammal Protection Act; thus the only way
to decipher cetacean brain function is from comparative
information garnered from laboratory animal experimen-
tation and compare this to post-mortem cetacean tissue.
Observations on cetacean brain structure presented here are
derived from sources in the literature and primary obser-
vations. Cetacean brain allometry is reanalysed and com-
pared to both extant and extinct mammals, and to the
environment of the various cetacean species. The allometry
and structure of the cerebral cortex is reviewed in light of
several recent and older studies demonstrating an atypical
structure of the cerebral cortex in cetaceans. Two speciali-
sations of the cetacean brain are described, which relate to
the vocalisations and sleep physiology of the cetaceans. The
evolution of the cetacean brain is traced by comparing fossil
endocasts of extinct cetacean species with those of modern
cetaceans. These data are assimilated to provide a neuro-
anatomical basis indicating that cetaceans lack sophisticated
cognitive abilities. Finally, a data-based hypothesis is for-
warded suggesting that the evolution of large brain size
in cetaceans is an adaptation to a thermally challenging
II. ALLOMETRY OF THE CETACEAN BRAIN
(1) The brain-body mass relationship amongst
mammals – interspecific and intraordinal
The allometric relationship between brain mass and body
mass in vertebrates has been calculated, recalculated, and
speculated upon for well over a century (reviewed in Jerison,
1973). It is clear that a significant, statistically reliable pre-
dictor of brain mass across the majority of vertebrate species
is body mass, although the reasons for this are still specu-
lative (Armstrong, 1990; Harvey & Krebs, 1990). Three
types of allometric calculations are generally undertaken,
those comparing species’ averages from a range of orders
(interspecific), those comparing species’ averages from the
same order (intraordinal), and those comparing data from
(Armstrong, 1990). The first two of these comparisons are
considered in this section, the latter in the next section.
Several studies have examined the brain mass versus body
mass relationship of cetaceans (e.g. Pilleri & Gihr, 1970;
Jerison, 1978), and a reanalysis of this relationship with ad-
ditional data and a new perspective is undertaken here.
Brain mass and body mass data were taken from several
published sources, for cetaceans (see Table 1), and other
mammals (Bininda-Emonds, Gittleman & Kelly, 2001;
Crile & Quiring, 1940; Stephan, Frahm & Baron, 1981;
Wood & Collard, 1999). Allometric equations using least-
squares regression analysis were calculated for five groups:
odontocete cetaceans, odontocete combined with mysticete
cetaceans, hominids, primates, and the remaining mammals
(Fig. 2). The division of the analysis into these five groups
was done for the following reasons. Firstly, the majority of
mammals show a similar brain-body scaling across species,
thus, it is most efficient to deal with these data as an inter-
specific comparison, to provide a baseline for comparison to
the species of interest. An intraordinal analysis was used for
primates (excluding the hominids), as it is clear from pre-
viously published material that this group, while scaling in a
similar manner to other mammals, does have a substantially
different brain mass: body mass ratio. An intrasubordinal
analysis was appropriate for hominids because of the dra-
matic difference in scaling of this suborder in comparison to
other primates. Finally, an intraordinal analysis of the cet-
aceans, and intrasubordinal analysis of the odontocetes were
used, as in both cases the species within this order have a
different brain mass: body mass scaling compared to that of
In the present analysis, the plot of brain (Mbr) versus body
mass (Mb) for mammals in general (excluding cetaceans and
primates) gave results similar to those previously published
(e.g. Armstrong, 1990; Harvey & Krebs, 1990). The al-
lometric equation calculated was:
Note from equation (1) that the slope of the line (0.718) and
the constant k (0.069) are in agreement with several previous
studies (see references in Armstrong, 1990 and Harvey &
Krebs, 1990). Also, the correlation coefficient is extremely
high, thus, for most mammals 95% of the variability in brain
mass can be accounted for by the variability in body mass.
The equation calculated for primates (excluding homi-
The slope of this regression (0.756) reflects a similar pattern
of scaling of primate brain mass versus body mass when
compared with other mammals, but primates appear to
have a greater brain mass relative to body mass than most
mammals (as reflected in the higher constant, k=0.100).
Again r2is high, with 94% of the variability in brain size of
primates being accounted for by changes in body size.
The scaling of brain mass and body mass in hominid
species, both extinct and extant is given by:
The slope of the line (1.793) appears steeper than that seen
for mammals (equation 1) and primates (equation 2)
(although P=0.059 using the mean squares between and
within slopes, indicating that while the slopes calculated
by the regression analysis are not statistically different, the
P value is close to significance, possibly as a result of the
Paul R. Manger
small sample size for hominids compared to mammals); r2
is lower so that for hominids, only 87% of the variability in
brain mass can be accounted for by body mass variation.
For the odontocetes the regression equation is:
(r2=0:793; P=1:1r10x11), (4)
and for all cetacean species (odontocetes+mysticetes):
For odontocetes, the slope of the line, at 0.469, is signifi-
cantly less steep than that of the other mammalian groups
examined (P=1.6r10x8, using the mean squares between
Fig. 2. (A) Plots of the raw data of brain (Mbr) and body mass (Mb) of a variety of mammalian species. The present analysis
examined four groups, mammals in general (black circles), primates (open circles), hominids (open squares), and cetaceans (odon-
tocetes – triangles, mysticetes – stars). (B) Regression lines and allometric equations of the various groups examined in the present
analysis. Note the altered scaling for both hominids and cetacean species from that seen for mammals and primates. The data used
in this plot are derived mainly from Crile & Quiring (1940), and other sources listed in Table 1.
Cetacean brain evolution and thermogenesis
and within slopes). For all cetaceans (equation 5), the slope
flattens even more, at 0.376 (comparison with the other four
groups using the mean squares between and within slopes
P=9.1r10x26). Note that cetaceans vary from the general
mammalian, or primate brain-body mass scaling in the op-
posite direction to the trend shown by hominids. For the
odontocete cetaceans and all cetaceans, only 80% or 81%,
respectively, of the variability in brain mass can be ac-
counted for by variability in body mass.
These calculations indicate that the brain mass versus body
mass relationship in cetaceans differs significantly from that
for other mammals while the hominid data also suggest a
different trend (see above). Analyses of individual orders of
mammals give slopes in the range of 0.55–0.66 (see the
evolutionary analysis of ungulates in Section VI and Fig. 12;
and the results of the studies referenced in Armstrong,
1990). We can conclude that while there is a trend for in-
creasing brain size with increasing body size in cetaceans
and hominids, in accordance with the general trend in
mammals (and indeed in other vertebrates), there must
be additional factors causing the observed differences in
scaling. The altered scaling of cetaceans is in the opposite
direction to the trend seen in hominids, and while cetaceans
are fully aquatic, hominids have remained terrestrial, thus, it
seems likely that different selection pressures acted upon
cetaceans and hominids leading to the observed scaling in
(2) The brain-body mass relationship within a
single species – intraspecific comparisons
Intraspecific comparisons have shown that the brain-body
mass scaling within a single species is quite different to
that of intraordinal and interspecific scaling with a mean
slope of 0.22 (see Armstrong, 1990, and references listed
therein). Thus, an individual twice the body mass of a
conspecific is likely to have a brain 20.22, or 116.47%, larger.
This scaling has been found in a range of mammalian
species, including humans, various primates, moles, dogs,
sheep, pigs, raccoons and ferrets (see references in
Armstrong, 1990). The curious exception to this general
consensus is the domestic cat, where the slope was 0.67,
closer to the intraordinal or interspecific scaling values
While intraspecific analyses of cetacean species are
available (Pilleri & Gihr, 1970), a reanalysis of these data
with additional data from other publications (e.g. Ridgway,
1990) is undertaken here. Only data judged to be reliable
are used, thus, individual data points that lie grossly out
of the normal range of the adult, presumably indicating
either a juvenile or sick animal, were excluded. Moreover,
data where body mass was estimated rather than measured,
such as for the larger cetaceans, were also excluded.
Intraspecific analyses were undertaken on Lagenorhynchus
Phocoenoides truei, Delphinus delphis, and Tursiops truncatus [data
from Pilleri & Gihr (1970) except Tursiops truncatus which
were from Ridgway (1990)]. Allometric equations, as de-
scribed above, were calculated for each of these species
These allometric equations have slopes ranging between
0.329 and 0.728, which appear to differ from the slope of
0.22 found for the majority of mammalian species pre-
viously studied (Armstrong, 1990). In the above intraordinal
analyses of the odontocetes (eq. 4) and all cetaceans (eq. 5),
the slopes were 0.469 and 0.376. The intraspecific allometric
Fig. 3. Intraspecific scaling of brain mass (Mbr) versus body mass (Mb) for five cetacean species. Data are derived from Pilleri & Gihr
(1970), and Ridgway (1990).
Paul R. Manger
slopes are very close to these values, with one exception, that
of Phocoenoides truei, where the slope was 0.728. The range of
slopes, and lower correlation coefficients, found in the in-
traspecific analysis may be due to the small data sets.
However, to a first approximation the general trend for
intraspecific scaling of brain and body mass in cetacean
species is similar to that found for the intraordinal allometric
scaling (in all cases the calculated regression slopes for indi-
vidual cetacean species are not significantly different to that
of the slope calculated for odontocetes using the mean
squares between and within slopes: T. truncatus vs odonto-
cetes, P=1; D. delphis vs odontocetes, P=1; P. truei vs
odontcetes, P=1; S. coeruleoalba vs odontocetes, P=1;
L. albirostris vs odonocetes, P=1).
It has been proposed that: ‘If species-specific differences
arose through natural selection, one obvious hypothesis is
that individual differences within a species would have
the same slope, so that selection for a bigger body (or brain)
would scale the correlated feature to the appropriate
size.’ (Armstrong, 1990). This clearly is not the case for
most mammals (Armstrong, 1990); however, the scaling
of intraspecific differences in brain and body mass in cet-
aceans is similar to the intraordinal scaling of these species.
It is therefore likely that natural selection, via a specific
selection pressure, initiated the altered scaling of brain
and body in cetaceans, and that this selection pressure
continues to influence brain-body scaling in extant cetacean
species. Thus, identification of a selection pressure in-
fluencing the scaling seen in extant cetaceans could also
explain the evolution of the difference in scaling of the entire
(3) The encephalisation quotient
Jerison (1973) suggested that the encephalisation quotient
(EQ), i.e. the relative amount of brain per unit body size, can
be used as a direct estimate of the intelligence of a species.
This use of the EQ is encapsulated by Gibson (2001, p. 3):
‘In Jerison’s framework, mammals were the most intelligent
vertebrates, and those mammals whose brain size exceeded
the predicted brain size of other mammals of similar body
size were the most intelligent mammals.’ While a superficial
examination of the data seems to fit intuitive reasoning
concerning the intellectual abilities of certain species, this
proposal has not stood up to scrutiny as a measure of bio-
logical intelligence (Harvey & Krebs, 1990). Despite this, the
modern literature on cetacean brain-body allometry still
uses the EQ as cause for speculation on the intellectual ca-
pacities of cetaceans (e.g. Marino, 1998).
I have recalculated the EQs of all cetaceans using the
allometric equation obtained for most mammals (eq. 1). The
choice of a reference group is a much-debated issue in the
study of allometry (Bauchot & Stephan, 1966; Jerison,
1973; Stephan et al., 1981), however, as we are investigating
differences between cetaceans and other mammals, the use
of equation (1) is appropriate. The EQs of cetaceans (Fig. 4)
show that some species have large EQs (second only to
humans) while some have very low values (lower than the
average mammalian EQ of 1). The range of values seen is
not surprising, as the slope of the allometric equation for
brain mass: body mass for cetaceans (Fig. 2B) is quite shal-
low, intersecting the regression lines derived for most
mammals and for primates. The raw data plot (Fig. 2A),
shows that some cetaceans fall well above the regression
lines for most mammals and primates, while some are well
The calculation of the EQ is a relatively simple matter
and, to an extent, the conclusions drawn are dependent on
the species included in the data set. For example, Marino
(1998) calculated the EQ of odontocete cetaceans, however,
did not include published data for several key odontocete
species. The exclusion of such species as Physeter catadon,
which has both a large brain and body mass is likely to alter
the outcome of this analysis: the slope calculated for the
brain: body mass scaling of odontocetes by Marino (1998) is
0.53, which is statistically similar to that found in the present
study: 0.469, equation (4) [comparison of the regression
slopes calculated for the data of Marino (1998) compared
with that used in the present study for odontocetes only re-
vealed no significant difference (P=0.275) using the mean
squares between and within slopes]. The inclusion of the
mysticetes into the regression analysis leads to a significant
shallowing of the slope of the regression: 0.38, equation (5)
[comparison of the regression slopes calculated for the data
of Marino (1998) compared with that used in the present
study for all cetaceans revealed a significant difference
(P=0.029) using the mean squares between and within
slopes]. Conclusions regarding ordinal encephalisation lev-
els should aim to include as many data points as possible.
Marino (1998) only included odontocetes with similar brain
mass: body mass ratios to the anthropoid primates (see Fig.
1 in Marino, 1998). Not surprisingly therefore Marino
(1998) concludes: ‘… the gap between human and non-
human levels of encephalisation (and, in a general way, in-
telligence) is substantially narrowed by a nonprimate
group …’. Marino (1998) goes on to assert that cetaceans,
especially the highly encephalised Delphinidae, are second
only to humans in intelligence. While the EQ is a useful
allometric measure (see Section VIII), it is difficult to resolve
this as a measure of biological intelligence as proposed by
Fig. 4. Bar graph of the encephalisation quotients (EQs) of
extant primates and cetaceans.
Cetacean brain evolution and thermogenesis
Jerison (1973). The high EQ values found in some cetaceans
may simply be due to the altered allometric scaling of brain
and body masses.
III. THE CETACEAN CEREBRAL CORTEX
The cerebral cortex is the most complex information-
processing station in the brain of all mammals. It is thought
to be central to many major processes, such as intra- and
inter-sensorial perceptual binding, and long-term memory,
and is believed by many to be essential for complex cogni-
(1) Lamination of the cetacean cerebral cortex
Several previous studies have described the cytoarchi-
tectural features and lamination of the cerebral cortex of
cetaceans. The majority of these reach conclusions that do
not differ from much earlier examinations (Major, 1879).
A brief overview of the cytoarchitecture of the cetacean
cerebral cortex is provided here with representative ex-
amples shown in Fig. 5.
Fig. 5. Nissl-stained sections of the cerebral cortex in three cetacean species from different families. Cortical layers 1–3, 5 and 6 are
identified in B and E. A–C are from putative primary visual cortex (V1); D–F are from putative primary auditory cortex (A1). A and
D are from a beluga whale (Delphinapterus leucas, brain mass 2083 g), B and E from a pilot whale (Globicephala melas, brain mass 2673 g),
and C and F from a goose-beaked whale (Ziphius cavirostris, brain mass 2004 g). Features of the cetacean cortex, such as a lack of the
granular layer 4, poor columnar organisation, thick layer 1, unclear lamination of layers 3 to 6, low cellular density, and high glia
density, among others, are evident in these sections of primary sensory cortex. Scale bar=500 mm, applies to all panels. The
photomicrographs used in this figure were generously supplied by Patrick Hof from the Morgane-Jacobs-Glezer marine mammal
Paul R. Manger
Several authors comment upon the thickness of layer 1
across the entire cetacean cerebral cortex (e.g. Haug, 1987;
Hof et al., 2000; Kesarev, Malofeyeva & Trykova, 1977;
Kojima, 1951; Revishchin & Garey, 1991). Layer 2 is
generally acknowledged to be the most cell-dense, thinnest,
and distinct layer in the cetacean cerebral cortex. More-
over, it is regularly reported that the majority of neurons
in layer 2 are pyramidal in nature, with a scarcity of
granular neurons, i.e. a ‘pyramidalisation’ of layer 2 has
occurred (e.g. Kojima, 1951; Manger et al., 1998; Pilleri &
Gihr, 1970). Layer 3 is a relatively thick cortical layer
in cetaceans, and is composed of a moderate density of
large pyramidal cells. The size of the pyramidal cells in-
creases with depth in this layer (Kojima, 1951), and some
authors have described sublamina on this basis (Morgane,
Glezer & Jacobs, 1988). Almost all authors agree that layer 4
is either absent or extremely underdeveloped (e.g. Breath-
nach, 1960; Glezer, Hof & Morgane, 1998; Hof et al., 1994,
2000; Kesarev et al., 1977; Kojima, 1951; Morgane et al.,
1988). Glezer, Jacobs & Morgane (1988) describe layer
4 as ‘incipient’. Layer 5 appears to show little regional
differences in thickness. It is especially prominent in the
motor region of the cortex, due to the giant cells of
Betz. However, the border between layers 3 and 5 is
often described as indistinct (e.g. Breathnach, 1960; Kesarev
et al., 1977; Kojima, 1951). Layer 6 is also found in all
regions of the cortex and is made up of several neuronal
types including scattered large pyramidal, round and stellate
neurons (e.g. Breathnach, 1960; Kesarev et al., 1977;
Three points of interest emerge from the above: the
lamination of the cetacean cerebral cortex is not distinct;
layer 2 exhibits ‘pyramidalisation’; and layer 4 appears to
be largely absent. Various names have been given to the
type of cerebral cortex exhibited by the cetaceans; however,
Brodmann’s (1909) terminology appears most appropriate.
On the basis of the lack of layer 4, cetacean cerebral cortex
is a ‘heterotypical formation’ resulting from a reduction in
the number of cortical layers. This is supported by the ob-
servation of a thin layer 4 in the visual cortex of the bottle-
nose dolphin during development (Garey & Leuba, 1986).
Brodmann (1909) also noted the pyramidalisation (Pilleri &
Gihr, 1970), or the ‘secondary transformation’, of the neur-
onal elements of layer 2 in various species of mammals. The
laminar organisation of the cetacean cerebral cortex should
thus be considered a heterotypical formation in which layer
2 has undergone a secondary transformation specific to the
(2) Parcellation of the cerebral cortex
An increase in the number of cortical areas is commonly
thought to reflect an increase in behavioural complexity.
Kaas (1995) stated that: ‘… the functioning of large brains
may be enhanced by having more subdivisions’. The num-
ber and organisation of cortical areas in several species of
mammals has been studied, however, few attempts have
been made to subdivide the cortex of the cetaceans.
Subdivision of the cortex can be assessed using several
techniques; however, those used on the cetacean cortex are
limited to cytoarchitectural analysis and a small amount of
The large surface area of the cerebral cortex of the cet-
aceans makes parcellation a daunting task, especially under
the generally accepted paradigm that larger brains are com-
posed of more sensory subdivisions (Kaas, 1995). However,
several studies have localised regions of bottlenose dolphin
neocortex using cytoarchitectural techniques (Garey &
Leuba, 1986; Kesarev et al., 1977; Kojima, 1951; Manger
et al., 1998; Morgane et al., 1988) and electrophysiological
recording (Bullock & Gurevich, 1979; Ladygina, Mass &
Supin, 1978; Lende & Akdikmen, 1968; Lende & Welker,
1972; Sokolov, Ladygina & Supin, 1972). These provide a
reasonable degree of detail regarding localisation of areas
within the bottlenose dolphin cortex (Fig. 6).
Kesarev et al. (1977) describe six major cytoarchitectonic
regions within the dolphin neocortex (Fig. 6A–D). These
regions are in turn subdivided into one or more cytoarchi-
tectonic fields. Physiological observations have provided
details of the locations of sensory projection areas in the
neocortex, these being visual and auditory (Ladygina et al.,
1978; Sokolov et al., 1972) and somatosensory and motor
areas (Lende & Akdikmen, 1968; Lende & Welker, 1972)
(Fig. 6E–H). There appears to be good correlation between
the cytoarchitectural and electrophysiological observations.
Kesarev et al. (1977) describe a region of cortex that they
term occipital (O), located on the occipital and posterior
midline cortex. This region corresponds to regions of cortex
responsive to visual stimulation (Ladygina et al., 1978;
Sokolov et al., 1972). Kesarev et al. (1977), Morgane et al.
(1988) and Sokolov et al. (1972) describe three cytoarchitec-
tonic fields within this region, one of which probably corre-
sponds to primary visual cortex (described as medial
occipital area, Om; heterolaminar; and short latency, re-
spectively in these three publications). Photomicrographs of
sections through this region suggest that layer 4 may be
present although cells that are granular in appearance are
interspersed within lower layer 3 and upper layer 5 (Kesarev
et al., 1977). The second cytoarchitectonic field (described as
superior occipital, Os; homolaminar; and long latency,
respectively) may correspond to extrastriate visual cortex;
however, this region has not been subdivided into multiple
areas as in other mammalian species, as no further studies
have examined this region of the cetacean cortex. The third
cytoarchitectonic field, the borderline medial occipital area
(Olm), lies in a position postero-medial to the Om, and exhi-
bits an architecture that indicates that it might correspond to
the splenial visual area of other mammals (assuming that
Om is primary visual cortex) (Rosa, 1999).
Lateral to the occipital cortex, Kesarev et al. (1977)
describe a large region of dorsal surface cortex, which they
term parietal cortex (P). This region corresponds with the
region known to be responsive to auditory stimulation
(Ladygina et al., 1978; Sokolov et al., 1972). This P region
has been subdivided into four cytoarchitectonic fields
(superior parietal Ps, medial parietal Pm, inferior parietal
Pi, and transitional parietal Pli), each of which is likely to
represent an auditory cortical area. It is unclear which
cytoarchitectonic field represents primary auditory cortex
and which are secondary or tertiary auditory areas.
Cetacean brain evolution and thermogenesis
Fig. 6. Parcellation of the cetacean cerebral cortex demonstrating the architectonic and physiological subdivisions of the cerebral
cortex of the bottlenose dolphin. A–D are redrawn from the architectonic subdivisions of Kesarev et al. (1977). The regions are
labelled according to the original publication as follows: Cl, central lateral area; Cm, central medial area; Fl, frontal lateral area;
Paul R. Manger
Lateral and posterior to both the occipital and parietal
regions of cortex is an underdeveloped wedge-shaped piece
of cortex termed temporal cortex (T) by Kesarev et al.
(1977). This is likely to correspond to the temporal cortex
of other mammalian species, an assumption based on its
location relative to the visual and auditory regions. It is
composed of two cytoarchitectonic fields, the internal tem-
poral area (Ti) and the external temporal area (Te). Anterior
to both the occipital (visual) and parietal (auditory) regions
of cortex lies a region designated as central (C) by Kesarev
to somatosensory stimulation (Ladygina et al., 1978; Lende
& Welker, 1972; Sokolov et al., 1972) and that producing
motor actions upon electrical stimulation (Lende &
Akdikmen, 1968). Kesarev et al. (1977) described central
lateral (Cl) and central medial (Cm) cytoarchitectonic fields;
Cl appears to correspond to somatosensory cortex and Cm
to primary motor cortex. The Cm region appears to corre-
spond to the region designated primary motor cortex in the
sperm whale by Kojima (1951) (Fig. 7), due to the presence
of Betz cells (Kesarev et al., 1977).
Anterior to central cortex (somato-motor cortex) is a small
region designated frontal (F) by Kesarev et al. (1977). This
region is composed of frontal lateral (Fl) and frontal medial
(Fm) cytoarchitectonic fields, and is located on the most
anterior pole of the cerebral cortex. On topological grounds,
one might be tempted to designate this region prefrontal
cortex; however, several observations indicate that this is
probably not the case. The exact definition of prefrontal
cortex across mammals is a complex and much debated
issue (e.g. Divac & O¨berg, 1990; Preuss, 1995); however,
this debate may be avoided by a closer examination of the
cytoarchitecture of this region. The feature of most interest
is the presence of numerous giant pyramidal cells in this
regionofcortex(dolphin – Langworthy,1932;Kesarevetal.,
1977; sperm whale – Kojima, 1951) (Fig. 7). These cells
exist in primary motor cortex and premotor cortex of other
species of mammals (Brodal, 1968, 1978, 1980) (Fig. 7), and
give rise to the cortico-pontine projection. They are not
found in prefrontal cortex. This observation suggests that
this region of cortex is premotor cortex, and stimulation
of this region does produce motor movements (Lilly, 1962).
One must note that this cytoarchitectonically distinct region
of cortex extends to the most anterior portion of the cerebral
cortex, thus, if there is a region of cortex that may be defined
as prefrontal in the cetaceans, it is very small.
On the medial surface of the hemisphere, located be-
tween the corpus callosum and the cingulate sulcus, is the
region of cortex defined as limbic cortex (L) by Kesarev et al.
(1977) (Fig. 6). Compared to other mammals, this region of
cortex is rather reduced in size, and probably corresponds to
cingulate cortex. Kesarev et al. (1977) describe five cyto-
architectonic fields in this region but also note the rather
homogeneous nature of this cortex. Finally, on the medial
bank of the insular cortex, entorhinal cortex has been
located, in a topological position that is consistent with
its location in other mammals (Manger et al., 1998).
The assignations of the cortical regions given above are
consistent with studies of thalamocortical connectivity in
cetaceans (Revishchin & Garey, 1990). Within the realms of
interspecies comparisons, it therefore appears that the
overall topology of the areal subdivision of cerebral cortex in
cetaceans does not differ dramatically from that seen in
other mammals. However, four points of importance
emerge: there does not appear to be a prefrontal cortical
region; the number of subdivisions of the cortex appears to
be low compared with other mammals with similarly sized
brains or even mammals with far smaller brains; the tem-
poral cortical region is small and undeveloped; and the
limbic region of cortex, or cingulate cortex, is small,
especially in its anterior aspect.
(3) Columnar organisation of the cerebral cortex
Vertically oriented columnar structures within the sensory
cerebral cortex have been identified in a range of mam-
malian species. These include several distinct types, from the
physiological columns first described by Mountcastle (see
review by Mountcastle, 1997), that often correspond to
anatomically identifiable modules (e.g. Manger et al., 1998),
to the microcolumns (or minicolumns) that make up the
larger cortical columns (Jones, 2000). These radially or-
ganised columns cross layer boundaries and are thought to
represent the fundamental processing units of the sensory
cerebral cortex. In cetaceans, visually identifiable cortical
columnar organisation has only been reported in the
entorhinal cortex of the bottlenose dolphin (Manger et al.,
1998). It is difficult to identify columnar and microcolumnar
organisation in the photomicrographs of architectonically
defined regions of dolphin brain provided by Kesarev et al.
(1977), whereas these features are readily identifiable in the
cortex of other mammals (Jones, 2000; Manger et al., 1998;
Fm, frontal medial area; La, anterior limbic area; Lla, anterior borderline area; Llp, posterior transitional, or borderline, limbic
area; Lp, posterior limbic area; Ls, anterior subgenual area; Olm, borderline medial occipital area; Om, medial occipital area; Os,
superior occipital area; Pi, inferior parietal area; Pli, transitional parietal area; Pm, medial parietal area; Ps, superior parietal area;
Te, external temporal area. (E) The approximate locations of primary somatosensory (S1) and primary motor (M1) cortex from the
mapping studies of Lende & Akdikmen (1968) and Lende & Welker (1972). Note the correspondence of the partial maps to the areas
termed Cl and Cm by Kesarev et al. (1977). (F) Architectonic and physiological locations of visual cortex from the studies of Morgane
et al. (1988) and Sokolov et al. (1972). It appears that the heterolaminar and short latency regions correspond to V1 of other
mammals. Note the correspondence between these regions and the regions termed Os and Om by Kesarev et al. (1977). (G, H)
Physiological subdivisions of dolphin cerebral cortex from Ladygina et al. (1978). Note the correspondence of the visually responsive
cortex to regions Os, Om and Olm, auditory to regions Pi, Pli, Pm and Ps, and somatosensory to Cl, in the scheme of Kesarev et al.
(1977). The location of entorhinal cortex is from Manger et al. (1998). Scale bar in C applies to all panels.
Cetacean brain evolution and thermogenesis
Mountcastle, 1997). Despite this Morgane et al. (1988)
identified two radially oriented columnar structures in dol-
phin visual cortex using computer-assisted methods: minor
columns with diameters of around 20 mm, significantly
smaller than the mean of 56 mm found in other mammals
(Mountcastle, 1997); and major columns, approximately
168 mm diameter, which are again smaller than the cortical
columns or modules (range 250–1000 mm) found in the
cortex of other mammals (Manger et al., 1998). Morgane
et al. (1988) note that these columns are often discontinuous
across the cortical layers.
(4) Neuronal morphotypes within the
One major feature of the mammalian cerebral cortex is the
diversity and complexity of the neuronal morphology.
Several studies have found a low diversity of neuronal types
Fig. 7. The location of the giganto-pyramidal cells that indicate the origin of the cortico-pontine tract in the macaque monkey
(Brodal, 1978, 1980), domestic cat (Brodal, 1968), and sperm whale (Kojima, 1951). Note the high density of these cells in primary
motor cortex (M1) and the moderate density in premotor cortex (Pre-M). None of these cells are seen in prefrontal cortex of the
macaque monkey or domestic cat. However, there appears to be no region anterior to the origin of the corticopontine tract in the
sperm whale that would indicate the presence of a prefrontal cortical region.
Paul R. Manger
in the cerebral cortex of odontocete cetaceans. These studies
confirm that the majority of cortical neurons are pyramidal
in nature, they have a few simple shapes, and there is sparse
ramification of the dendrites (Kesarev, 1971; Kesarev et al.,
1977; Glezer et al., 1988; Morgane, Jacobs & Galaburda,
1985; Morgane et al., 1988; Morgane, Glezer & Jacobs,
1990). An interesting feature to emerge from these studies
is the presence of extraverted pyramidal neurons in layer 2.
These neurons exhibit a dendritic ramification into layer 1
and, by comparison with other pyramidal neurons of cet-
acean cerebral cortex, are quite spinous. These neurons are
not a common feature of the cerebral cortex of other
mammals. The majority of pyramidal neurons in the cet-
acean cerebral cortex exhibit triangular, club-shaped or
clavate-type soma, which are thought to indicate a poor
(Morgane et al., 1990).
Non-pyramidal, or stellate, cells make up around 12% of
the neuronal population in odontocete cetacean cortex
(Morgane et al., 1985). The majority of these neurons are
of the long-radiator type, which is thought to represent
an undifferentiated neuronal morphology (Morgane et al.,
1990). Stellate neurons of the short-radiator type have been
reported only occasionally (Morgane et al., 1985, 1990).
In a series of studiesHofet al.(1999, 2000) and Glezer etal.
(1998) used calcium-binding protein immunohistochemistry
network. Many neurons immunoreactive for the calcium-
binding proteins, calbindin, calretinin and parvalbumin are
also immunoreactive for c-aminobutyric acid (GABA) and
are thus considered to be inhibitory. Cetaceans have a high
proportion of calbindin- and calretinin-immunoreactive
neurons compared to those showing parvalbumin im-
munoreactivity (approximately 4:1), whereas the ratio is
closer to 1:1 in primates and rodents (Hof et al., 1999, 2000;
Glezer et al., 1988). However, cetaceans have almost twice as
expressed as a proportion of total neuronal number (Hof
et al., 2000). In cetaceans, calbindin- and calretinin-
immunoreactive cells are found mostly in the upper cortical
layers, while parvalbumin-immunoreactive cells are located
in the lower cortical layers. The diversity in neuronal
morphologies of these inhibitory neurons is low in cetaceans
compared to many other mammals (Hof et al., 1999).
Calbindin- and calretinin-immunoreactive neurons have
been implicated in the flow of inhibitory influences in the
vertical dimension in cerebral cortex, i.e. within a cortical
column, and parvalbumin-immunoreactive cells function in
horizontal inhibitory flow, i.e. between cortical columns.
The high proportionof
immunoreactive cells in cetacean cerebral cortex suggests
marked vertical inhibitory influences. This, combined with
a low diversity in neuronal morphology, might indicate a
high degree of monotonous specificity in vertical infor-
mation processing, which might be seen as indicative of
detailed perceptual abilities. By contrast, the relative paucity
of parvalbumin-immunoreactive cells indicates a lack of
horizontal inhibitory influences, potentially characterizing
inefficient horizontal processing between cortical columns,
and suggesting poor integrative abilities.
(5) Allometry of the cerebral cortex: the
corticalisation index (CI)
Glezer et al. (1988) used the percentage of the total brain
volume that is cerebral cortex [the corticalisation index (CI)]
to assess the relative size of the cerebral cortex in cetaceans.
They compared the CI of bottlenose dolphin against two
species of insectivores and six primates and found that the
CI of the bottlenose dolphin was significantly smaller than
that of these other mammals.
I have repeated this analysis with the addition of futher
species (see Table 2), and calculated the CI using two dif-
ferent methods. First, the CI was calculated as the total
combined volume of the grey and white matter of the cer-
ebral cortex expressed as a percentage of brain volume.
Fig. 8A shows the CI calculated using this method plotted
against brain volume. Using this method, we see that the
cetaceans show similar CIs to those of the simian primates.
The average CI for simian primates was 70.22% (range
66.09–84.02%), and for odontocete cetaceans 72.14%
(range 70.39–73.40%). Both these groups cluster above
the average and range found for other mammals (average
(average 49.57%, range 33.87–59.55%), and insectivores
(average 23.67%, range 11.84–57.31%). This analysis
indicates that the amount of the odontocete brain devoted
to grey and white matter of the cerebral cortex is compar-
able to that in simian primates, but greater on average
than that seen in prosimians, other mammals and in-
In the second method CI was calculated as the volume
of the grey matter of the cerebral cortex expressed as
a percentage of brain volume (see Table 2 and Fig. 8B).
Using this method, a slightly different picture emerges.
The simian primates have an average CI of 52.69% (range
49.17–56.07%), while the odontocete cetaceans have an
average CI of 40.56% (range 36.14–42.44%). Thus, this
second method separates the odontocete cetaceans from the
simian primates. Moreover, they average less than the other
mammals (average 47.29%, range 40.13–56.73%) included
in this analysis, and the one prosimian used (CI=49.08%),
but higher than the insectivores (average 28.49%, range
26.31–30.03%). The single mysticete for which data was
available had a CI of 20.53%.
These two analyses offer somewhat contradictory views.
Using the first method, the odontocete cetaceans group with
the simian primates, indicating that in these two groups,
similar amounts of the total brain volume is devoted to the
grey and white matter of the cerebral cortex. But when
only the grey matter of the cerebral cortex is used (method
2), the odontocetes have a smaller CI than the simians and
other mammals used in this analysis. This indicates that
while much of the odontocete brain is occupied by the
cerebral cortex, as in simians, the amount of grey matter
in odontocete (and mysticete) cetaceans is less than that
of simians and other mammals of similar brain sizes.
This indicates that a greater proportion of the cerebral
cortex of cetaceans is occupied by white matter, which
connects the various regions of the brain, rather than
by grey matter where neuronal computation occurs. This
Cetacean brain evolution and thermogenesis
Table 2. Calculation of the corticalisation index (CI) (see Fig. 8). The brain volume was calculated as brain mass divided by the
specific gravity of brain tissue (1.036; Stephan et al., 1981) where not directly provided in the source. The CI was calculated using
two methods: (1) total volume of grey and white matter of cerebral cortex (neocortex plus schizocortex as defined by Stephan et al.,
1981), expressed as a percentage of brain volume, or as otherwise described in the text; (2) volume of grey matter only, expressed as
a percentage of brain volume. Where it was not given in the original reference, the cortical volume was calculated by multiplying
the cortical surface area by 0.175, which is the maximum cortical thickness reported for Tursiops truncatus (range 1.3–1.75 mm;
Ridgway & Brownson, 1984). Data sources: (1) Hofman (1985, 1988); (2) Ridgway & Brownson (1984); (3) Kesarev et al. (1977);
(4) Stephan et al. (1981); (5) Pirlot & Nelson (1978); (6) Reep & O’Shea (1990); (7) Schwerdtfeger et al. (1984).
(grey only, cm3)
Paul R. Manger
Table 2 (cont.)
(grey only, cm3)
(method 2) Source
Cetacean brain evolution and thermogenesis
suggests that less of the cetacean cerebral cortex is devoted
to computation, and more is occupied by wiring, which
may impact negatively on the computational power of the
(6) Neuronal density, the glia:neuron index, and
the composition of the neuropil
Previous authors have noted that there is a very low neuro-
nal density in the cetacean brain, ranging between 34000
and 50000 neurons mmx3in Tursiops truncatus (Morgane
et al., 1988), 65444 mmx3in Globiocephala melaena (Pilleri &
Gihr, 1970), and 13112 mmx3in Balaenoptera physalus (Pilleri
& Gihr, 1970). This low neuronal density has been stated
to be a correlate of brain size (Haug, 1987; Prothero,
1997). However, neuronal density from homologous cortical
areas in different cetaceans has not been examined system-
atically even though it is well known that neuronal density
differs in different areas of the cortex. The neuronal density
even differs among different studies in the same species,
which is a cause for concern [for example compare values
in Haug (1987), and Prothero (1997)]. In other mammals,
the neuronal density in primary motor cortex (area 4)
has been quantified: Mus musculus – 950000 mmx3; Cavia
cobaya – 538000 mmx3; Rattus rattus – 502000 mmx3; Lepus
cuniculus 302000 mmx3; Felis domesticus – 242000 mmx3;
Canis familiaris – 204000 mmx3; Bos taurus – 174000 mmx3;
Capra hicus – 172000 mmx3; Ovis aries – 170000 mmx3; Sus
scrofa 115000 mmx3; Equus caballus – 115000 mmx3; Homo
sapiens – 163000 mmx3(Chow, Blum & Blum, 1950).
Reichenbach (1989) showed that the glia:neuron index
increases with increasing thickness of the cerebral cortex
(see his Fig. 3); however, his analysis did not include
cetaceans. The glia:neuron index from the cerebral cortex
of two species of cetaceans, the bottlenose dolphin
(values ranging from 2:1 to 3:1; Garey & Leuba, 1986)
and the fin whale (4.5:1 to 5.9:1; Hawkins & Olszewski,
1957), are available to compare with the allometric re-
lationship derived by Reichenbach (1989). The cetacean
cerebral cortex ranges between 1 and 2 mm in thickness
(e.g. Ridgway, 1990) and from the allometric relation-
ship determined by Reichenbach (1989), the predicted
glia:neuron index for cetaceans would be 0.2:1–0.7:1.
Thus it appears that the cetacean cerebral cortex has a
substantially higher proportion of glia than is found in other
One of the most important features of the neocortex in
terms of computational abilities is thought to be the com-
position and amount of neuropil. Here, the term neuropil
refers to that part of the cerebral cortex that is not occupied
by neuronal and glial cell bodies and blood vessels. Thus,
the neuropil is that fraction of the cerebral cortex made up
of axons, dendrites, boutons, spines, glial processes, myelin
sheaths, and extracellular space. Chklovskii, Schikorski &
Stevens (2002) found that the cerebral cortex of rats is
organised in a manner that balances the proportion of
these constituents to ‘optimize the wiring’ of the cerebral
cortex, such that axons and dendrites occupy around 60%
of the neuropil volume. Several features indicate that this
differs in cetacean cerebral cortex.
As discussed above, there appears to be a high proportion
of glial cells in the cetacean cerebral cortex. It is therefore
reasonable to assume that glial processes occupy a greater
proportion of the neuropil in cetaceans than in other
mammals. The cerebral cortex of cetaceans stains heavily
for myelin (e.g. Manger et al., 1998). Glezer et al. (1988) have
shown that myelinated thalamocortical axons pass through
the cetacean cerebral cortex reaching layer 1 before turning
to branch into the cellular layers. A high density of myeli-
nated axons indicates that a higher proportion of the neuro-
pil is occupied by myelin sheaths. Moreover, the passage
of thalamocortical axons through the cortex will lower the
potential computational volume of the neuropil. Golgi
studies of cetacean cortical neurons indicate a poor degree
of dendritic arborization, as well as a low number of spines
(Kruger, 1966). A smaller percentage of the cetacean
Cl method 1 (%)
Brain volume (cm3)
Cl method 2 (%)
0.11 10 100 100010000
Brain volume (cm3)
Fig. 8. Plots of the corticalisation index (CI) against brain
volume (A, CI calculated using method 1 with cortical
volume=total combined volume of grey and white matter; B,
CI calculated using method 2 with cortical volume=volume of
grey matter only) in a variety of mammal species. The data in
this plot are derived from Table 2.
Paul R. Manger
neuropil is therefore likely to be occupied by dendrites and
spines in comparison with other mammals.
These features indicate that the relative proportions of
the constituents of the cetacean cerebral cortex neuropil are
likely to differ from other mammals. This suggests that the
cetacean cerebral cortex may not be optimally wired
(Chklovskii et al., 2002), presumably impacting negatively
on processing efficacy and power of the cetacean cerebral
IV. THE CETACEAN HIPPOCAMPAL
The hippocampal formation of mammals is composed of
four subregions: the dentate gyrus, the hippocampus, subi-
culum, and entorhinal cortex (Amaral & Soltesz, 1997).
This formation is involved in the assimilation of sensory
and other neural information, interacting with storage
areas to consolidate this information into long-term, or en-
during, memories (e.g. Amaral & Soltesz, 1997). Thus, it
has an indirect, but essential role for cognitive behaviours.
Breathnach & Goldby (1954) and Jacobs, McFarland &
Morgane (1979) give detailed descriptions of the cetacean
hippocampal formation. All four components of the hippo-
campal formation can be found in cetaceans; however, the
hippocampal formation is of relatively small size. Moreover,
other regions of the brain generally associated with the
hippocampal formation, such as the mammillary region,
anterior thalamic nuclei (Breathnach & Goldby, 1954), an-
terior cingulate cortex (Morgane, McFarland & Jacobs,
1982), and prefrontal cortex (see Section III.2), are all also
A quantitative assessment of the hippocampal formation
of cetaceans is difficult due to a lack of data; however, three
values are available: for the harbour porpoise (Phocaena pho-
caena) (Breathnach & Goldby, 1954) hippocampal formation
volume can be calculated to be 10% [hippocampal index
(HI)=0.22%] that found in humans and for two species of
river dolphin, the franciscana (Pontoporia blainvillei) (HI=
0.5%) and the Indian river dolphin or susu (Platanista gang-
etica) (HI=0.75%) (Schwerdtfeger, Oelschla ¨ger & Stephan,
1984) values can be calculated from the given percentage of
total brain volume. These were compared to similar data for
insectivores and primates (Stephan et al., 1981) and mono-
tremes and the opossum (Pirlot & Nelson, 1978), by con-
hippocampal index (HI), or percentage of the brain oc-
cupied by the hippocampal formation. For most mammals
(excluding cetaceans) the HI decreases with increasing brain
size (Fig. 9). However, the data points for cetaceans fall well
below the 95% confidence intervals of the values expected
based on the regression line from other mammals. Thus, in
both actual and relative terms (based on the available sam-
ple of three species), the size of the hippocampal formation
in cetaceans is small, supporting the qualitative impression
derived from the studies of its architecture (Breathnach &
Goldby, 1954; Jacobs et al., 1979). The small relative and
actual size of the cetacean hippocampus becomes more
evident when compared to the enormous and highly con-
voluted hippocampus of the African elephant (Hakeem et al.,
V. SPECIALISATIONS OF THE CETACEAN
There are two significant specialisations of the cetacean
brain (although neither is limited to the order Cetacea) that
to date have not been satisfactorily explained. These are
related to their vocal and sleeping behaviours. The neuro-
anatomical features involved are the nucleus ellipticus of
the periaqueductal grey matter, which is suggested to be
involved with vocalisation, and the neural assembly of the
pontomesencephalon which is proposed to control uni-
hemispheric sleep phenomenology. The vocal capability of
cetaceans is a major factor in the popular assumption that
cetaceans represent an aquatic intellectual counterpart of
humans (Forestell, 2002). The control of sleep is based upon
the release of neurotransmitters from various nuclei in
the brain, several of which reside in the tegmentum of
the pontomesencephalon. The release of these transmitters
in light of the unihemispheric nature of cetacean sleep is
discussed here in relation to central nervous system thermo-
(1) Conspecific communication among cetaceans
Any discussion of vocal communication in cetaceans must
first place their vocal behaviour within the framework of all
conspecific communication between cetaceans. In general,
non-human animals communicate about a limited range of
topics, which include sex, aggression, predators and food,
and they do this via a limited set of signals. Communication
conveys information about the internal state of an individual
to conspecifics by the use of stereotyped vocalisations, pos-
tures or movements.
Hippocampal index HI (%)
Brain mass Mbr (g)
Fig. 9. Allometric plot of hippocampal index (HI) (hippo-
campal volume expressed as a percentage of brain volume)
against brain mass (Mbr). The regression line is based on all data
excluding the three odontocetes.
Cetacean brain evolution and thermogenesis
The skeleto-muscular system of cetaceans limits their
ability to use body language as an effective means of com-
municating internal state, or intentionality, to conspecifics.
First, the facial musculature of cetaceans has atrophied such
that they are no longer capable of facial expressions
(Caldwell & Caldwell, 1972). Second, the loss of limbs limits
their range of body postures. Third, the evolution of a
streamlined body necessary for fast swimming and sub-
cutaneous blubber has resulted in a homogeneous external
morphology. Given these limitations, what are cetaceans
capable of in terms of body language? Madsen & Herman
(1980) list the probable set of body language signals available
to cetaceans including: breaching the water surface, displays
of the ventral body surface, tail slaps, mouth opening, head
nodding and shaking, and some stereotyped gross body
postures and swimming patterns. This body language rep-
ertoire is clearly limited to gross movements.
Olfaction plays an important role in conspecific com-
munication in numerous species. Odontocetes lack olfactory
bulbs, and mysticetes have olfactory bulbs that are atrophied
(reviewed in Ridgway, 1990). Thus, olfactory communi-
cation among cetaceans is likely to be greatly limited in
mysticetes, and absent in odontocetes. Interestingly, the
terminal nerve is present in cetaceans, and the ganglia of the
terminal nerve are quite large (Ridgway et al., 1987). This
structure is thought to be related to chemical signals in-
volved in sexual reproduction; thus, the cetaceans may be
able to communicate reproductive state via the terminal
nerve system, although this may not be intentional com-
munication. The above list should be compared to the esti-
mated set of around 200 paralinguistic elements (plus
thousands of facial expressions) found in humans, which
only slightly exceeds that available to chimpanzees and
rhesus monkeys (Wilson, 1975). It is clear therefore that the
cetaceans lack a significant set of non-vocal communication
The majority of cetacean conspecific communication is
achieved by the use of sound (Herman & Tavolga, 1980;
Ridgway & Au, 1999). The vocal proclivity of cetaceans,
combined with the large size of the brain, has led many
investigators to believe that cetacean vocalisations may
be structurally and functionally as sophisticated as human
language. Lilly (1967) maintained that dolphin vocalisations
represented a language, that they conversed regularly, and
that they were capable of imitating human sounds.
However, numerous rejections of these ideas have been
published (see review by Herman & Tavolga, 1980).
Herman & Tavolga (1980) showed that the repertoire of
dolphin vocalisations that may be used for communication is
quite small: between 5 and 20. Bullock & Gurevich (1979)
concluded that the total vocal repertoire of the bottlenose
dolphin was limited to less than 40 distinct vocalisations.
The greatest number of identifiable vocalisations classified
for a cetacean species is 30 (in seven broad classes) for the
pilot whale, Globicephala melaena (Taruski, 1976, cited in
Herman & Tavolga, 1980).
McCowan et al. (1999) used the principles of information
theory to examine vocalisations of the bottlenose dolphin as
a predictor of their communication capacity. Their results
suggested a certain level of internal structure to be present in
dolphin vocalisations; however, it was clear that higher or-
der entropies, typical of human language, were not found.
Despite these studies, other investigators still persist with the
possibility that dolphins have a language. For example,
Janik (2000) concludes that wild dolphins were addressing
each other at distances of up to 580 m as individuals to in-
itiate conversation. However, a close inspection of these
results reveals that only 39 of 1719 whistles studied (2.27%,
or as stated by the author ‘less than chance’) were classified
as matched interactions (i.e. that two whistles of the same
type produced within 3 s of each other by different dolphins
were judged to be ‘relatively similar’ by five naı ¨ve human
observers). Janik (2000) reports that in three instances a
dolphin whistle was matched by another individual, and
then repeated by the initial dolphin. These matching whis-
tles were limited to the signature whistles of the individual
dolphins, which in some instances are the only vocalisations
that dolphins produce (Janik & Slater, 1998). Thus, the be-
havioural evidence for a cetacean language is at present
The neuronal control of vocalisation in various mam-
malian species has been extensively studied, and the neural
circuitry that underlies vocalisation can be described (re-
viewed by Ju ¨rgens, 1998). Neurons from the anterior
cingulate cortex project to four locations: the medial nucleus
of the amygdala, the hypothalamus, the midline dorsal
thalamus and the lateral periaqueductal grey matter. The
amygdala, hypothalamus, and dorsal thalamus in turn
project to the periaqueductal grey matter. The periaque-
ductal grey matter then projects to the nucleus ambiguus
and nucleus retroambiguus, which constitute the phonatory
motoneurons and premotoneurons controlling the vocal
cords and respiratory muscles. Two interesting features of
the mammalian vocal control system of relevance to the
cetaceans are: (1) the majority of the vocal control system of
the telencephalon belongs to the limbic system; and (2) all
telencephalic control of vocalisation is channeled to the
brainstem through the periaqueductal grey matter.
The limbic system of the dolphin telencephalon has been
the subject of detailed anatomical study (Breathnach &
Goldby, 1954; Kruger, 1959, 1966; Morgane et al., 1982).
These observations indicate that the limbic lobe of the
telencephalon is greatly reduced in comparative terms
(Kruger, 1966; Morgane et al., 1982; Pilleri & Gihr, 1970).
The relative volume of the limbic portion of the dorsal
thalamus of the bottlenose dolphin is approximately half
that seen in other eutherian mammals (Kruger, 1959, 1966);
however, the amygdala appears unchanged, apart from a
specific loss of olfactory connections (Breathnach & Goldby,
Previous studies have shown that the anterior cingulate
cortex of monkeys is important in the voluntary control of
vocalisations (Sutton, Larson & Lindeman, 1974). Thus, as
the cetacean limbic system is reduced, and the anterior
cingulate cortex is both reduced and lacks a granular region,
it is not unlikely that the voluntary control of vocalisation by
cetaceans suffers serious deficiencies. However, as the
amygdala appears normal, we can also conclude that in-
voluntary species-specific intonations provided to vocalis-
ations by this structure (Ju ¨rgens, 1998) are present.
Paul R. Manger
The second relevant feature of importance to emerge is
the channeling of all the telencephalic pathways through the
periaqueductal grey matter (Ju ¨rgens, 1998). This region of
the brain controls the activity of the phonatory motoneurons
and may act as a vocal pattern generator (Zhang et al., 1994).
Studies of mammals and other vertebrates have shown that
natural-sounding species-specific vocalisations are produced
in response to electrical or chemical stimulation of these
neurons (reviewed in Ju ¨rgens, 1994). Moreover, specific calls
are topographically organised within this region and all calls
of a given species are represented here. Lesion or ablation of
this region leads to mutism, even in humans; however, in
humans mute for this reason, language comprehension and
para-linguistic capacities are still present (Esposito et al.,
Within the cetacean mesencephalon is a specialised nu-
cleus, the nucleus ellipticus, which appears to be a par-
cellated elaboration of the ventral and ventral-lateral
periaqueductal grey matter (Fig. 10). This structure is
prominent at birth in the bottlenose dolphin (Fig. 10A), at
which time the calf can vocalise but not produce echolo-
cation sounds (Herman & Tavolga, 1980).As this structure is
a feature of both odontocetes and mysticetes (Jansen, 1969;
Ridgway, 1990), it is unlikely to be related to echolocation
(only found in odontocetes). Rather, the nucleus ellipticus is
likely to be a specialised column of the periaqueductal grey
matter related to vocalisation. If this is correct, it can be
concluded that vocalisations of the dolphin must be mainly
under the control of a mesencephalic structure, with minor
telencephalic influence. This feature of the cetacean brain
indicates a specialised, but probably non-conscious and in-
voluntary, vocalisation-generation system (probably under
significant influence from the amygdala). Interestingly, a
nucleus ellipticus is also found in elephants (Cozzi, Spagnoli
& Bruno, 2001), another species with a specialised vocal
(2) Sleep in cetaceans
One of the more intensely studied specialisations of the cet-
aceans is the physiological and behavioural phenomen-
ology surrounding sleep. That the dolphin may sleep with
half its brain at a time was first suggested by Lilly (1967), and
was later demonstrated physiologically by Serafetinides,
Shurley & Brooks (1972), Mukhametov (1987, 1988, 1995),
Mukhametov & Lyamin (1994), and Mukhametov, Supin &
Polyakova (1977). This form of sleep has been identified
physiologically in five species (see above references and
Mukhametov & Polyakova, 1981; Oleksenko et al., 1994;
Lyamin et al., 2002a) and behaviourally (Flanigan, 1974a,b,
1975a,b,c; Lyamin et al., 2000) in several cetacean species,
and it is likely to be a common feature of sleep in all extant
cetaceans. The generalised sleep pattern observed is alter-
nating approximately 1 h long bouts of slow-wave sleep
(SWS) in each hemisphere, with very small (10–60 s)
amounts of rapid eye movement (REM) sleep interspersed,
either at the end of the SWS period, or in short bursts during
SWS. Very little is known of the neuronal control of uni-
hemispheric sleep in these species. However, results from
other mammals and preliminary observations on cetaceans
(Manger, Ridgway & Siegel, 2003; Pillay & Manger, 2004)
allow some speculations in terms of cetacean brain evolution
The sleep patterns of mammals (and most vertebrates) are
largely under the influence of nuclei located in the ponto-
mesencephalon. In particular, three groups of neurons have
been implicated in the control of sleep, especially REM
sleep (Siegel, 1994). These are the locus coeruleus complex,
which produces noradrenalin, the dorsal raphe nuclei,
which produce serotonin, and the pedunculopontine (PPN)
Fig. 10. Photomicrographs of myelin-stained coronal sections
through the rostral rhombencephalon in a newborn (A) and
adult (B) Tursiops truncatus. These photomicrographs demon-
strate the extreme nuclear specialisation of the ventral lateral
periaqueductal grey matter into the distinct nucleus ellipticus
(n.ell.). This region is located in a topologically similar region to
the vocalisation column of the periaqueductal grey matter in
other mammals, thus, it may be a specialised vocalisation nu-
cleus. At birth bottlenose dolphins can whistle but they cannot
echolocate. A nucleus ellipticus has been found in all odonto-
cetes and mysticetes examined. These photomicrographs are
from sections belonging to the Comparative Mammalian Brain
Collection [http://brainmuseum.org]. Scale bars=5 mm.
Cetacean brain evolution and thermogenesis
and lateral dorsal tegemental (LDT) nuclei, which produce
acetylcholine. Each of these nuclear groups have a specific
pattern of discharge that correlates with different sleep/
wake phases. During wake, the neurons of each group dis-
charge at a random, high average rate; during SWS, the
neurons of each group discharge rhythmically at a slower
rate; and during REM sleep, the neurons of the locus
coeruleus complex and dorsal raphe cease to discharge,
while those of the LDT and PPN fire at a rate and manner
similar to that seen during wake.
As the sleep pattern of cetaceans is modified, the neural
activity of these cell groups might also be modified. Each
hemisphere of the cetacean brain exhibits SWS electro-
encephalogram (EEG) patterns for approximately 4 h per
day, the remainder of the time exhibiting EEG patterns
consistent with waking (Mukhametov, 1995). REM sleep in
cetaceans is cryptic both physiologically (Mukhametov,
1988) and behaviourally (Lyamin et al., 2002b), and is likely
to account for a very small amount of total sleep time in
cetaceans. Anatomical observations of the locus coeruleus
complex (Manger et al., 2003) have not shown features that
might relate to unihemispheric sleep phenomenology. As
the locus coeruleus complex emerges during the phenotypic
stage of development (Clancy, Darlington & Finlay, 2001;
Galis & Metz, 2001), alterations in its function, in both the
developing and adult animal, are unlikely. It is possible that
the firing pattern of locus coeruleus neurons will correspond
to hemispheric sleep EEG patterns seen in other mammals.
Thus, during wake, the neurons of the locus coeruleus will
discharge at a high constant rate, and will slow unihemi-
spherically during SWS. As there is little REM sleep, there
will be only very short periods when these neurons are in-
active. If these predictions are correct the cetacean brain
will be virtually in constant receipt of noradrenalin and
serotonin; with no time period when their brain is deprived
of these neurotransmitters, as happens in bihemispheric
sleeping mammals during REM sleep.
One of the major effects of neuronal production of
noradrenalin is the facilitation of skeletal muscle tone
(Siegel, 1994; Kiyashchenko et al., 2001). In mammals
30% of the heat production required to maintain body
temperature is met by basal muscle tone (Gisolfi & Mora,
2000). The ability to maintain body temperature is likely
to be a strong selection pressure on cetaceans, as heat
loss in water is 90.8 times faster than in air at the same
ambient temperature (Downhower & Blumer, 1988). Con-
tinually maintaining muscle tone would be a consistent
source of heat production. Unihemispheric sleep, as well
as allowing breathing and maintenance of body position
in the water, could also facilitate thermoregulation. Com-
bined with other features of cetacean thermoregulation
(Hokkanen, 1990) unihemispheric sleep could be an adap-
tation to ensure maintenance of body temperature in
an extremely thermally challenging environment (Pillay &
It has been suggested that one role of glia in the vertebrate
brain is thermogenesis (Donhoffer, 1980; Szele ´nyi, 1998).
The metabolic activity of glia is increased by exposure to
noradrenalin, significantly above increases in neural metab-
olism (Donhoffer, 1980; Stone & Ariano, 1989). If the
cetacean brain does have consistently high levels of
noradrenalin the glia may have a consistently higher
metabolic rate, in the absence of order-specific alterations
in glia function. As discussed previously (Section III. 6), the
cetacean brain has a higher glia:neuron index than that
of other mammals. A high percentage of glia, and a con-
sistent metabolic influence of noradrenalin, would suggest
that the brain of the cetacean is likely to be a proficient
VI. EVOLUTION OF THE CETACEAN BRAIN
The evolutionary history of cetaceans recently has been
advanced by the discovery of several key fossils and through
molecular techniques. A comprehensive discussion of
cetacean evolution can be found in Thewissen (1998).
The only terrestrial cetaceans to be identified were
members of the pakicetids, an early Eocene group, which
together with the alleged amphibious cetacean Ambulocetus
and the artiodactyls form the Cetartiodactyla (Thewissen
et al., 2001). Although no calculations of brain and body size
have been published or endocasts found, the photographs
and diagrams of the fossilized skulls indicate that the brain of
these species was relatively small (see Fig. 3 of Thewissen
For example, the terrestrial pakicetid, Pakicetus attocki, a wolf-
sized animal, appears to have maximal brain dimensions of
4 cmr3.5 cmr2 cm (anteroposterior
height) (Thewissen et al., 2001). It would have a brain mass
under 20 g, far less than most modern wolf-sized animals
that have a brain mass over 100 g. For the amphibious
Eocene cetacean, Ambulocetus natans, estimated body mass
ranges between 140–250 kg (Thewissen et al., 1996) and
around 720 kg (Gingerich, 1998). Maximal brain dimen-
sions for this species, as judged from the published figures
(Thewissen et al., 1996), are 10 cmr6 cmr6 cm (antero-
posterior lengthrwidthrheight). Brain mass for Ambulocetus
natans would therefore be less than 200 g, small for a mam-
mal with a body mass of around 200 kg and significantly less
than the comparable-sized polar bear, which has a brain
mass of around 500 g.
The first fully aquatic group of cetaceans is the
Archaeoceti. These cetaceans evolved and speciated in the
warm Tethys sea, for a period of around 20 million years,
from the beginning of the middle Eocene (53 million years
ago) to the early Oligocene (32 million years ago) (Fordyce &
Barnes, 1994). Several fossil endocasts of archaeocetes
have been found. The earliest and best description of these
endocasts is provided by Dart (1923), some of whose figures
are redrawn in Fig. 11. The cerebellum occupies the largest
part while the brainstem and midbrain are of a size appro-
priate to the body size of these species; however, the most
striking feature is the extremely small size of the cerebral
hemispheres: a generous estimate of the cortical surface
area from the specimens described by Dart (1923) is 20 cm2.
This is far less than that of modern cetaceans, which
have cortical surface areas ranging between approximately
1500 and 14000 cm2(Table 2). The cortical volume for
Paul R. Manger
the Archaeoceti would be around 3–5 cm3compared to
250–2400 cm3for modern cetaceans, and the corticalisation
index would be 0.3–2%, compared to approximately 40%
for modern odontocetes or 20% for the single mysticete
for which data are available (Table 2). The rich fossil record
of the Archaeoceti, and the relatively high number of
species – 25 known genera, six families (Gingerich, 1998),
clearly indicates that this group managed to thrive and di-
versify in their environment. Thus, one can only conclude
that a big brain was not necessary for successful adaptation
of early cetaceans to an aquatic environment.
The morphology and relative size of the archaeocete
brain does not appear to have changed significantly during
the 20 million years that these fully aquatic species existed
(Fig. 12) (see also Gingerich, 1998; Marino, McShea &
Uhen, 2004). Allometric analysis of brain mass and body
mass of the Archaeoceti reveal a regression line with a slope
of 0.672. This slope is significantly steeper than that
calculated herein for modern cetaceans (0.376, see equation
5, a comparison of the slopes of the regression equations
derived for archaeocetes and modern cetaceans revealed
a significant difference, P=0.014 using the mean squares
between and within slopes), and was not significantly dif-
ferent from other contemporary mammals (e.g. a compari-
son of the slopes of the regression equations derived for
archaeocetes and Neogene ungulates revealed no significant
difference, P=1 using the mean squares between and within
The sudden extinction of the Archaeoceti and the sub-
sequent evolution of the modern cetacean fauna occurred at
the junction of the early and late Oligocene, approximately
30 million years ago. Marino et al. (2004) estimated brain
and body masses of seven Oligocene cetaceans, all presum-
ably odontocetes (see Table 1). The relative brain size, or
encephalisation quotient of Oligocene cetaceans is higher
than the archaeocete values, and falls within the range
seen for modern cetaceans (see Fig. 13). The scaling of
the relationship between brain and body mass is also
altered compared to archaeocetes. The slope of the al-
lometric equation derived for the Oligocene cetaceans
(Fig. 12) is 0.47, and is identical to that seen for extant
odontocetes, suggesting that the selection pressures de-
termining the scaling of extant cetaceans were present in
Photographs and descriptions of three endocasts of
Miocene cetaceans have been published, Aulophyseter morricei
(18 million years old), Argyrocetus sp., and Schizodelphis sp.
(agesnot provided) (Edinger,
Gingerich, 1998). The morphology of the brain, as de-
termined from these endocasts resembles closely that of
extant cetaceans (see Figs 15.3 and 15.4 in Jerison, 1973) in
the expansion of the cerebral hemispheres. Thus, from
being a minor feature in Archaeoceti, the endocasts of
the Miocene odontocetes are dominated by the cerebral
The calculated brain and body masses of 38 Miocene
odontocetes [see Table 1, data from Gingerich (1998) and
Marino et al. (2004)] are similar to those of extant odonto-
cetes (Fig. 12). Moreover, the scaling relationship between
brain and body mass in the Miocene cetaceans (slope 0.52) is
statistically similar to that found for extant odontocetes
(slope 0.47, a comparison of these slopes revealed no sig-
nificant difference, P=1 using the mean squares between
and within slopes).
To put these alterations in the scaling of the brain-body
mass relationship and EQs during cetacean evolution into
perspective the cetaceans can be compared with their closest
mammalian relatives the ungulates (Thewissen et al., 2001).
The brain-body scaling of ungulates during evolution
(Fig. 12) shows features in common with the majority of
mammalian lineages. First, over time, the mean relative size
of the brain increases gradually. Second, the slopes of the
allometric equations are close to parallel (a comparison of
the slopes of the regression equations derived for the various
groups revealed no significant differences using the mean
squares between and within slopes: Archaic ungulates and
Paleocene ungulates, P=1; Paleocene ungulates and
Fig. 11. Diagrams of fossil endocasts of three species of
Archaeoceti redrawn from the diagrams presented in Dart
(1923). Note the large cerebellum and very small cerebral cor-
tex. The diameter of the cerebral cortex is approximately 4 cm;
it occupied less than 2% of the total brain mass.
Cetacean brain evolution and thermogenesis
Fig. 12. Changes of brain mass and body mass during the evolutionary history of the cetaceans and the ungulates. Data for these
plots are derived from sources listed in Table 1 for cetaceans, and Jerison (1973) for ungulates. Note the increase in brain size relative
Paul R. Manger
Neogene ungulates, P=1; Neogene ungulates and extant
ungulates, P=1). Third, the correlation coefficients for these
equations indicate that the majority of the variation in brain
mass (between 87 and 96%) can be accounted for by vari-
ations in body mass. The ungulate EQ values also show a
gradual increase in the relative size of the brain over time
The pattern of cetacean brain evolution is dramatically
Archaeoceti with the contemporaneous Neogene ungulates
shows a similar allometric relationship (see above). At
the archaeocete – Oligocene cetacean transition there
appears to be a punctuation in cetacean brain evolution,
which from the fossil endocasts of the Miocene cetaceans
appears to be due to the expansion of the cerebral hemi-
spheres. This change in slope and upward shift of the re-
gression line is unlike anything seen in the evolution of
the ungulate brain. Following this is a lack of change in the
evolution of the cetacean brain both in scaling and relative
size. The punctuation in the evolution of the cetacean brain
is also demonstrated by the EQ values (Fig. 13) (archeocete
EQs average 0.53 and range from 0.31–0.97, while
Oligocene cetacean EQs average 2.55 and range from
1.34–3.85, approximately a fivefold increase in average
EQ); the EQs of archaeocetes fall within the range seen
for Neogene ungulates, whereas those of the Oligocene
and Miocene odontocetes fall in the range of the modern
VII. THE INTELLECTUAL CAPACITIES OF
In the following sections, a synthesis of the available ob-
servations is used to formulate a neuroanatomical test of
cetacean intellectual abilities.
(1) Actual and relative brain size of cetaceans
Cetaceans have large brains. It is this observation that has
led many scientists to regard them as having high intellec-
tual abilities. Why is it that large brain size is considered the
equivalent of intellectual capacities? Jerison (1973) influen-
tially related the residual brain size once body mass was
corrected for (the encephalisation quotient) to intellectual
ability. This led him to propose (Jerison, 1978) that some
cetaceans, especially the Delphinidae (see Table 1), possess
high intellectual capacities. However, the larger cetaceans,
such as sperm whales and the baleen whales, have very low
EQs, in fact cetaceans have some of the highest and lowest
Fig. 13. Encephalisation quotients based on the general extant mammalian regression (see Fig. 2) for extinct and extant ungulate
and cetacean species. Note the gradual increase in relative brain size of the ungulates with time. The cetaceans show a dramatic
change in relative brain size at the Archaeoceti – modern cetacean faunal transition. This type of logarithmic alteration of brain size
is not a common event in mammalian brain evolution; rather, the pattern exhibited by ungulates is more commonly seen.
to body size over time in the ungulates. There is a major punctuation in this relationship in cetaceans at the transition from
Archaeoceti to Oligocene odontocetes. This punctuation is accompanied by a change in the scaling of the brain (slope of regression)
relative to body size.
Cetacean brain evolution and thermogenesis
EQs of mammals, plus the entire range between (see Figs 2,
The above examination of the allometry of the cetacean
brain raises a series of interesting observations regarding
the evolution of a large brain. The volumetrically large
brains of the cetaceans evolved more than 20 million years
after their ancestors led a fully aquatic lifestyle. The evol-
ution of large brain size in cetaceans seems to have occurred
as an evolutionary punctuation, and not as a gradual
Darwinian-type increase (as is the case for ungulates and
many other mammals). This can be interpreted as indicating
a specific evolutionary pressure acting at a particular
time. Second, the brain-body scaling of the extant cetaceans
differs from that of other extant mammalian species (see
Section II.1). For a given increase in body size, the relative
increase in brain size in cetaceans is less than it is for other
mammals and much less than in hominids: both hominids
and cetaceans appear to represent exceptions to the general
pattern of brain-body allometric scaling for mammals.
Nevertheless, it is not parsimonious to claim that increases
in relative brain size in hominids and some selected cet-
aceans (Marino, 1998), were both driven by the need for
greater information-processing capacity. Moreover, an ex-
amination of the intraspecific scaling of cetaceans indicates
that the selection pressure causing the intraordinal scaling
pattern of cetaceans continues to act upon extant cetaceans.
Previous studies of cetacean allometry have interesting
parallels with those of the craniometrists of the 1800s
measurements of brain mass and skull size and shape into
a preconceived notion of the rank of different races of
humans, in an attempt to prove some imagined superiority
of the Caucasian male. In doing this, the craniometrists
ignored available data, statistically manipulated and mis-
represented results, and provided imaginative and often
untestable explanations for data that did not fit their pre-
conceived notions. In the study of cetacean allometry par-
allels can be found in the absence of certain species from
analyses, statistical manipulation without sound evolution-
ary logic (e.g. the grouping of Delphinidae and primates
to allow the recalculation of the EQ), and imaginative ex-
planations to account for the observed differences (e.g.
‘aquatic weightlessness’, and non-innervated blubber) (see
Given its importance in thermoregulation the thickness of
cetacean blubber is surprisingly low with dolphins only
having a blubber layer 2.5 cm thick (Hokkanen, 1990),
whereas in adult pinnipeds this blubber layer is commonly
7–10 cm thick (Iverson, 2002). Moreover, the manner in
which blubber scales in cetaceans (Ryg et al., 1993), means
that subtraction of blubber mass from total body mass, while
increasing the EQ, will reduce futher the slope of the brain-
body mass scaling relationship.
(2) Vocalisations of cetaceans: language or
simple species-specific calls?
The vocalisations of cetaceans have been the subject of
speculation ever since Lilly (1962) entertained the possibility
of a dolphin language, or ‘dolphinese’. Despite extensive
efforts to either impose a language upon cetaceans, or de-
cipher their vocalisations, it is clear that no such language
exists (Herman & Tavolga, 1980; Herman, 2002).
Mammals have a common vocalisation pathway (Ju ¨rgens,
1998). The only known exception to this is the language
areas of the human cerebral neocortex (see Price, 2000, for
review). There are no reports of a region of the cetacean
neocortex that might be analogous to the language areas of
the human neocortex. In fact, given the relatively small size
and simple areal organisation of the cetacean cerebral cor-
tex, it is likely that no neocortically initiated vocalisations
can be produced by cetaceans. In comparison to other
mammals, the anterior cingulate cortex of cetaceans is also
small and undifferentiated. This limbic region is involved
in the voluntary initiation of vocalisations in mammals
(Ju ¨rgens, 1998); thus, any cortical origin for vocalisations in
cetaceans must be greatly compromised or does not exist.
The region of the vocalisation system localised in the
periaqueductal grey matter does appear to be specialised in
cetaceans. Within the periaqueductal grey matter of cet-
aceans lies a large and distinct nucleus, the nucleus ellipticus.
If this nucleus is indeed involved in vocalisations, as seems
likely (see Section V.1), then the probable centre for con-
trolling vocalisations in cetaceans lies in the brainstem.
In humans, the main centres for the control of language lie
in the neocortex (Price, 2000). Thus, the study of cetacean
neuroanatomy suggests that dolphin ‘language’ is a
uniquely evolved brainstem specialisation, dramatically dif-
ferent from the neocortically based language of humans.
A more parsimonious explanation is that cetaceans do
not possess the capacity for language. Rather, they have
approximately seven different species-specific vocalisations
(Herman & Tavolga, 1980), which are controlled mainly at
the brainstem level. Several species of mammals possess
an equal or greater range of vocalisations and are not con-
sidered linguistically sophisticated. For example, the grey-
headed flying fox (Pteropus poliocephalus) has over 30 different
calls (Hall & Richards, 2000), yet has not been suggested to
possess linguistic capacities.
It is a general belief that cetacean vocalisations have a
semantic meaning. However, this assumption can be chal-
lenged by using a more strict and non-anthropomorphic
approach, by asking what the animal accomplishes by vo-
calising, instead of asking what it is trying to say (Morton,
1977; Morton & Page, 1992; Owings, 1992). The most
common vocalisation of bottlenose dolphins is the signature
whistle, presumed to be a ‘cohesion call’ (Janik & Slater,
1998) i.e. it is used for group coherence to keep the pod
within acoustic range of each other. The main predators of
dolphins are large sharks, and by schooling an individual is
less likely to be predated (Acevedo-Gutie ´rrez, 2002). The
vocalisation in itself is not required to have a semantic or
symbolic meaning; dolphins just have to learn, by associ-
ation, that increasing pod coherence in response to a specific
vocalisation decreases their chance of being predated.
Vocalisations have also been used to argue that cetaceans
possess ‘culture’, by the transference of information
from one individual to another and subsequently to
the entire population (Rendell & Whitehead, 2001). The
most commonly cited example of ‘cultural’ transference of
Paul R. Manger
vocalisations across individuals are the ‘songs’ of the
humpback whale (Payne, 1999). It has been shown that the
majority of breeding humpback whales ‘sing’ nearly the
same ‘song’, but that this ‘song’ changes over the course of
a breeding season and between breeding seasons. It has
been postulated that these changes reflect cultural trans-
mission and learning across the male humpback population
(Rendell & Whitehead, 2001). However, it has been shown,
using a simple mathematical model, that birds copying each
other’s songs but with a low and constant random error rate,
can explain regional variations in bird song (Williams &
Slater, 1991). It is likely that a constant random error rate in
song copying in whales leads to the observed alteration in
songs, rather than a meta-cognitive cultural phenomenon
(Rendell & Whitehead, 2001).
(3) The cerebral cortex and hippocampal
Any serious proposal concerning the intellectual capacities
of mammalian species must be supported by neuroanatom-
ical complexity of the cerebral cortex, the region thought
to be involved in complex cognitive behaviours. In the
present survey, 15 differences in the structure of the cet-
acean cerebral cortex in comparison to other mammals
were found: (1) cortical lamination is not distinct; (2) there is
pyramidalisation of layer 2 neurons; (3) layer 4 recedes
during development; (4) the cortex is thin relative to total
brain size; (5) neuronal density is low; (6) there is imperfect
vertical columnar and microcolumnar organisation; (7)
there is low diversity and complexity of neuronal mor-
phologies; (8) the glia:neuron ratio is very high; (9) there is a
very small number of cortical areas; (10) there is no apparent
prefrontal cortex; (11) the temporal cortex is relatively
small; (12) the limbic lobe, especially the anterior cingulate
cortex is relatively small; (13) the relative amount of total
cerebral cortex is low; (14) the cerebral cortical volume ex-
pands proportionally, not allometrically, with increased
brain size across cetacean species; and (15) there are altered
proportions of the constituents of the neuropil.
These features are intimately linked with the processing
capacity of the cerebral cortex. One way in which the
mammalian cerebral cortex processes information is by
vertical, or interlaminar, connectivity (Jones, 2000). This
basic vertical processing unit is seriously compromised in the
heterotypical cetacean cerebral cortex. Intercolumnar pro-
cessing is also compromised due the paucity of parvalbumin-
immunoreactive neurons (Hof et al., 2000). Blurring of
the cortical lamination, lack of layer 4, a thin cortex, low
neuronal density, and pyramidal cells in layer 2, will all
compromise the processing capacity of the mammalian
cortical network. No clear alternatives to compensate
for these alterations in structure have been identified in
Kaas (1995), states that: ‘All mammals appear to have
roughly 20 cortical areas, …, in common as retentions from
an early ancestor …’. It would appear that cetaceans possess
only those areas in common to all mammals, though many
of these may be greatly reduced in relative terms (see Fig. 6).
Moreover, the general trend for increasing numbers of
cortical areas with increasing cortical size (Kaas, 1995) is
not apparent for cetaceans. An increase in the number of
cortical areas would increase the sophistication of infor-
mation processing and reduce the problem of interconnect-
ing circuits (Kaas, 1995), probably resulting in a greater
behavioural range and increased cognitive capacities.
In the present analysis, prefrontal cortex is designated
as the region of cortex rostral to the distribution of the
gigantopyramidal cells that project to the pontine nucleus
(found within motor and pre-motor cortex – the origin of
the cortico-pontine tract). The definition and homologies of
prefrontal cortex across mammalian species is a contentious
issue (Divac et al., 1987; Divac & O¨berg, 1990; Preuss,
1995). In cetaceans it is difficult to identify any region of
cortex rostral to premotor areas, although agranular pre-
frontal cortex is readily identified in a range of mammalian
species, including primates (Brodmann, 1909; Divac et al.,
1987; Preuss, 1995). Agranular prefrontal cortex plays a
major role in complex cognitive functions.
For mammals in general, an increase in brain size means
that a greater proportion of the brain is made up of cerebral
cortex (Finlay & Darlington, 1995). This trend is not found
in the cetaceans, where the percentage of the brain that is
cerebral cortex remains unchanged with changes in brain
The altered proportions of the contents of the neuropil
discussed in Section III.6 will have a direct impact on the
processing power of the cetacean cerebral cortex. The ob-
served higher proportion of glial processes, myelin sheaths,
and axons of passage (thalamocortical axons), plus lower
spine numbers and less branched dendrites will all impact
negatively on its processing power. For example, a lack
of dendritic branching will cause lowering of processing/
parcellation of inputs in the dendritic tree.
This analysisof the cetacean cerebralcortex makes itclear
that cetacean cerebral cortex is unique to these animals,
rather than representing a primitive mammalian brain
(Glezer et al., 1988). In all aspects investigated to date, the
cetacean cerebral cortex can be argued to be deficient in
terms of processing capacity, with no unique structures yet
identified that could compensate for this.
The hippocampal formation of cetaceans is small in
relative and actual terms. The function of this structure in
forming enduring memories and the interaction of memory
with cognitive functions, again casts doubt on reports of
complex cognitive abilities in cetaceans.
One major theory of comparative intelligence is based on
the assumption that intelligence is a product of various
cognitive modules, and that each species has its own set of
cognitive modules, the sum of which describes the intelli-
gence of that species. This is known as the ecological theory
& Macphail, 2001). The main experimental focus of the
ecological theory of intelligence has been to compare the
differences in hippocampal formation size in food-storing
birds (which have a comparatively better spatial memory)
with related non-food-storing birds. The relatively small size
of the cetacean hippocampal formation could suggest that
the cognitive module associated with spatial memory is
greatly compromised in cetaceans. It appears appropriate
Cetacean brain evolution and thermogenesis
therefore to suggest that functions related to hippocampal
processing must be compromised in cetaceans.
(4) Does acoustic specialisation account for
the increase in cetacean brain size?
It has been proposed that the increase in cetacean brain
size isrelatedto their
(Langworthy, 1931, 1932). Ridgway & Au (1999) state
that: ‘… the great hypertrophy of the dolphin auditory
system – and perhaps the entire cerebrum – may result
from the animal’s need for great precision and speed in
processing sound.’ This reasoning has particularly been
used for the Delphinidae, which have the highest en-
cephalisation quotients of cetaceans (Table 1). It is hy-
pothesised that specialisations of the delphinoid acoustic
system for echolocation may have been the driving force
behind the relative increase in brain size of this group above
The peripheral auditory structures of cetaceans are highly
modified (for review see Ridgway & Au, 1999). The dolphin
cochlea is rich in outer hair cells, and possesses many
ganglion cells. The vestibulocochlear nerve (8th cranial) is
large in all cetaceans (Pilleri & Gihr, 1970) consisting of a
large number of fibres, e.g. 153500 in the fin whale, 179000
in the humpback whale, and 214500 in the sperm whale,
compared with 50000 in man (Jacobs & Jensen, 1964).
All central neural structures associated with auditory
processing, such as the inferior colliculus, cochlear nucleus,
superior olive, and the medial geniculate body, are relatively
enlarged and heavily myelinated (Hosokawa et al., 1969;
Glezer et al., 1998). As described above, the proportion of
the cortical sheet devoted to auditory processing is also
substantial. It is clear that much of the brain of the cetacean
is used for processing acoustic information. However, does
this mean that the enlargement of the entire brain was
driven by acoustic specialisation or that this increase in
brain size was accompanied by an increase in the general
level of intelligence?
Many mammalian species possess specialised sensory
systems and certain regularities in the modifications of per-
ipheral and neural structures are evident. The specialised
sensory systems of the bill of the platypus (Ornithorhynchus
anatinus) and the visual system of primates, including man,
can be compared to the cetacean auditory system to high-
light these regularities, and also to show where the cetaceans
differ compared to other mammals. The bill of the platypus
is a highly derived sensory structure containing specialised
tactile and electrical receptors (Pettigrew, Manger & Fine,
1998). There are approximately 46500 push-rod mechano-
receptor complexes and 43500 electroreceptors (of two
types), innervated by a total of 672000 axons per trigeminal
nerve (Manger & Pettigrew, 1996). The primate eye is an
elaborate structure with a significant diversity in cell types
within the retina (Robinson, 1991); the human optic nerve
contains around 1200000 axons (Jacobs & Jensen, 1964).
The trigeminal ganglion and the ventral posterior medial
nucleus of the platypus thalamus are both greatly enlarged
(Hines, 1929), as are the lateral geniculate and pulvinar
nuclei of primates (Jones, 1985). Approximately two-thirds
of the platypus neocortex is involved with the representation
and processing of sensory information obtained via the bill
(Krubitzer et al., 1995). A major portion of the neocortex of
primates is also devoted to processing visual sensory infor-
mation (van Essen et al., 2001). The primary somatosensory
cortex of the platypus is highly derived, and exhibits a
mechano/mechano-electro dominance column configur-
ation (Krubitzer et al., 1995; Manger, Calford & Pettigrew,
1996). Similarly, the primary visual cortex of primates is
highly derived and exhibits many forms of modules includ-
ing ocular dominance columns, orientation columns, and
blob and interblob zones (Mountcastle, 1997).
Similarities arising from this comparison include: (1) per-
ipheral specialisation with extensive innervation; (2) en-
largement and specialisation of all subcortical structures
involved with the specialised sense; and (3) occupation of a
large portion of the cerebral cortex by the specialised sense.
These features are seen in all mammals that possess special-
ised sensory systems including dolphins.
The first difference of note is that within the auditory
cortex of the dolphin, no specialised, anatomically identifi-
able, cortical modules have been found, despite the range of
stains used to examine this region (Glezer et al., 1998; and
references therein). Such anatomically identifiable modules
are found in the primary sensory cortices of other mammals
with specialised sensory systems, e.g. platypus (Manger et al.,
1996), insectivores (Catania, 2000), marsupials (Elston &
Manger, 1999; Huffman et al., 1999), rodents (Woolsey,
Welker & Schwartz, 1975), and primates (Mountcastle,
1997) among many others. Second, mammals with special-
ised sensory systems do not have the encephalisation
quotient (EQ) grossly altered due to brain-body mass scaling
differences that is seen in cetaceans. The platypus has an EQ
of around 1.07, only slightly above the ‘average’ mammal
[EQ of the average mammal=1, 95% confidence intervals
0.51–1.99, the platypus EQ of 1.07 falls well within (66%)
the Gaussian frequency distribution of mammalian EQs].
Other mammals, such as carnivores or primates, with
specialised visual systems similarly lie within the normal
range for mammals or primates (see Fig. 4). Third, the vol-
ume of the cerebral cortex of mammals with specialised
sensory systems does not scale unusually compared with
other mammals, i.e. they have the same amount of cerebral
cortex as a mammal of the same brain size that lacks the
sensory specialisations (Finlay, Darlington & Nicastro,
2001). As shown earlier, cetaceans actually have less cer-
ebral cortex than mammals of similar brain size, so the
concept that sensory specialisation has driven a ‘hyper-
trophy’ of the cerebrum (Ridgway & Au, 1999) does not fit
the anatomical data. Moreover, the number of fibres in the
vestibulocochlear nerve is less than half that of the trigem-
inal nerve in all cetaceans studied (Jacobs & Jensen, 1964),
raising a question as to the degree of specialisation of the
cetacean acoustic system.
abilities to the cetaceans (Covey & Casseday, 1999). As with
the cetaceans, the auditory system of the Microchiroptera
exhibits peripheral and central specialisations (e.g. Covey &
Casseday, 1999; Fitzpatrick, Olsen & Suga, 1998; Sakai &
Suga, 2001; and references therein). Within the auditory
Paul R. Manger
cortex of the Microchiroptera, around seven auditory areas
have been defined (Fitzpatrick et al., 1998). This is probably
matched by the cetaceans, even though on cytoarchitectonic
grounds only four areas have been identified (Kesarev et al.,
1977). Despite the potential similarities in the organisation
of the acoustic system in these two groups of mammals,
microchiropteran bats do not have disproportionately large
allometric patterns and there has been no increase in rela-
tive brain size to accommodate their specialised acoustic
system (Baron, Stephan & Frahm, 1996).
Echolocation in microchiropterans provides a maximum
of 3 m detection range (best range is 1 m), whereas delphi-
noids have a range of around 100 m (Ridgway, 1990), thus
it is possible that echolocation distance is responsible for
the relative brain size differences between cetaceans and
microchiropterans. However, given that dolphins are some
1000 times larger than Microchiropteran bats, the differ-
ence in range could also be accounted for simply by the
Microchiropteran, there are numerous surfaces that will
reflect sound (Covey & Casseday, 1999), whereas in the
open-ocean environment of most cetaceans this is not the
case. In both Microchiroptera and the barn owl (Tyto alba),
specific neuronal groups within the auditory space map of
the inferior colliculus have been identified that compensate
for echoes (Covey & Casseday, 1999; Keller & Takahashi,
1996). Thus, it is unlikely that physical acoustic properties
are acting as a selection pressure resulting in large brain size
It has been argued that cetaceans must echolocate a
sphere of 100 m diameter, whereas in a microchiropteran
this sphere is only 3 m diameter, and that this requires an
enlarged cerebral cortex (Ridgway, 1990). However, it has
been shown that a precise map of auditory space exists
within the inferior colliculus of all mammals studied (Park &
Pollack, 1994; Grothe, Covey & Casseday, 1996; Wu & Jen,
1996; Zhou & Jen, 2000). This collicular auditory space
map has also been intensively studied in the barn owl
(Cohen & Knudsen, 1999) in which the space map is based
on the tuning features of the individual neurons to such
stimuli as interaural time differences and interaural level
differences (Moiseff & Konishi, 1981; Mogdans & Knudsen,
1994; Pen ˜a & Konishi, 2001). A complete and accurate
map of auditory space is created in the midbrain portion of
the auditory system.
The formation of the auditory space map in the owl is
assisted by an asymmetric morphology of the head, with one
ear being lower than the other. Cranial asymmetries are
found in the skull of echolocating odontocetes, but not in the
non-echolocating mysticetes (Ness, 1967; Ridgway, 1990),
which may assist in the creation of the collicular auditory
space map. Moreover, the echolocation pulses of cetaceans
are often described as being emitted ‘directed forward in a
narrow pattern’ (Ridgway & Au, 1999) making it probable
that rather than scanning a 100 m diameter sphere with
sound they are instead focussed on a narrow portion of this
These observations question the need for an exceptionally
enlarged cerebral cortex in delphinoids to localise acoustic
follow normal mammalian
the environmentof the
stimuli accurately. In fact, the inferior colliculus of the dol-
phin appears to have a modular organisation of GABAergic
neurons (Glezer et al., 1998) that could subserve an accurate
map of acoustic space as seen in the Microchiroptera (Park
& Pollack, 1994; Zhou & Jen, 2000). Taken together the
above discussion shows that echolocation does not provide a
satisfactory explanation for the altered brain-body mass
scaling of cetaceans.
(5) Can apparent convergences in cognitive
behaviour explain the increase in
cetacean brain size?
A recent article by Marino (2002) lists three apparently
complex cognitive abilities that are implied to infer high
levels of intelligence in cetaceans and are suggested to
underlie their increased brain size: social group behaviour,
language comprehension, and self-recognition ability. In
Section VII.2 it was shown that there is little evidence for a
language and the vocalisations of cetaceans are more parsi-
moniously explained by an anatomical specialisation within
the rostral brainstem, the nucleus ellipticus.
It has been reported that there is a significantly positive
correlation between EQ and pod or group size in cetaceans
and primates (Marino, 1996, 2002). For cetaceans, Marino
(1996) provides a plot of data from a limited number of
species (of which only two are solitary), no equation is given
for the regression line, or any correlation statistics, making it
impossible to judge the validity of the relationship. Fuller
examination of the available data supports only a weak
positive relationship for primates and cetaceans (Fig. 14).
For all cetaceans there is no significant relationship between
EQ and pod size (r2=0.063, P=0.138), although with the
removal of the solitary living cetaceans, the regression just
reaches significance (r2=0.167, P=0.026). Note that the
three solitary-living species used in this analysis, Platanista
gangetica, P. minor and Pontoporia blainvillei, have EQs ranging
from 1.83 to 2.38 (Table 1), which are in the middle of the
observed range of cetacean EQs. The allometry for primates
(r2=0.205, slope=1.43) indicates a slightly better predict-
ability of group size from EQ, with a steeper slope, and a
significant correlation (P=7.1r10x5). This analysis sug-
gests that while there are weak relationships between EQ
and social group size in both primates and cetaceans it is
likely that other factors such as levels of predation, food
abundance, and other life-history variables also determine
cetacean pod size.
Cooperative feeding strategies have also been used as
evidence for intelligence in cetaceans. Marino (2002) cites
three examples: water-surface trapping of fish by dusky
dolphins [genus Lagenorhynchus, EQs ranging from 4.43 to
6.32 (Table 1); the EQ of Lagenorhynchus obscurus is un-
known], ‘strand feeding’ by bottlenose dolphins (Tursiops
truncatus, EQ=4.47), and bubble-net feeding by humpback
whales (Megaptera novaeangliae, EQ=0.35). It is clear from this
comparison that cooperative feeding strategies in cetaceans
are not related to encephalisation levels. Other social
behaviours listed by Marino (2002), such as alloparental
care, cultural transmission, fission-fusion societies, interpod
‘warfare’, and intrapod alliances, all rely on behavioural
Cetacean brain evolution and thermogenesis
observations and have not been sufficiently documented to
allow independent scrutiny. Many of these apparently pri-
mate-cetacean convergent social behaviours are found in
other species of mammals and do not support her artificial
grouping. A serious cladistic analysis of these behaviours is
required to test the conclusions of Marino (2002). Many of
these behaviours occur in a range of cetacean species, with a
range of EQ levels, thus, it may not be parsimonious to
relate them to increased relative brain size. For example
alloparental care, or ‘babysitting’, is said to occur in bottle-
nose dolphins (Tursiops truncatus, EQ=4.47), sperm whales
(Physeter catadon, EQ=0.44), killer whales (Orcinus orca,
EQ=2.62), and harbour porpoises (Phocoena phocoena,
Mirror self-recognition has been used as evidence for
sophisticated cognitive abilites, and has been consistently
found in chimpanzees, however, findings in other species are
limited and controversial. Reiss & Marino (2001), claim to
have presented the only convincing evidence for mirror self-
recognition in dolphins (Tursiops truncatus), despite other
with similar claims (e.g. Delfour & Marten, 2001). Again,
the range of EQ levels for these species indicates that EQ
and mirror self-recognition ability are unlikely to be related;
this also applies to primates: the chimpanzee (Pan troglodytes)
has an EQ of 2.76 which is far lower than that of the capu-
chin monkey (Cebus capucinus, EQ=4.55) which does not
have mirror self-recognition abilities. Moreover, the meth-
odology (Delfour & Marten, 2001), interpretation (Mitchell,
1995), and controls (Anderson, 1995) in studies of mirror
self-recognition in cetaceans have been questioned. The
conclusions of Reiss & Marino (2001) are greatly weakened
by not addressing these issues and their reliance on measures
of latency to infer cognitive activity. Moreover, their data
show that unmarked dolphins spent almost as much time in
front a mirror as marked individuals, and that the target
behaviour was increased dramatically even in the absence of
a mirror (see Fig. 3b of Reiss & Marino, 2001).
In summary, the features listed by Marino (2002) that led
her to conclude that ‘Cetacean brains and primate brains
represent alternative ways brains can increase in size and
complexity and arrive at similar cognitive or even compu-
tational abilities’ are questionable.
VIII. WATER TEMPERATURE AND
THE LARGE CETACEAN BRAIN
If the large brain of modern cetaceans did not evolve to
increase its information-processing capacity (i.e. intelligence)
then why do they have such large brains? A serious de-
ficiency in modern evolutionary thinking in regards to brain
evolution is that the evolution of large brain size is assumed
solely to effect an increase in intelligence. So can an evol-
utionary increase in brain size be related to a specific selec-
tion pressure without the need for increased intellectual
capacity? In this section neuroanatomical features of cet-
aceans, the evolution of modern cetacean brain size, in-
traordinal and intraspecific brain-body mass scaling,
encephalisation quotients, the glia:neuron index, and uni-
hemispheric sleep phenomenology are related to past and
present oceanic temperatures, in which cetaceans evolved
and now live. It is suggested that oceanic temperature
was the selection pressure that drove the evolution of, and
continues to influence, the brain size of modern cetacean
(1) Water temperature during the archaeocete/
Oligocene cetacean transition
In Section VI it was argued that a punctuated change oc-
curred during evolution in the relative size of the cetacean
brain. This occurred at the demise of the Archaeoceti and
the rise of the modern cetacean fauna, as represented by the
Oligocene cetaceans (Gingerich, 1998; Marino et al., 2004).
The Archaeoceti lived, for the most part, in the equatorial
Tethys sea which is described as a shallow, nutrient-rich,
warm sea with low water temperature gradients (Fordyce &
Barnes, 1994). The Archaeoceti diversified, both at the
species and family level, in this environment, for around 20
million years. During this period, they had a brain with a
tiny cerebral cortex (Dart, 1923). During the last 1–2 million
years of the archaeocete radiation, significant cooling of the
oceanic waters occurred, and this is associated with a decline
in archaeocete diversity (Fordyce & Barnes, 1994). At the
extinction of the Archaeoceti and the evolution of the
modern cetacean fauna there was a major cooling of oceanic
temperatures (Whitmore, 1994), with increased latitudinal
Average pod/group size
Ps = 6.6 × EQ0.35
(r2 = 0.063, P = 0.138)
Gs = 2.8 × EQ1.43
(r2 = 0.205, P = 7.1×10−5)
Fig. 14. Plots of average pod (Ps) or group (Gs) size against
encephalisation quotient (EQ) of cetaceans and primates. EQ
was calculated using equation (1) in Section II.1. In cetaceans,
there is a trend towards increasing group size with increasing
brain size but this relationship is not significant (r2=0.063,
P=0.138). For primates the relationship does reach significance
(r2=0.205, P=7.1r10x5). These results indicate that there is
no relationship between encephalisation level and pod size as
previously reported (Marino, 2002); and those for primates,
while reaching statistical significance, do not have a high level
of predictability (Reader & Laland, 2002). Average pod/group
sizes used in this plot were taken from Nowak (1999).
Paul R. Manger
thermal gradients, and the closure of the Tethys sea by the
suturing of India and Africa to the Eurasian landmass
(Fordyce & Barnes, 1994).
(2) Neuroanatomical features of the cetacean
brain related to thermogenesis
It has been shown in a variety of mammals, especially ungu-
lates, that the temperature of the brain is regulated separ-
ately to the temperature of the body (reviewed in Gisolfi &
Mora, 2000). During increased thermal pressure, body
temperature increases dramatically while brain temperature
remains relatively stable. The pioneering studies of
Donhoffer (1980) showed that during exposure to cold, the
body temperature of a mammal decreases but the brain
temperature remains stable due to increased cerebral heat
production (Szele ´nyi, 1998). Szele ´nyi (1998) reviewed the
thermogenetic mechanisms allowing brain temperature to
remain stable, or even increase, during exposure to cold.
Thermogenesis within the central nervous system (CNS)
results from glycogenolysis within the glial cells.
The cetacean cerebral cortex contains an abundance
of glia compared to other mammals (Section III.6). The
cerebral cortex was the part of the brain that changed most
during the period of oceanic cooling that coincided with the
archaeocete/Oligocene cetacean transition. This part of
the brain probably has a major thermogenetic role in the
cetacean CNS due to its higher glia:neuron index. However,
in the absence of further data, it is likely that the whole brain
is probably involved in thermogenesis, and not just the
cerebral cortex. In fact, the increased size of the cetacean
brain could have been achieved by simply doubling the
number of glia present throughout all regions of the brain.
In Section V it was argued that cetacean sleep patterns,
i.e. unihemispheric sleep with a small proportion of REM
sleep will effectively bathe the cetacean brain with higher
levels of noradrenalin than found in other mammals.
Noradrenalin is known to increase glial metabolism by
stimulating the breakdown of glial glycogen (Stone &
Ariano, 1989). It therefore appears that the greater number
of glia in the cetacean brain are also bathed in higher levels
of noradrenalin, which will together lead to increased heat
production. These observations link the anatomy of the
cetacean brain and sleep phenomenology (Manger et al.,
2003; Pillay & Manger, 2004) with a thermally challenging
environment in which heat loss is likely to be a significant
(3) Brain-body mass scaling in modern cetaceans
and its relation to water temperature
Two features characterise the punctuation in cetacean brain
evolution at the archaeocete/Oligocene cetacean transition:
an increase in actual brain size and an altered brain-body
mass scaling. The intraordinal allometric slope of cetacean
brain-body mass scaling is lower than either interspecific or
intraordinal slopes found for other mammalian groups (see
Section II.1) presumably due to a selective force different
from those acting on other mammals. It is also of interest
that the intraspecific scaling of cetacean species is similar to
the intraordinal scaling (see Section II.2), implying that the
factor causing altered brain scaling in cetaceans is still in-
fluencing extant cetaceans.
In Fig. 15 brain mass, body mass and EQ are plotted
against the upper, lower and range of water temperatures
(yearly average water temperatures for 1998 from the
National Oceanograpic Data Center, Fig. 16) in which the
various cetacean species are found [distributional limits for
cetaceans derived from Gaskin (1982), Ridgway & Harrison
(1985, 1989, 1994) and Waller (1996), see Table 1 and
Fig. 16]. Fig. 15 shows there is a trend for larger cetaceans
to inhabit environments with lower average maximum
and minimum temperatures and these relationships are
significant (r2=0.56, P=1.9r10x6for Tmax; r2=0.35,
P=4.0r10x4for Tmin), but the predictability of these
regressions is low. This might be taken as evidence for
the concept of thermal inertia – large bodies lose heat less
rapidly than do small bodies, thus providing greater toler-
ance to lower water temperatures. A similar pattern is found
for brain mass: there is a significant relationship between
brain mass and Tmax(r2=0.39, P=0.0002) or Tmin(r2=
0.30, P=0.0012), but again the predictability of the re-
gressions is low. The EQs in Fig. 15 were calculated
for cetaceans using mammals in general as a reference
group (Table 1) as this is an attempt to uncover factors in-
fluencing the scaling of cetacean brain-body mass compared
to other mammals. Again, there is a trend for an increase in
relative brain size (i.e. an increased EQ) to be associated
with greater maximal and minimal environment tempera-
tures. These relationships do reach signficance: Tmax,
r2=0.54, P=3.4r10x6); Tmin, r2=0.29, P=0.0015), but
the predictability of the regressions was low.
When the range of environmental temperatures was
used on the y axis trends for increasing body size with lower
environmental temperature (r2=0.53, P=4.3r10x6), and
increasing brain size with lower environmental temperature
(r2=0.22, P=0.0057) were seen, but the predictability of
the regressions was low. The relationship between environ-
mental temperature range and EQ for cetaceans was
strongly statistically significant, and the predictability of
the regression was higher (r2=0.7, P=9.9r10x9). Thus
the strongest relationship exists between the environmental
temperature range and EQ with temperature range ac-
counting for around 70% of the variability in EQ.
These analyses suggest that the altered scaling of brain
and body mass of cetaceans may be linked to environmental
water temperature. A similar conclusion can be reached by
qualitatively comparing the distribution of modern cetacean
species with oceanic temperatures (Fig. 16): the distri-
butional limits of cetacean species in many cases match
isothermal lines of oceanic water temperature.
To illustrate the above points we can examine two species
whose distributions cover the same range of temperatures,
but whose body size is dramatically different. Neophocaena
phocaenoides and Tursiops truncatus both inhabit an environ-
mental temperature range of 16 x (12 x–28 xC and
13 x–29 xC, respectively). They have a similar EQ of 4.49
and 4.47, respectively, however, T. truncatus is around five
times larger with a body mass of 165 kg and a brain mass of
1530 g, whereas N. phocaenoides has a body mass of 32.4 kg
Cetacean brain evolution and thermogenesis
Fig. 15. Plots of body mass, brain mass and encephalisation quotient (EQ) against mean high (Tmax) and low (Tmin) temperature
extremes and range (Trange) of water temperatures encountered by cetaceans. Body mass, brain mass and EQ show statistically
significant trends associated with absolute water temperatures, but none of these have a high predictability. The strongest re-
lationship is between EQ and the environmental temperature range (r2=0.7, P=9.9r10x9), with a positive slope indicating an
increasing EQ with increasing range of environmental water temperatures. The data in these plots are derived from Table 1.
Paul R. Manger
Fig. 16. Continued.
Cetacean brain evolution and thermogenesis
Fig. 16. Global water temperatures and the distribution of cetaceans. The upper figure shows average water temperatures at depths
between 0 and 10 m from the surface in 1998. (Derived from the National Oceanographic Data Center web page using the World
Ocean Atlas Interactive Image Access for 1998 [http://www.nodc.noaa.gov/OC5/WOA98F/woof_cd/search.html].) The lower
figures show the distribution of various cetaceans and their relationship to the isothermal lines of water temperature. Note that many
of the edges of the distributions match isothermal lines, often on both sides of a continent. Distributional data were taken from
Gaskin (1982), Ridgway & Harrison (1985, 1989, 1994), and Waller (1996).
Paul R. Manger
and a brain mass of 468 g. Thus, although inhabiting similar
environmental temperatures (both absolute and range),
these two species differ greatly in size. The same level of
encephalisation in these two species may explain this ob-
servation, enabling them to inhabit the same geographical/
oceanic range despite differences in body size.
(4) The size of the cetacean brain
The sheer volume of the cetacean brain has been one of the
main reasons for attaching high intellectual abilities to cet-
aceans. However, the size of the cetacean brain can also be
explained in terms of water temperature.
Downhower & Blumer (1988) calculated that the rate of
heat loss in water is around 90.8 times faster than in air and
demonstrated that the smallest body size for neonate cet-
aceans (y6 kg) is limited by this rate of heat loss. Cetaceans
are eutherian mammals, and as such, to produce a young of
at least 6 kg, the adult cetacean must weigh more than 30 kg
(Fig. 17) this allometric relationship applies to all eutherian
mammals. This adult cetacean must also have a brain-body
mass scaling that allows it to cope with thermal loss to the
environment. Given these two factors, it becomes impossible
for smaller cetaceans to produce offspring without large
brains for their body size, hence having high encephal-
ization quotients. Larger cetaceans will produce larger off-
spring, resulting in actual larger brains. However, due to the
altered scaling of brain and body mass, the encephalisation
quotients of these larger species will be smaller.
(5) Evidence from other aquatic mammals
Cetaceans are not the only mammals that have adopted a
secondarily aquatic mode of life. Both pinnipeds (seals, sea
lions and walrus) and sirenians (manatees and dugongs) have
successfully adapted to semi-aquatic and fully aquatic life-
styles. If the hypothesis proposed here that water tempera-
ture is a significant evolutionary pressure on cetacean brain
evolution is correct, then convergent features may be found
in both these groups. Comparable data to those presented
here for cetaceans are not available for pinnipeds or
sirenians, but some data are available for consideration.
The pinnipeds (Order Carnivora) are generally subdivided
into three families: the Otariidae (eared seals, sea lions),
Odobenidae (walrus) and Phocidae (earless seals). Despite
previous disagreements, these groups are now thought to be
monophyletic (Bininda-Emonds, Gittleman & Purvis, 1999).
Neuroanatomical data are scarce. The external structure
of the brain (Fig. 18) shows a highly convoluted cerebral
cortex, with a somewhat enlarged cerebellum; however,
systematic quantification of the size of regions of the brain
has not been undertaken. A recent examination was made
of trends in adaptation to an aquatic environment of
pinnipeds, compared with terrestrial carnivores (Bininda-
Emonds et al., 2001). Few systematic differences were
observed, however, features such as a streamlined body,
smaller litter sizes, shorter interbirth interval, and shorter
lifespan were reported for aquatic carnivores. Of most in-
terest to the present study is that Bininda-Emonds et al.
(2001) reported that aquatic carnivores had larger brain
sizes than their terrestrial relatives, indicating to those
authors an increased need for cognitive and sensory abilities:
the aquatic carnivores are really semi-aquatic, with an
amphibious lifestyle encompassing both aquatic and terres-
Fig. 17. Allometric plot of the relationship between neonatal (Mbirth) and adult body mass (Mb) in three orders of eutherian
mammals. The data used in this plot are derived from that given in Nowack (1999).
Cetacean brain evolution and thermogenesis
Fig. 18. Photographs of the lateral (A) and dorsal (B) surfaces of the California sea lion (Zalophus californianus) brain. Scale
bar=1 cm. Note the extensive gyrification of the cortex, especially when compared to terrestrial carnivores of similar brain sizes (c.v.
African lion, Panthera leo, brain, Fig. 62 in Welker, 1990). Also note the very anterior location of the orbital gyrus, indicating a
proportionately very small amount of prefrontal cortex. The brain photographed here is from the collection of Dr Sam H. Ridgway.
Paul R. Manger
A reanalysis of carnivore brain and body size data was
undertaken here to examine if trends similar to those de-
scribed above for cetaceans were evident. The data used
were generously supplied by Olaf Bininda-Emonds from
that used by Bininda-Emonds et al. (2001). Two groups of
carnivores were examined: unambiguously terrestrial car-
nivores and pinnipeds. Other ‘aquatic’ species as defined by
Bininda-Emonds et al. (2001) were excluded. Allometric
equations describing the brain-body mass scaling of these
groups were calculated (Fig. 19).
The terrestrial carnivores show a typically mammalian
intraordinal scaling of brain and body mass (see Armstrong,
1990, and the present analysis of ungulates in Section VI)
with a slope of 0.66 (r2=0.91, P=6.6r10x114). However,
the relationship for pinnipeds has a much shallower slope of
0.46 (r2=0.77, P=1.7r10x12; P=0.004 for a comparison
using the mean squares between and within slopes of the
regressions for pinnipeds and terrestrial carnivores). This
slope is not significantly different from that calculated for
odontocetes (equation 4, Figs 2 and 12) where the slope was
0.469 (a comparison of the regressions derived for pinnipeds
and odontocetes revealed no significant difference using the
mean squares between and within slopes, P=3.46). This
implies that similar selection pressures act on the scaling of
pinniped brains to those of odontocete cetaceans, lending
support to the hypothesis that water temperature is a sig-
nificant evolutionary pressure on homeotherms inhabiting
an aquatic environment. Fig. 19A shows that smaller pinni-
peds have higher EQs than most carnivores whereas larger
ones would have lower EQs than a hypothesized carnivore
of similar body size.
The eared seals and sea lions (Otariidae) and walrus
(Odobenidae) exhibit unihemispheric sleep, while the non-
eared seals (Phocidae) do not (Lyamin, 1987, 1993; Lyamin
& Chetyrbok, 1992; Lyamin, Oleksenko & Polyakova, 1989,
1993; Lyamin et al., 1996; Mukhametov, Supin &
Polyakova, 1984; Mukhametov, Lyamin & Polyakova,
1985). Intrasubordinal analyses of these groups indicates no
difference in scaling that might be attributable to this dif-
ference in unihemispheric sleep phenomenology (Fig. 19B).
The unihemispheric sleepers have a slope of 0.41 (r2=0.81,
P=1.2r10x6) compared to 0.50 (r2=0.81, P=1.3r10x8)
for bihemispheric sleepers; the difference between these
slopes is not significant (P=0.235).
The pinnipeds evolved more recently than the cetaceans
(Bininda-Emonds et al., 1999); however, there are some
fossil endocasts available. As summarised by Edinger (1975),
the general form and shape of the brain of extinct pinnipeds
does not differ dramatically from their modern rep-
resentatives, although the cerebral hemispheres are not
as gyrencephalic as in extant pinnipeds. Thus, there
appears to have been an increase in the gyrencephalic
nature of the cerebral hemispheres of pinnipeds over time.
While the evidence is not extensive, the trends exhibited in
pinnipeds are similar to those discussed above for cetaceans,
implying that water temperature is a significant selective
The Sirenia are represented by two families the Dugongidae
and the Trichechidae, all inhabiting shallow coastal equa-
torial waters. The Dugongidae is represented by only one
extant species, Dugong dugon; the Stellar’s sea cow,
Hydrodamalis gigas, a member of the Dugongidae, was hunted
to extinction in the 1700s. There are three extant species of
the Trichechidae. The brain of the West Indian, or Florida,
manatee (Trichechus manatus) is the subject of a special re-
search project (http://www.manateebrain.org).
Like other aquatic mammals, the superficial structure of
the manatee brain appears unusual, being lissencephalic
except for one major sulcus (Fig. 20). Extant sirens
have extremely enlarged lateral ventricles. O’Shea & Reep
(1990) recorded brain and body masses for the sirens, which
can be used in an allometric analysis: Dugong dugon (N=2)
brain mass 250–282 g, body mass 262–300 kg; Trichechus
manatus (N=13) 309–445 g (mean 364 g) and 449–1620 kg
(mean 756 kg) respectively; Hydrodamalis gigas (N=3)
Fig. 19. Allometric plots of brain mass versus body mass for (A)
pinnipeds and terrestrial carnivores, and (B) Otariidae and
walrus which have unihemispheric sleep patterns, and phocids
(bihemispheric sleepers). Data are derived from Bininda-
Emonds et al. (2001).
Cetacean brain evolution and thermogenesis
1014–1129 g (mean 1068 g) and 5335–8870 kg (mean
The allometric equation derived from these data (Fig. 21)
shows a strong resemblance to those derived previously for
cetaceans and pinnipeds; the slope (0.43) is not significantly
different from that calculated for odontocete cetaceans
(slope=0.47, comparison between slopes P=1) and pinni-
peds (slope=0.46, comparison between slopes P=0.96),
Fig. 20. Photographs of the lateral (A) and dorsal (B) surfaces of the brain of the Florida manatee (Trichechus manatus). Scale
bar=1 cm. Note the unusual form of the brain, with the large Sylvian (or lateral) cleft (or fossa) on the lateral aspect of the cerebral
hemisphere, resembling human agyria pathology (see Fig. 26 in Welker, 1990). The brain photographed here is from the collection
of Dr Sam H. Ridgway.
Paul R. Manger
indicating that the brain-body mass scaling is similar in
all three groups of aquatic mammals. The correlation co-
efficient (r2) is higher for sirenians (0.978, P=2.1r10x6)
than for other aquatic groups.
Encephalisation quotients calculated using the general
mammalian regression (see Section II.1, equation 1), were
found to be 0.52–0.53 for the dugong, 0.25–0.43 for the
manatee, and 0.18–0.23 for the Stellar’s sea cow. These
values are slightly higher than those reported by O’Shea &
Reep (1990) due to the different equations used to derive
A cytoarchitectural analysis of the manatee cerebral cor-
tex available at http://www.manateebrain.org reveals fea-
tures in common with cetaceans. There appears to be very
few cortical areas. There also appears to be a very small
amount of cortex at the anterior pole of the brain that might
be prefrontal cortex, the primary motor cortex being located
very close to the anterior pole. Given that premotor cortex
must be rostral to this region, any prefrontal cortex must be
small. However, published proportions of various structures
of the manatee brain indicate that the corticalisation index is
63.96% (see Fig. 8, and Reep & O’Shea, 1990, who give
telencephalic volume as 71% of total brain volume, and the
cerebral cortex as 90% of this volume). As noted by Reep &
O’Shea (1990), the percentage of the brain that is cerebral
cortex is within the range of mammals of similar brain size,
but from Fig. 8 is somewhat below the values observed in
Another interesting parallel is the unihemispheric nature
of sleep in the manatee (Mukhametov et al., 1992).
Unihemispheric slow-wave sleep occupies approximately
25% of total sleep time, and REM sleep approximately 1%
of total sleep time in the Amazonian manatee (Trichechus
inunguis), with the remainder made up of bihemispheric
slow-wave sleep. This sleep behaviour might relate to en-
vironmental temperature: dugongs (Dugong dugon) reportedly
avoid water temperatures below 19 xC (Anderson, 1986),
Amazonian manatees (Trichechus inunguis) have been kept
successfully in water temperatures between 22 x and 30 xC
(Husar, 1977), West Indian manatees (Trichechus manatus)
prefer water temperatures above 20 xC (Lefebvre et al.,
1989), and the West African manatee (Trichechus senegalensis)
is distributed in waters with a temperature minimum of
18 xC (Husar, 1978). Moreover, the sirenians have an ex-
tensive blubber layer, ensheathed in a skin that is up to 5 cm
thick, even though they have been shown to have a high rate
of thermal conductance (Irvine, 1983), which is thought to
limit their distribution to warmer waters.
Behavioural tests examining the cognitive abilities of the
sirens have not been performed. However, it has been ob-
served that dugongs can ‘gang up’ to drive sharks from their
shallow-water feeding locations by butting them with their
heads (Lekagul & McNeely, 1977). Similar behaviour is seen
in some cetaceans, suggesting that it is not a behaviour that
requires unusually large cognitive abilities.
Several fossilized endocasts of the Sirenia have been de-
scribed, and Edinger (1975) provides a summary of sirenian
brain evolution. Sirenians first appeared in the Eocene
(Savage, 1976); endocasts of Eocene to Recent sirenians
show few changes: the lissencephalic nature of the sirenian
brain and its size are unaltered over time. The sirens evolved
in an aquatic habitat over approximately the same length
of time as the cetaceans, but in contrast to the punctuation
in brain size evolution seen for cetaceans, the brain size of
Fig. 21. Allometric plot of brain and body mass in sirenians, pinnipeds and odontocetes (data derived from O’Shea & Reep, 1990;
Bininda-Emonds et al., 2001; and Table 1). Note that all three aquatic mammalian groups scale similarly, and that the sirenians have
the lowest relative brain sizes.
Cetacean brain evolution and thermogenesis
sirenians has remained stable. This contrast might be related
to the lack of environmental expansion of the sirenians
compared to cetaceans. Both groups were abundant and
diversified in the Tethys sea and were also found in equa-
torial Central America and Asia (Savage, 1976) during the
Eocene. At the Oligocene transition of Archaeoceti to
modern cetaceans, several new species of Sirenia appeared
(Savage, 1976). However, no change in brain size and
structure, and no expansion of their distribution occurred in
The sirens have a similar brain-body mass scaling as other
marine mammals (Fig. 21), but it appears that they arrived
at this common scaling in a different manner. O’Shea &
Reep (1990) provide data on the growth rate of the manatee
(Trichechus manatus) brain and body. They show that the
majority of postnatal brain growth occurs within the first
two years of life (prior to weaning). There is then further
enlargement of the body, with no enlargement in brain size,
for the next eight years. Thus, in the sirens brain growth
ceases early, with an extended period of body growth
(O’Shea & Reep, 1990). A contrasting pattern of brain
growth occurs in cetaceans. The most comprehensive data
set was compiled by Pirlot & Kamiya (1982) for the striped
dolphin (Stenella coeruleoalba) and indicates that brain and
body size growth rates are not uncoupled as seen in the
manatee but brain growth continues into adulthood.
(1) This paper provides a comprehensive review of the
salient features of the cetacean brain in relation to behaviour
and evolution of this mammalian order. It is demonstrated
that there are no neurological correlates for the purported
intellectual abilites of cetaceans, and that the evolution of the
extant cetacean brain, in terms of size, micromorphology
and unusual sleep phenomenology, can be explained in
terms of water temperature being a significant selection
(2) The scaling of cetacean brain mass in relation to body
mass differs to that of other mammalian orders, leading to
relatively large encephalisation quotients (EQ) for smaller
cetaceans and relatively small EQs for larger cetaceans.
Individuals of the same species show similar scaling trends of
brain and body mass to that of the entire order, indicating
that a similar selection pressure shapes this relationship in
(3) The neuroanatomical features of the cetacean cer-
ebral hemisphere do not indicate a structure supportive of
high levels of intellectual capacities. In particular, the high
glia:neuron index, the poorly differentiated neuronal mor-
phology, the low number of neurons and cortical areas, the
lack of a distinct pre-frontal cortex, the small hippocampal
formation, and the altered proportions of the neuropil, will
all impact negatively on the processing capacity of the cer-
(4) The vocalisations of cetaceans appear to be under the
control of a specialised brainstem system of the peri-
aqueductal grey matter, the nucleus ellipticus, which may in
fact be a vocal pattern generator. This differs to the corti-
cally based language found in humans, and argues against
suggestions of cetacean linguistic and cultural abilities.
(5) It is hypothesised that unihemispheric slow-wave
sleep and lack of REM sleep in cetaceans functions to
compensate for heat loss to the water during sleep. As sig-
nificant thermogenesis is downregulated during sleep in
normal mammals, this altered sleep pattern will allow
thermogenesis to be maintained in both the brain (through
increased glial metabolism via noradrenergic stimulation)
and the body (through increased muscular movement).
The restorative function of sleep can then be enabled in
an aquatic environment where heat is lost approximately
90 times faster than in air.
(6) It is shown that during the course of cetacean evol-
ution there was a major punctuation in brain size, seen
mainly as an increase in the size of the cerebral hemispheres.
This punctuation occurred at the transition of the ancestral
cetacean faunal assemblage (the archaeocetes) to the
modern cetacean fauna (the Oligocene cetaceans) approxi-
mately 32 million years ago. At this transition there was a
dramatic increase in both actual and relative brain size that
coincided with the loss of a warm and nutrient-rich
environment (the Tethys sea) and global oceanic cooling
of water temperatures. Following this the size of the brain
remained stable. Such a marked change in brain size does
not occur in the closely related ungulates over the same time
(7) It is demonstrated that previous proposals of the
causal factors underlying large relative brain size in the
smaller cetaceans do not explain the full range of observ-
able data. Theories associating relative brain size with
an increase in general levels of intelligence rely upon un-
proven assumptions. Vocalisations are shown to consist of
seven species-typical calls and not a language. The anatomy
of the acoustic system demonstrates that while it is special-
ised, this is to a similar degree as specialised sensory sys-
tems in other mammals with standard brain sizes and
therefore cannot be a contributing factor to increased rela-
tive brain size. Finally, it is shown that apparent con-
vergences in primate and cetacean behaviour and the
behavioural assumptions upon which these are based are
(8) The observations made are drawn together to dem-
onstrate that water temperature as a selection pressure may
explain all facets of the evolution of the modern cetacean
brain. The archaeocete/Oligocene cetacean transition,
which coincided with major changes in brain mass and
scaling, is coincident with a significant reduction in oceanic
temperatures. The microanatomy of the cetacean brain, and
their altered sleep phenomenology, indicates that the cet-
acean brain may be an effective thermogenetic organ. The
scaling of brain to body mass in cetaceans (or the EQ as
based on a mammalian regression) is found to be signifi-
cantly linked to the range of oceanic temperatures inhabited
by the various extant cetacean species. Lastly, it is shown
that the actual size of the cetacean brain may be due to the
combination of three constraints: the allometric birth mass
of eutherian mammals, the minimum birth mass required to
prevent lethal hypothermia in aquatic mammals, and the
Paul R. Manger
allometric relationship between EQ and water temperatures
in adult cetaceans.
(9) Along with supporting evidence from other marine
mammals, this thermogenetic hypothesis of cetacean brain
evolution represents a credible and testable alternative to
explain actual and relative brain size, brain micro-
morphology, behaviour, and sleep phenomenology in the
extant and extinct cetaceans.
(10) It is the first hypothesis to relate these features to a
specific and significant environmental selection pressure
during evolutionary history.
I wish to thank the many colleagues and friends with whom I have
discussed the ideas presented here (although some of them did
suffer!). Of course not all of them agree, and I must take full re-
sponsibility for any bad, or good, ideas that have arisen, but the
lively debate only helped to sharpen ideas and make the arguments
more cogent. These people include in particular: Anne Butler, Guy
Elston, Patrick Hof, Carl Holmgren, Niklas Lindgren, Oleg
Lyamin, Zolta ´n Molna ´r, Jack Pettigrew, Ernesto Restrepo, Sam
Ridgway, Per Roland, Olga Shpack, Jerry Siegel, Sven O¨gren, and
Peter A˚rhem. Special thanks also to Olaf Bininda-Emonds, Patrick
Hof, and Sam Ridgway, for generously supplying unpublished data
sets and photographs and to Jason Hemingway for his invaluable
assistance with the statistical analyses. Most of all I thank Oxana
Yeshenko for introducing me (on the banks of the Aura Joki in
Turku, Finland) to the extraordinary behavioural concepts of Kira
Nikolskaya, and for Kira (at Moscow State University) and Oxana
for spending so much time explaining the specifics of these ideas to
me. Without this information I am certain that the problem of
cetacean brain evolution would not have become such a focus of
my efforts over the past years.
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