Current Zoology
61 (2): 274–280, 2015
Preliminary notes on brain weight variation across labrid
fish species with different levels of cooperative behaviour
Marta C. SOARES*, Gonçalo I. ANDRÉ, José R. PAULA
CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Campus Agrário de Vairão,
4485-661 Vairão, Portugal
Abstract Brain size and weight vary tremendously in the animal kingdom. It has been suggested that brain structural development must evolve balanced between the advantages of dealing with greater social challenges and the energetic costs of maintaining and developing larger brains. Here we ask if interspecific differences in cooperative behaviour (i.e. cleaning behaviour) are
related to brain weight variations in four close-related species of Labrid fish: two are obligatory cleanerfish throughout their entire life (Labroides dimidiatus and L. bicolor), one facultative cleaner fish Labropsis australis and one last species that never engage in cleaning Labrichthys unilineatus. We first search for the link between the rate of species’ cooperation and its relative
brain weight, and finally, if the degree of social complexity and cooperation are reflected in the weight of its major brain substructures. Overall, no differences were found in relative brain weight (in relation to body weight) across species. Fine-scale differences were solely demonstrated for the facultative cleaner L. australis, at the brainstem level. Furthermore, data visual examination indicates that the average cerebellum and brainstem weights appear to be larger for L. dimidiatus. Because variation was
solely found at specific brain areas (such as cerebellum and brainstem) and not for the whole brain weight values, it suggests that
species social-ecological and cognitive demands may be directly contributing to a selective investment in relevant brain areas.
This study provides first preliminary evidence that links potential differences in cognitive ability in cooperative behaviour to how
these may mediate the evolution of brain structural development in non-mammal vertebrate groups [Current Zoology 61 (2):
274–280, 2015].
Keywords
Brain weight, Body weight, Macro-area weight, Labridae, Cooperation, Cleaning behaviour
Recent evidence has implicated vertebrate social landscape, even more than ecological factors, as the main
underlying factor shaping brain evolution and cognitive
competences (Barton and Dunbar, 1997; Byrne and
Bates, 2007; Dunbar and Shultz, 2007). Due to the high
metabolic cost of brain tissue, it is expectable that larger
brained species trade-off the investment in brainpower
for the ability to deal with complex cognitive challenges
(Jerison, 1973; Aiello and Wheeler, 1995). So far, the
strongest proxies of general brain size development
across species are group size and social bonds, which
ultimately reflect the cognitive demands necessary to
coordinate and synchronize behaviours between individuals and within groups (Dunbar and Shultz, 2007;
Shultz and Dunbar, 2010). The rise of the demands on
cognitive abilities should alter the size of neural structures while the converse should also occur, with interspecific variance of relative brain size reflecting cognitive complexity (Kotrschal and Junger, 1988; Clark et
al., 2001; de Winter and Oxnard, 2001, Gonzalez-Voyer
et al., 2009).
Received Oct. 14, 2014; accepted Feb. 3, 2015.
 Corresponding author. E-mail: [email protected]
© 2015 Current Zoology
To understand the evolution of brain structural development and how it is linked to social cognitive abilities, we must look at vertebrate species other than primates and other mammals (Bshary, 2011; Bshary et al.,
2014). Teleost fish for instance have been relatively
well studied on the relationship between brain structure
and the relative development of brain areas, which tend
to be closely associated to feeding mode (diet), habitat
complexity, life-history and care type (Kotrschal et al.,
1998; Huber et al., 1997; Pollen et al., 2007; Ito et al.,
2007; van Staaden et al., 1995; Kolm et al., 2009;
Gonzalez-Voyer et al., 2009). For intance, in cichid
fishes, piscivours have larger olfactory bulbs and optic
tecta than otherwise insectivorous and zooplactivorous
(Huber et al., 1997). In another study, also aimed at
Tanganyikan cichlids, habitat complexity has been
found to associate with larger brains and, with both cerebella and telecenphalon showing a similar pattern
(Pollen et al., 2007). Sex- related characteristics might
also influence brain evolution: for instance, females that
provide sole parental care were found to have larger
SOARES MC et al.: Brain weight variation and cooperative behaviour
brains (Gonzalez-Voyer et al., 2009). Hence, uniparental
care appears to impose an extra selection pressure on
female cognitive demands (Gonzalez-Voyer et al., 2009).
More recently, Kotrschal and colleagues (2013) provided experimental evidence (using the guppy Poecilia
reticulata) that relative brain size evolved rapidly but
responded differently in both sexes and, proposed that
brain size evolution is mediated by a functional tradeoff between cognitive ability and reproduction performance.
Teleost fish, can express complex cognitive abilities
contrarily to amphibians and reptiles, which generally
show little scope for social behaviour (Byrne and Bates,
2007). For instance, fishes are particularly suitable to
study social complexity resulting from stable interspecific interactions as they permanently occur in interspecific shoals (Bumann and Krause, 1993), forage in
mixed-species parties (Dugatkin and Godin, 1992), hunt
with interspecific partners (Bshary et al., 2006) and engage in cooperative interactions (e.g., interspecific
cleaning, Feder, 1966; Côté, 2000). Marine cleaning interactions and specifically cleaner fish species, offer a
promising model system to study the evolution of cooperative behaviour as closely related species may differ
markedly in the degree to which they depend on interactions with other species for their diet (Feder, 1966).
Cleaners are fishes that inspect the body surface, gill
chambers and mouth of cooperating larger fishes (known
as clients) in search of ectoparasites, mucus and dead or
diseased tissue (Limbaugh, 1961; Feder, 1966; Gorlick
et al., 1987; Losey et al., 1999; Côté, 2000).
However, in the well-studied Indo-Pacific bluestreak
cleaner wrasse Labroides dimidiatus conflicts over the
quality of each interaction are frequent because these
often feed on healthy tissue, mucus or scales instead on
clients’ ectoparasites, which they prefer (Grutter and
Bshary, 2003). In these situations, cleaners often ride
the back of their clients and provide a massage with
their pelvic and pectoral fins — a behaviour termed
tactile stimulation (Bshary, 2002), which is known to
lower basal and acute cortisol levels in clients (Soares et
al., 2011). Solely in this species, many interesting and
complex behaviours have so far been described, such as:
individual recognition of their clients, manipulation of
client decisions (on different levels of action), reconciliation, punishment, advertising of their cleaning services, tactical deception and indirect reciprocity based on
image scoring (reviewed by Bshary and Côté, 2008;
Bshary and Noe, 2003; Bshary, 2001). Moreover, these
cleaners often work in stable male-female pairs, and
275
their service quality towards clients varies depending on
whether they clean alone or in pairs (Bshary et al.,
2008).
Here we ask if interspecific differences in cooperative behaviour towards clients (i.e. cleaning behaviour)
are related to brain weight variations in four close-related
species of Labrid fish belonging to the tribe Labrichthyni (Westneat and Alfaro, 2005; Cowman et al., 2009).
We choose two Labrid fish (Fig. 1, tribe Labrichthynes)
that are obligatory cleaners throughout their entire life
(L. dimidiatus and L. bicolor), one other species that is a
facultative cleaner (Labropsis australis; juvenile are
cleaners and adults are corallivorous), and one
“non-cleaner” species (Labrichthys unilineatus; corallivorous throughout its entire life, Fulton and Bellwood
2002, Cole 2009, 2010). Species selection was based on
their phylogenetic proximity and on the variance regarding the expression of cleaning behaviour, while
these inhabit, in theory, similar environmental conditions (e.g. coral reefs, Cole, 2010). Both chosen obligatory species have a wide array of behavioural similarities (e.g. they engage in cleaning with a great number of
species and adjust their behaviour in accordance) but
they differ on a few other important characteristics, such
as territory size, which will potentially change the likelihood that repeated interactions will occur with the
same partner and have a direct influence on these cleaners behaviour (Oates et al., 2010). As cleaner-client
interactions occur in an extremely dynamic context,
cleaners must continuously act and react in response to
stimuli, if they want to continue to forage. Consequently,
evolution should select for the development of the best
framework mechanisms that enable these cleaners to
respond to daily complex social challenges. We investigated if these species socio-ecological challenges are
linked to an overall brain weight increase, particularly
in obligate cleaner fish species. Nevertheless, considering that even between such close-related obligatory
cleaner fish species, cognitive challenges may differ, we
expect that these may distinctively contribute to brain
weight development. Moreover, we predict a higher
Fig. 1 Cladogram with the Labrichthynes lineage, including our study species
Adapted from (Cowman et al., 2009)
276
Current Zoology
brain weight development in integration areas (such as
telencephalon, diencephalon and cerebellum) contrarily
to sensory brain areas (as the optic tectum and brain
stem) for obligatory cleaner fish species when compared with non-cleaner species.
1
Materials and Methods
1.1 Study species
We used a total of 13 L. dimidiatus (standard length,
mean ± SEM = 5.815 ± 0.274; body mass, mean ± SEM
= 2.767 ± 0.391), 17 L. bicolor (SL = 6.471 ± 0.279;
BW = 4.216 ± 0.716), 14 L. australis (SL = 6.564 ±
0.284; BW = 4.517 ± 0.636) and 12 L. unilineatus (SL =
8.725 ± 0.422; BW = 6.465 ± 1.795).
Most of the knowledge on the behavioural biology of
these species is focused on L. dimidiatus. L. dimidiatus
are protogynous hermaphrodites, i.e. individuals first
reproduce as females and eventually change sex into
males that control a harem of females (Robertson, 1972).
Thus, in the wild the amount of females available is
always quite higher than those of males. Because all
fish were wild caught and imported to Portugal by a
local distributor, only a residual amount of these were
males. We thus decided to use solely adult females in
order to avoid spurious effects of possible sex differences, due to sample size differences. The sex of all
individuals was confirmed by direct inspection of the
gonads and with the help of an acetocarmine stain
(Guerrero and Shelton, 1974).
1.2 Brain sampling
All fish were euthanised with an overdose of tricaine
solution (MS222, Pharmaq; 500–1000 mg/L) and the
spinal cord sectioned to be sure that the animal was
dead. The brain was then visually macro-dissected from
the cranial cavity, under a stereoscope (Zeiss; Stemi
2000) into five areas: Forebrain (olfactory bulbs + telencephalon), Diencephalon, Optic tectum, Cerebellum
and Brain stem. Brain areas were then weighted in an
analytical balance OHAUS.
1.3 Experimental design caveat
In this study we choose four phylogenetic close related species that are also known to express different
levels of cooperative behaviour. Our scope of inference
may therefore be theoretically limited to the small
number of species used. However, this was designed to
be a preliminary study, which could provide first indications on how this behavioural variance could be reflected on structural brain changes. Questions have also
arisen, to the method chosen here to divide the brains
substructures. We followed the methodology used in
Vol. 61 No. 2
recent studies (Almeida et al., 2012, Teles et al., 2013)
to ascertain the neuro-hormonal (neuropeptides and
neurotransmitters) changes at brain substructure level.
In theory, the methodology used seems rather course,
which could potentially hinder the disclosure of some
patterns. However, we consider this unlikely because it
is a methodology already established which may provide additional information to the majority of volumetric-based studies.
1.4 Statistical analysis
First, to examine the importance total body weight
and species differences as determinants of whole brain
weight we used analyses of covariance (ANCOVA) with
species and body weight as a continuous covariate.
Then, to examine the importance of overall brain weight
and species differences as determinants of each specific
macro-area (Forebrain, Diencephalon, Optic Tectum,
Cerebellum and Brainstem) weight we used analyses of
covariance (ANCOVA) with species and whole brain
weight as a continuous covariate. All tests were done in
SPSS Statistics, version 22.
2
Results
Overall, brain weight did not differ with body weight
(ANCOVA F1,48 = 0.006, P = 0.936; Fig. 2, Table 1) or
across species (F3,48 = 2.124, P = 0.109, Fig. 2, Table 1),
however there was a significant interaction between
species and body weight (F3,48 = 3.458, P = 0.023, Fig.
2, Table 1). Visual examination of Fig. 2 indicates this is
likely due to a negative relationship between brain and
body weight for the obligatory cleaner fish L. dimidiatus.
For the majority of specific macro-areas, weight did
not vary amongst species (forebrain: F3,48 = 0.404, P =
0.751; diencephalon: F3,48 = 0.604, P = 0.615; optic
Fig. 2 The relationship between individual total brain
weight and body weight for each of our study species
SOARES MC et al.: Brain weight variation and cooperative behaviour
tectum: F3,48 = 0.045, P = 0.987; cerebellum: F3,48 =
0.624, P = 0.603; Fig. 3A–D, Table 2) but differed
significantly with total brain weight (forebrain: F1,48 =
149.316, P < 0.001; diencephalon: F1,48 = 78.680, P <
0.001; optic tectum: F1,48 = 39.959, P < 0.001; cerebelTable 1
277
lum: F1,48 = 109.463, P < 0.001; Fig. 3A–D, Table 2).
The exception was the brainstem weight, which differed
with brain weight (ANCOVA F1,48 = 80.556, P < 0.001,
Fig. 3E, Table 2) but did not vary across species (ANCOVA F3,48 = 0.855, P = 0.471, Fig. 3E, Table 2).
Regression values for overall brain weight plotted against body weight (Fig. 2), for our studied labrid species
Brain structure
Whole Brain
L. dimidiatus
L. bicolor
L. australis
L. unilineatus
Slope (α)
Intercept (β)
Slope (α)
Intercept (β)
Slope (α)
Intercept (β)
Slope (α)
Intercept (β)
-0.009
0.079
0.002
0.052
0.004
0.040
0.003
0.057
Fig. 3 The relationship between individual brain macro-areas weight and
total brain weight for each of our study
species according to: A) forebrain, B)
diencephalon, C) optic tectum, D) cerebellum and E) brainstem
Table 2 Regression values for weight of individual brain macro-areas plotted against overall brain weight (Fig. 2A–E) in
our studied labrid species
Brain structure
L. dimidiatus
L. bicolor
Slope (α)
Intercept (β)
Slope (α)
Intercept (β)
L. australis
Slope (α)
L. unilineatus
Intercept (β)
Slope (α)
Intercept (β)
Forebrain
0.213
-0.001
0.236
-0.001
0.202
0.002
0.271
-0.003
Cerebellum
0.227
-0.004
0.101
-0.004
0.078
-0.006
0.154
-0.005
Diencephalon
0.202
0.001
0.281
0.001
0.422
-0.006
0.216
0.003
Optic Tetum
0.175
0.005
0.207
0.004
0.192
0.003
0.236
0.006
Brainstem
0.182
0.000
0.134
0.000
0.043
0.003
0.123
-0.001
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Current Zoology
Moreover a significant interaction was found between
brainstem and brain weight (ANCOVA F3,48 = 0.006, P =
0.936, Fig. 3E, Table 2). Visual examination of Fig. 3E
indicates that the average brainstem weight adjusted for
total brain weight seems lower in L. australis than for
the remaining species.
3
Discussion
In this study, we predicted that differences in cognitive abilities related to cooperative behaviour could be
an overall selective force on brain weight variance but
that differences would also be found at brain macro-area
level. Indeed, significant fine-scale differences were
demonstrated for the facultative cleaner L. australis, at
the brainstem level, while further data visual analysis
indicated that the average cerebellum and brainstem
average weight seem also to be larger for L. dimidiatus.
However, variation was solely found on specific brain
areas and not on whole brain weight values, which suggests that species social-ecological and cognitive demands might be directly contributing to more selective
investment in relevant brain areas.
In a recent study Kotrschal and colleagues (2013)
proposed that the increase of cognitive ability (tested in
a associated learning assay) in guppies should be mediated by rapid evolution of brain size. Both obligatory
cleaner fish species (L. dimidiatus and L bicolor) would,
in theory, be perfect candidates to test the influence of
living in a complex social environment and if this could
be linked to a potential rise in brain weight. Indeed,
individuals of these species similarly interact with a
wide array of interspecific partner individuals and exhibit some flexibility in adjusting their levels of cooperation. Moreover, the requirement of cleaning in malefemale pairs, e.g. to the need to synchronize and adjust
behaviour in accordance to the response of its conspecific male partner (female behavioural adjustment during pairwise inspections), would be a further selective
force exerting high cognitive demands on females of L.
dimidiatus. However, we failed to detect significant
differences in overall brain weight between females of
our close related labrid species. The absence of evidence revealed here may be due to the small number of
species considered in this study, to the lack of control
when it comes to fish age and to other biotic (client fish
diversity, predation pressures) and abiotic variables (for
instance, reef structural differences, temperature shifts,
currents) which limited the strength of our analysis.
Furthermore, visual analysis of L. dimidiatus data revealed a surprising negative relationship between brain
Vol. 61 No. 2
and body weight. It looks like data is distributed in two
groups: one with smaller brain weight and larger whole
brain weight and, a second group of individuals that
hold larger body weight but smaller whole brain weight.
And the same trend occurs when body size (instead of
body weight) is considered. In a recent study, Wismer
and colleagues (2014) showed that L. dimidiatus coming from 2 different locations varied tremendously in
terms of behavioural performance in cooperative tasks.
These authors found that individuals that failed in these
tasks lived in a socially simple environment (these live
in patch reefs while others habit fringing reefs, both
around the coasts of Lizard Island, Australia), which
could be affecting their ability to acquire and storage
information (Wismer et al., 2014). So far, no further
structural and physiological information have been gathered from these two populations of L. dimidiatus. Because our sampled L. dimidiatus were wild caught, it
could be that these were, for instance, collected at two
different sites/reefs, however at this point we can only
speculate. While it is impossible to find out more about
the specific origin of these individuals, our data adds to
the already published evidence that L.dimidiatus populations are quite variable and may live in social environments that differ significantly in terms of cognitive
challenges. The extent of link and causality between
environment complexity and these individuals’ structural/brain development is still to be discovered.
In the current study, we also predicted to find finerscale weight differences (brain macro-areas), which
would further help to localize cognitive development to
a more specific brain area. These fine-scale differences
were solely demonstrated for the facultative cleaner fish
L. australis, at the brainstem level. L. australis brainstem average weight adjusted for total brain weight appears to be lower than all other close-related species.
However, it is important to mention that only L. australis adults were sampled, which were all at a non-cleaner
stage of life. Interestingly, visual analysis of Figure 3D
and 3E indicates that the cerebellum and brainstem average weight seems to be larger for L. dimidiatus. The
cerebellum is one of the most variable parts of the vertebrate brain in terms of size, mass and shape, however
its neurophysiological mechanisms and neural circuitry
are quite conservative across vertebrate species (Rodríguez
et al., 2005). Usually associated with motor control, the
involvement of the teleost cerebellum and associated
brainstem circuitry is highly implicated in several cognitive and emotional functions, particularly in associative learning and memory processes (Rodríguez et al.,
SOARES MC et al.: Brain weight variation and cooperative behaviour
2005). It is probably through associative learning that
most of the behavioural tactics shown by L. dimidiatus
are acquired. These cleaner fish have about 2,000 behavioural interactions per day (Grutter, 1995), therefore, in
spite of interacting with a wide diversity of partner species; the constant and contiguous amount of feedback
received may easily become predictable. This type of
“classical” delay learning depends (classical conditioning) on the cerebellum and associated brainstem circuitry (Rodríguez et al., 2005; Gómez-Laplaza and Gerlai,
2010; Yoshida and Hirano, 2010) while for instance the
ablation of the forebrain will not impair this type of
learning (Gómez et al., 2004; Bangasser et al., 2006).
Visual analysis of Figure 3B indicates that L. australis have a higher diencephalon average weight (adjusted
for total brain weight) when compared to the remaining
species. This is an interesting trend that may reflect this
species’ ontogenetic shifts in habitat and feeding mode
(from cleaners during the juvenile stage to non cleaners
in the terminal adult stage) and, may also reflect the
influence of certain key neurohormonal compounds. For
instance, the number of cells expressing the hypothalamic neuropeptide arginine vasotocin (AVT) is known
to continue to increase with growth until differentiation
to terminal phase males, in the facultative bluehead
cleaner fish Thalassoma bifasciatum (Godwin et al.,
2000). One can speculate that a similar trend of growth
of AVT ir-cells may underline sexual and foraging transitions observed in L. australis. Also, evidence shows
that L. dimidiatus have smaller and less numerous AVTir neurons than the non-cleaner species, L. unilineatus
(Mendonça et al., 2013). In that case, it would be expectable for cleaners to hold a smaller number of AVT
varicosities projecting to their telencephalon (forebrain),
contributing to a decrease of this area’s brain tissue,
however no differences were found. Finally, the absence
of significant differences in the optic tectum may be a
reflection of living in similar environmental conditions:
all species inhabit clear coral reef waters and rely tremendously on visual signals (Cole, 2010).
This study provides first indications on the appropriateness of these model species to future studies (both
in the wild and in artificial conditions), while further
focus should be given to the effects of other behavioural
traits associated with cooperation, on brain structural
development. More is still to be discovered regarding
the strength of cognitive benefits and, on the extent of
trade-offs, between the costly investment in brain tissue
and other aspects of organisms’ biology (such as muscle,
gonads, fat storage or even reproductive success; Kotr-
279
schal et al., 2013).
Acknowledgments We thank Gonçalo Cardoso for helpful
comments on an earlier version of the manuscript. This study
was financed by Fundação para a Ciência e Tecnologia (FCT,
grant PTDC/MAR/105276/2008 given to MCS). MCS is supported by the Project “Genomics and Evolutionary Biology”,
co-financed by North Portugal Regional Operational Programme 2007/2013 (ON.2 – O Novo Norte), under the National Strategic Reference Framework (NSRF), through the
European Regional Development Fund (ERDF). Animal procedures used in this study have been approved by the Portuguese Veterinary Office (Direcção Geral de Veterinária, license # 0420/000/000/2009).
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