Total neocortical cell number in the mysticete brain

Total Neocortical Cell Number in theMysticete Brain

NINA ERIKSEN,* AND BENTE PAKKENBERGResearch Laboratory for Stereology and Neuroscience,

University of Copenhagen Bispebjerg Hospital, Copenhagen, Denmark

ABSTRACTThe cetacean brain has long been of scientific interest, not only

because of its large size – the largest in the animal kingdom – but alsobecause of its high gyrification. It shows several adaptations to the aquaticenvironment, especially in the cortical arrangements of functional areas.To study structural aspects of the mysticete brain we estimated neocorticalfeatures in the common minke whale using stereological methods. Theneocortex was surprisingly thick, equal to that in humans. The total neo-cortical neuron number was 12.8 3 109, and the total neocortical glia num-ber 98.2 3 109. Total cell numbers in the auditory and visual cortex werealso estimated, and showed that the auditory cortex contained more cellsthan the visual cortex. In this small sample, no sexual dimorphism wasseen within the neocortex of the common minke whale. Our aim was toestimate the total cell number, cortical volume and cell density in theentire mysticete neocortex and compare the total cell number in the audi-tory cortex with that of the visual cortex using stereological methods.Here, we used the common minke whale as a model of all mysticetes. Wewanted to compare these neocortical features to those of other mammalsto forward understanding of the evolution of the mammalian brain. Anat Rec,290:83–95, 2007. � 2006 Wiley-Liss, Inc.

Key words: mysticete; neocortex; cell number

The number of neurons and their relative abundancein different parts of the brain is at least partly a deter-minant of neural functions and consequently also a de-terminant of behavior. The neurons and glia in the neo-cortex in particular are involved in important brainprocesses, and it is assumed that neurons are somehowresponsible for the evolution of intelligence, since phylawith larger brains and more neurons more easily adaptto environmental change with a greater range and ver-satility of behavior (Jerison, 1985). Cetaceans possesscomplex behaviors and social patterns, such as culturaltransmission of vocal and behavioral traits (Payne andPayne, 1985; Rendall and Whitehead, 2001), and bottle-nose dolphins have shown that they are capable of self-recognition (Reiss and Marino, 2001), cooperation, andtool use (Krutzen et al., 2005). Moreover, they also havethe largest brain in the animal kingdom in absolutesize, but not in relation to body size [here expressed asencephalization quotient, EQ (Jerison, 1973)]. Odonto-cetes (toothed whales) possess above-average encephali-zation levels compared to other mammals, second onlyto humans, whereas the encephalization level of the

mysticete (baleen whales) is much lower, because of non-linearities in EQ for very large animals (Marino, 2002,2004). However, the large absolute size and high degreeof cortical gyrification show that the mysticete brain hasundergone substantial enlargement and elaboration dur-ing the course of evolution (Oelschlager and Oelschlager,2002).The cetacean brain differs from the terrestrial mam-

malian brain in many ways. It has a very high level ofgyrification, and, as the rest of the whale body, it pos-

*Correspondence to: Nina Eriksen, Research Laboratory forStereology and Neuroscience, University of Copenhagen Bispeb-jerg Hospital, Bispebjerg Bakka 23, DK-2400, Copenhagen NV,Denmark. E-mail: [email protected]

Grant sponsor: Stereology and EM Research Laboratory, Uni-versity of Aarhus, Denmark; The Augustinus Foundation.

Received 16 May 2006; Accepted 26 September 2006

DOI 10.1002/ar.a.20404Published online in Wiley InterScience(www.interscience.wiley.com).

� 2006 WILEY-LISS, INC.

THE ANATOMICAL RECORD 290:83–95 (2007)

sesses several traits that show adaptation to water. Theblowhole has migrated from the frontal to the parietalregion, which makes it easier for whales to breath atthe surface. This migration has changed the shape ofthe brain and the distribution of the cranial nerves(Oelschlager and Oelschlager, 2002). Cytoarchitecturalorganization does not resemble that of terrestrial mam-mals; cortical layer IV is absent or very poorly developedessentially guarantees that inputs and outputs and in-terneuronal connections are very different from othermammals (Glezer et al., 1988; Morgane and Glezer,1990). Furthermore, layer I is far more cellular, layer IIcontains atypical neurons, and layer III contains verylarge pyramidal neurons (Glezer, 2002; Hof et al., 2005).The cortical arrangement of functional areas has alsochanged compared to terrestrial mammals. Whereas theprimate brain contains large frontal lobes, the frontalregion in the dolphin brain is very modest (Morganeet al., 1980). Compared to primates, it displays its ownunique pattern of differentiation, but is distinctly lami-nated and comprises several cortical fields as in otherlobes (Hof et al., 2005). Electrophysiological mappingstudies have placed both the auditory and the visual cor-tices in the parietal region in dolphins and porpoises(Supin et al., 1978), whereas they are located in the tem-poral (auditory) and occipital (visual) regions in terres-trial mammals. The auditory region occupies broadareas of the suprasylvian gyrus, which adjoins the visualareas in the lateral gyrus and dorsal parietal regions.There is no intervening cortex between the auditoryareas and the visual areas, or between visual-auditoryareas and the sensorimotor areas (Glezer et al., 1988).Whether this is because cetaceans use sound as theirprimary communication channel is unknown. The audi-tory cortex is involved in elementary sound processingin mammals, and mammals therefore expectedly need acertain amount of neurons in the auditory cortex to beable to discriminate sound properly (Talwar et al., 2001).The auditory systems are smaller in mysticetes than inodontocetes, but the mysticete visual system containsmore axons than that of the odontocete (Oelschlager andOelschlager, 2002).Cetacea have a completely different evolutionary his-

tory compared to terrestrial mammals: they returned tothe aquatic environment about 50 million years ago(Gingerich et al., 1983). Both evolutionary lines haveculminated in large complex central nervous systemswith highly developed neocortices, and comparisonshould help to unravel some of the basic mechanismsessential for such convergent development. This investi-gation studies the mysticete neocortex; here we use thecommon Minke whale (Balaenoptera acutorostrata) as amodel of all mysticetes. The Minke whale is a small ba-leen whale and grows to about 7–9 m long, weighingabout 6–7.5 tonnes. Females are about 0.6 meter longerthan males.

Some measurements of cetacean neuronal density havebeen reported (Tower, 1954; Oelschlager and Oelschlager,2002), but no actual total cell numbers have previouslybeen estimated. Thus, our aim was to estimate the totalneocortical cell number, cortical volume, and cell densityin the common Minke whale in the entire neocortex andto estimate and compare the total cell number in the au-ditory cortex with that of the visual cortex using stereo-logical methods.

MATERIALS AND METHODS

Five brains from common Minke whales were used inthis study. Due to their length, they were all estimatedto be mature animals (Christensen, 1980, 1981). Theywere immersion-fixed in 10% formalin and kept in ourbrain bank for 1–2 years with origin from the BarentsSea in Norway. We used a single hemisphere from eachbrain, taking the best preserved from each specimencovering both sexes (Table 1).

Ethics

The brains were originally collected during commer-cial whaling, and CITES (Convention on InternationalTrade in Endangered Species) guidelines for importinganimal material were followed.

Cortical Mapping

It was assumed that the auditory and visual corticesof mysticetes follow the same structure as in odonto-cetes. Therefore, primary auditory and visual cortices(referred to as auditory and visual cortices) were de-lineated according to the mapping of primary cortices inbottlenose dolphins (Tursiops truncatus) (Morgane et al.,1990; Glezer, 2002; Oelschlager and Oelschlager, 2002)and the morphology of the balaenopterid brain (Breath-nach, 1955; Pilleri, 1966a, 1966b). In our definition, theauditory cortex is located at the suprasylvian gyrus,while the visual cortex is placed next to the auditory cor-tex on the lateral gyrus, as are the primary cortices inodontocetes. The deep end of the gyrus was used todelineate the anterior and posterior cortical borders. Thetwo subregions were delineated on the pial surface indifferent colors to distinguish the different regions afterembedding (Fig. 1A).

Stereological Design

A series of parallel sections was cut at 2.5 cm intervalsthrough the formalin-fixed hemisphere (Fig. 1B). Theunbiased Cavalieri principle of point counting was usedto estimate the shrinkage of the tissue area from formalin

TABLE 1. The material

Animals

Total length (cm) 802 780 771 756 678Sex Female Female Male Male MaleHemisphere intact Right Left Left Right LeftHemisphere weight (g) 1142 1079 1119 1033 974

84 ERIKSEN AND PAKKENBERG

Fig. 1. Tissue processing. A: On one hemisphere, the functionalcortical areas were delineated on the pial surface with ink, where blueindicates the auditory cortex, and red the visual cortex. B: The hemi-sphere was cut into 2.5 cm thick blocks that were C: embedded inparaffin and D: cut exhaustively into 40 mm thick coronal sections on

a Leica microtome using a wetted filter paper to allow collection ofthe section without the use of water baths. E: By gently pressing aprinting roller on the paper side with the section side down F: the sec-tion was then mounted on a microscope slide.

85TOTAL NEOCORTICAL CELL NUMBER

Fig. 2. The optical fractionator. A: Sections were sampled system-atically with a predetermined fraction, the section sampling fraction(ssf ), with a random start and stained with a modified Giemsa stain.B: Optical disectors were positioned systematically random on eachof the sections C: and cells were counted at final magnification of1,9003. Cells were counted when inside the counting frame and whenhitting the green inclusion line, providing they did not touch the red

exclusion line. The large counting frame was used for neurons and thesmall counting frame for glial cells. The area of the counting frame ofthe disector represents the area sampling fraction (asf) for the x,ysteps. D: Cell nuclei were counted by moving the counting framethrough the tissue in an optical plane inside the section. The height ofthe disector, h, to the tq-weighted section thickness represents theheight sampling fraction (hsf).

fixation to paraffin. The areas of the cut surfaces of theformalin-fixed sections (

Parea) were estimated using a

point grid, which has a known area associated with eachpoint, a(p). The sum of points, Pi, on each section fallingon the cut surface of the cerebrum was counted, and thearea of the cerebrum at that position estimated from

XArea ¼ aðpÞ �

XPi

The blocks were then dehydrated and embedded inparaffin in a LeicaASP300 tissue processor, and due totheir large size the blocks were cut in half (Fig. 1C). Thebrain was cut coronally into parallel sections of equalthickness of 40 mm using a Leica microtome, resulting ina total number of about 3,000 sections from each hemi-sphere. A wetted filter paper was placed on the paraffinblock allowing collection of the section without usingwater baths (Fig. 1D). When the section stuck to the fil-ter paper, it was mounted on a double-silane-coated mi-croscope slide by placing the paper with the section downon the slide, pressing gently on the paper side with aprinting roller (Fig. 1E and F). This resulted in a com-plete absence of artifacts stemming from tissue deforma-tion usually taking place in water baths, one consequencebeing that tissue section height is � 40 mm postprocess-ing. Using a random start within the sampling period, apredetermined fraction of these sections was systemati-cally sampled, dried for a minimum of 1 hr at 408C, andsubsequently stained with a modified Giemsa, whichstains neuron and glial cell bodies (Fig. 2A).Areas of the paraffin sections of the selected positions

were estimated again also using point counting, and theshrinkage was calculated from

Vshrinkage ¼ 1�P

AreaparaffinPAreaformalin

The shrinkage of the surface was less than the shrink-age of volume, since volume shrinks in three directions,whereas surface shrinks in only two directions. Surfaceshrinkage was calculated as

Sshrinkage ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiVshrinkage

3

q

Counting Procedure

A combination of two stereological principles, the opti-cal disector and the fractionator sampling design, theso-called optical fractionator method was applied (Gun-dersen, 1986). This technique was ideal for this studybecause it is less affected by the considerable and unpre-dictable shrinkage during fixation of the brain. The opti-cal fractionator method involves counting particles withoptical disectors in a systematic, uniform, random sam-ple that constitutes a known fraction of the structure tobe analyzed. This is achieved by counting cells on aknown fraction of sections (ssf; Fig. 2A), under a knownfraction of the sectional area of the region (asf; Fig. 2Band C) in a known fraction of the thickness of a section(hsf; Fig. 2D). The total neocortical cell number wasfound by multiplying the total number of counted particles,

PQ�, by the reciprocal sampling fractions, adding a

multiplication of 2 for bilateral number:

Ntotal ¼ 1

ssf� 1

asf� 1

hsf

XQ�

8>:9>;2

The optical disector, a 3D probe, was placed randomlyon the sections generated with the aid of a microscopeand an oil immersion objective, in which it was possible toobserve thin focal planes inside thick sections (Fig. 2B–D).A counting frame with exclusion and inclusion lines wassuperimposed on the magnified image of the tissue on amonitor (Fig. 2C), and the orientation in the z-axis wasmeasured with a digital microcator with a precision of0.5 mm. The purpose of the exclusion and inclusion linesof the counting frame is to exclude edge effects arisingfrom subsampling (Gundersen, 1977, 1978). Similarly,upper and lower guard zones protect the counting frameto prevent bias as a consequence of loss of cells close tothe section surfaces. All cells that came into focus withinthe counting frame were counted as the focal plane wasmoved through the section in a predetermined height, h(Fig. 2D). All cells were counted in a microscope arraywith a BX-50 Olympus microscope with a 603 oil-im-mersion objective (1,9003 magnification), a motorizedstage, a Heidenhain microcator, and a corresponding cam-era and computer running CAST-GRID software (Visio-pharm, Denmark).

Counting Criteria

Cells were identified as neurons if they had a clearlydefined nucleus with a pale cytoplasm and a dark cen-trally located nucleolus, including a relatively large sizeof the cell body (Fig. 3). The nucleolus was used as thecounting item, and the cell was counted only if thenucleolus was in focus inside the counting frame andthe disector height. Glial cells were defined as muchsmaller than neurons, without a clear identifiable nucle-olus and cytoplasm (Fig. 3). No differentiation was madebetween astrocytes, oligodendrocytes, or microglia. En-dothelial cells were easily recognized by their dark andelongated nucleus and excluded from all counts. Cellswere counted in all layers of cortex from the pial surfaceto the gray/white transition (Fig. 4). The neocorticalboundary from gray/white transition was determined bythe following method: presence of at least 15 neurons atmagnification ¼ 653 was considered to belong to neocor-tex. Layer I was always included in neocortex eventhough fewer than 15 neurons were present.

Sampling Fractions

To ensure that all parts of the neocortex were uni-formly sampled, the design was based on systematic uni-form random sampling (SURS). Based on a pilot study,the ssf, asf, and hsf in the z-axis were estimated andoptimized for statistical reasons to obtain a count ofapproximately 150–200 neurons and 150–200 glial cellsper sample, which previously has provided an optimalprecision compared to the biological variation (Pakken-berg and Gundersen, 1988, 1997; Korbo et al., 1990).


Section sampling fraction. Depending on the sizeof the brain, the ssf was chosen to be between 1/260th to1/290th to obtain 12–13 sections per brain. The first sec-tion was selected randomly using a random number

from 1–260 or 1–290, and the following sections weresampled systematically. In case of tissue artifacts due topreparation or cutting, the next section was sampledwithout altering the systematic sampling in the follow-ing sections.

Area sampling fraction. In each sampled section,neuron or glial cell counts were made with optical disec-tors at regular predetermined x,y positions in the neo-cortex. The first disector was positioned randomly overcortex within the x,y step pattern by the CAST-GRIDsoftware. The area of the counting frame, a(frame), ofthe disector was known relative to the area associatedwith each step in the x,y direction, a(x,y step). The areasampling fraction, asf, was calculated as

asf ¼ aðframeÞaðx; y� stepÞ

A small counting frame was used for glial cell counting,because of the high number of cells.

Height sampling fraction. The height of the disec-tor should be known relative to the section thickness. Inthis study, we applied guard zones of 5 mm at the topand around 14 mm at the bottom, and the fixed height,

Fig. 3. Minke whale brain cells. Note the large size differencebetween neurons (black arrow) and glial cells (red arrow), and the dis-tinct nucleolus in the neuron. Magnification ¼ 1,9003.

Fig. 4. Cytoarchitecture in Minke whale neocortex. A: Suprasylvian gyrus corresponding to primaryauditory cortex. B: Lateral gyrus corresponding to primary visual cortex. Roman letters indicate layers;wm, white matter. Magnification ¼ 653.


h, of the disector was 21 mm. To compensate for deforma-tion of the section thickness, hsf is equal to

hsf ¼ h�tQ�

for

�tQ� ¼PðtiqiÞPðqiÞ

where ti is the local section thickness centrally in the ithcounting frame with a disector count of qi

� (Dorph-Petersen et al., 2001). The stereological parameters usedin this study are shown in Table 2.

Volume and Surface Estimation

The systematic uniform random placements of the dis-ectors were also used to estimate neocortical volumes inaccordance to the Cavalieri estimator:

Vneocortex ¼X

P � aðpÞ � t � k

forP

P being the number of upper-corner points hittingthe neocortical tissue, a(p) is the x,y step area, t is thethickness of the section, and k is the inverse sectionsampling fraction. The volume was corrected for shrink-age (as previously described) to obtain the fixed volumeof the neocortex.Cortical surface area was estimated using a line-point

grid. The intersections between grid lines and the innerand outer surface of neocortex,

PI, were counted as well

as the number of grid points on each section overlyingneocortical tissue,

PP.

The surface of neocortex was then calculated from

Sneocortex ¼ Vneocortex2P

I

lðpÞ �PP

8>>:9>>;

where 2 is a constant, and l(p) is the unit test linelength per point.It was assumed that there was isotropy and no differ-

ential shrinkage in the surface; accordingly, the estima-tions of cortical thickness and cortical surface area arenot unbiased estimates.The thickness of cortex is estimated from the volume

and surface estimates of neocortex:

Statistical Analysis

The precision of the estimate of the total volume fromeach sample was estimated as the coefficient of error(CE). CE is a function of the noise effect, also knownas the point counting variance, and the SURS variancefor sums of areas,

Pa (Gundersen et al., 1999). The

noise effect is the uncertainty that comes from pointcounting,

PP:

Noise ¼ 0:0724 � bffiffiffia

p �ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffin �

XP

q

where n is the number of sections, b/Ha is the averageprofile shape (found by eyeballing the nomogram fromGundersen and Jensen, 1987).SURS variance for the sum of areas is the uncertainty

of sampling between sections, because repeated esti-mates based on different sections may vary. It was calcu-lated from

VARSURSP

a ¼ 3ðPi � Pi �NoiseÞ � 4ðPi � Piþ1 þ Pi � Piþ2Þ240

where Pi is the number of points counted on one section,and Piþ1 is the number of points counted on the nextsection (Gundersen et al., 1999). The total sampling var-iance, CE(

PP), is estimated from

CEX

P� �

¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiVARNOISE þ VARSURS

Pa

qP

P

The sampling is considered optimal when CE is abouthalf the coefficient of variation (CV ¼ SD/mean), sinceCV2 ¼ biological CV2 þ estimated CE2. Then the real bi-ological variability (biological CV2) contributes most tothe observed relative variance. In the estimation of CEin the optical fractionator counting particles, noise effectis equal to

PQ�.

A Student’s t-test was used to test for differencesbetween sexes in the neocortex, auditory and visual cor-tices, and for differences between auditory and visualcortex, applied with a significant level of 0.05. One-wayANOVA test was performed to test for differences indensity of cells between the different cortical regions.Spearman’s correlation coefficient was used to test forcorrelation between sex and brain size, and betweentotal body length and brain size.

TABLE 2. Stereological parameters

Stepsize

BA (mm) 1/ssfP

sect a(frame) (mm2) x,y (mm) 1/asfP

dis hdis (mm) tq� (mm) 1/hsfP

Q�

NeuronsNeocortex 40 306 11 4493 15000 50074.4 125 5–25 41.4 2.0 215Auditory cortex 40 270 11 4493 3600 2663.7 96 5–25 40.5 1.9 167Visual cortex 40 270 8 4493 2400 1553.5 106 5–25 40.2 1.9 177

Glial cellsNeocortex 40 306 11 670 15000 335820.9 125 5–25 41.4 2.0 247Auditory cortex 40 270 11 670 3600 19343.3 96 5–25 40.5 1.9 192Visual cortex 40 270 8 670 2400 8597 106 5–25 40.2 1.9 210

Tneocortex ¼ Vneocortex

Sneocortex


RESULTS

The neocortex of the Minke whale was thick (Table 3)and characterized by a thick layer I and a dense layer II.Layers III–VI are less distinguishable with large pyrami-dal neurons (Fig. 4). Overall, the Minke neocortex resem-bles that of other cetaceans. The gyrification level (¼ surfacearea/brainweight) of theMinkewhale was 2.2.

Cell Numbers

The mean neocortical neuron number in the commonMinke whale was 12.8 3 109 and the glial cell numberwas 98.2 3 109. For the auditory cortex, the total neuronnumber was 4.65 3 108 and the total glial cell numberwas 3.80 3 109; 2.28 3 108 neurons were found in thevisual cortex, whereas the total glial cell number wasequal to 1.74 3 109 (Table 3). The total number of cellsin each region (entire neocortex, auditory and visual cor-tices) for each individual as a function of its hemispheri-cal weight and total body length is shown in Figure 5.Other measurements of the mysticete neocortex, such astotal neocortical volume and cell density, are shown inTable 3. The mean percent shrinkage from formalin-

fixed brain tissue to paraffin was 50.5% and was used tocorrect for cortical volume and surface area shrinkage.Figure 6 shows comparison of different mammals and

their neocortical features, reporting only total numberor density obtained using stereological methods. Esti-mates have been obtained for the following: rat (Rattusnorvegicus) (Mooney and Napper, 2005), pig (Sus scrofadomisticus), Gottingen minipig (Sus scrofa gottingen)(Jelsing et al., 2006), rhesus monkey (Macaca mulatto;data not shown), and human (Homo sapiens) (Pakken-berg and Gundersen, 1997; Pelvig et al., 2003). Minkewhales have more neurons than small mammals, butless than humans (Fig. 6A), whereas they have moreglial cells (Fig. 6B). The density of neurons is lower inthe common Minke whale (Fig. 6C), but the glial celldensity is about the same as in humans, though lowerthan other mammals (Fig. 6D). The Minke neocorticalvolume is much higher than any of the other mammalslisted above (Fig. 6E). Figure 7 shows neocortical fea-tures of cetaceans, including fin whale (Balaenopteraphysalus) (Tower, 1954) and humpback whale (Mega-ptera novaeanligae) (Oelschlager and Oelschlager, 2002),bottlenose dolphin (Tursiops truncatus), harbor porpoise(Phocoena phocoena), common dolphin (Delphinus delphis)

TABLE 3. Major structural components of the Minke whale brain

Neocortex CE (CV) Auditory cortex CE (CV) Visual cortex CE (CV)

Mean neuron number, 109

F 14.0 0.06 (0.12) 0.52 0.08 (0.20) 0.17 0.08 (0.15)M 12.0 0.07 (0.22) 0.43 0.08 (0.41) 0.27 0.08 (0.10)All 12.8 0.07 (0.10) 0.47 0.08 (0.21) 0.23 0.08 (0.27)p-value 0.42 0.58 0.46

Mean glial cell number, 109

F 97.7 0.06 (0.27) 4.81 0.07 (0.08) 1.59 0.07 (0.17)M 98.6 0.07 (0.20) 3.12 0.08 (0.05) 1.84 0.09 (0.06)All 98.2 0.07 (0.17) 3.88 0.07 (0.25) 1.74 0.08 (0.14)p-value 0.68 *0.05 0.23

Mean density of neurons, 106/cm3

F 7.6 0.07 (0.19) 6.70 0.08 (0.20) 6.83 0.08 (0.16)M 8.3 0.07 (0.07) 9.63 0.08 (0.18) 11.08 0.08 (0.12)All 8.0 0.07 (0.11) 8.45 0.08 (0.27) 9.37 0.08 (0.26)p-value 0.45 0.20 *0.04

Mean density of glial cells, 106/cm3

F 53.3 0.06 (0.33) 6.28 0.07 (0.10) 6.31 0.07 (0.18)M 68.8 0.07 (0.16) 7.44 0.08 (0.21) 7.64 0.09 (0.03)All 62.6 0.07 (0.24) 6.98 0.07 (0.09) 7.11 0.08 (0.14)p-value 0.68 0.40 0.20

Mean volume, cm3

F 1857 0.04 (0.07) 76.96 0.04 (0.17) 25.17 0.04 (0.01)M 1466 0.05 (0.28) 43.42 0.07 (0.24) 24.07 0.06 (0.08)All 1622 0.05 (0.11) 56.90 0.06 (0.33) 24.51 0.05 (0.01)p-value 0.30 *0.05 0.50

Mean surface area, cm2

F 6563 0.05 (0.01) – –M 5479 0.04 (0.14) – –All 5912 0.05 (0.08) – –p-value 0.50

Mean cortical thickness, mmF 2.83 0.05 (0.01) – –M 2.75 0.04 (0.14) – –All 2.78 0.05 (0.08) – –p-value 0.80

Glial cell/neuron ratioAll 7.7/1 8.2/1 7.6/1

*All total quantities are bilateral. P-values are from the sexual dimorphism tests.aStatistically significant.


Fig. 5. Total neocortical cell number in the Minke whale. A: Neuron and glial cell number as a functionof hemisphere weight and total body length of the animal in the entire neocortex. B: Neuron and glial cellnumber as a function of hemisphere weight and total body length in the auditory cortex. C: Neuron andglial cell number as a function of hemisphere weight and total body length in the visual cortex.


(Ridgway and Brownson, 1984; Haug, 1987; Oelschlagerand Oelschlager, 2002), and Stenella genus (saddlebackand spinner dolphins) (Ridgway and Brownson, 1984). Itshould be noted that cetacean data are not directly com-parable with our data because of differences in tissueprocessing and measurements. The neocortical neuron

density is about the same for mysticetes, but higher insmall-toothed whales (Fig. 7A), whereas the glial cell den-sity is about the same (Fig. 7B). The surface areaincreases with increasing brain weight (Fig. 7C), and thegyrification level of neocortex in cetaceans is about thesame, whereas it is lower in humans (Fig. 7D).

Fig. 6. Comparison of neocortex in mammalian brain. A: Neocortical neuron number. B: Neocorticalglial cell number. Note that the larger the brain, the more glial cells. C: Neuron density. D: Glial cell den-sity of different mammals. E: Volume of neocortex.


Sexual Differences

Data were tested for sex differences, and brain weightwas correlated to sex (r ¼ 0.99), with females having thelarger brain, and total body length (r ¼ 0.7). All valuesfrom the following tests in the different cortical regionsare shown in Table 3.

Entire neocortex. No significant differences werefound in the entire neocortex, neither in cell number norin cell density or volume of neocortex.

Auditory cortex. Sexual differences were not foundin neuron number, but females had significantly moreglial cells than males. No significant differences werefound in cell density, but females had a significantlylarger volume of the auditory cortex than males.

Visual cortex. No significant differences were foundbetween sexes in the visual cortex in either total neuronnumber or glial cell number. Males had a significantlydifferent higher neuron density than females, but nodifferences were found in glial cell density or volume ofcortex.

Functional Cortices

No significant difference was seen in cell density inthe different cortices (neurons: P ¼ 0.68, glial cells: P ¼0.94). However, the auditory cortex had significantly

more cells than the visual cortex (neurons: P ¼ 0.01,glial cells: P ¼ 0.001). The auditory cortex also had thelargest glial cell-to-neuron cell ratio (Table 3).

DISCUSSION

The Minke whale neocortex has the same cytoarchitec-ture as other cetaceans (Glezer et al., 1988, 2002; Mor-gane and Glezer, 1990; Hof et al., 2005), and there wasno obvious difference in cytoarchitecture between pri-mary auditory and visual cortices. Not only is the Minkewhale neocortex highly gyrified, it is also thicker thanmost mammals, probably because the neocortical cellnumber is high, especially the glial cell number. The au-ditory cortex contains more cells than the visual cortex,but in this relatively small sample, there seems to be noobvious sexual dimorphism in the neocortex.The total neocortical cell number in the common

Minke whale was estimated to be 12.8 3 109 neuronsand 98.2 3 109 glia. It is approximately 2/3 of thehuman neuron number, but 13 times that of rhesusmonkeys and around 500 times that of rats.The Minke whale has the highest number of glial cells

in the neocortex seen in any mammal studied to date.The ratio of neocortical glial cells to neocortical neuronsis species-specific and therefore varies among the mam-malian groups and during ontogenesis due to changes in

Fig. 7. Comparison of neocortex in cetacean brain. A: Neuron density. B: Glial cell density. C: Surfacearea. D: Gyrification level in cetaceans and humans. Note that gyrification level is about the same in ceta-ceans, but lower in humans.


neuron density (Oelschlager and Oelschlager, 2002;Nishiyama et al., 2005). The glia/neuron ratio is 7.7/1 inMinke whales, 1.4/1 in humans, and 2/1 in rats. Fewratios have been reported for cetaceans: Tursiops � 3/1,fin whales � 5/1 (Oelschlager and Oelschlager, 2002),which shows that there is a tendency for glia/neuron ra-tio to increase with increasing brain mass. Conse-quently, the glia/neuron ratio signals the importance ofglia for growing neurons, and thus for neocortical func-tion, and they probably play a crucial role in cetaceansseen in the high ratio of glia. Since the Minke neocorti-cal neurons seem to be very large, it is also possible thatlarge neurons may need a higher number of glia thansmaller ones. Though the Minke whale possesses fewerneurons than humans, it still has more than other mam-mals. This, along with the very high number of glia,means that whales evolved a substantially larger num-ber of cells in their neocortex than other nonhumanmammals, even larger than lower primates such as therhesus monkey. This could possibly be an adaptation tomaintenance and control of large bodies as well as a con-sequence of a complex social system or due to theaquatic environment, as suggested for odontocetes byMarino et al. (2005).The Minke whale density of neurons in the neocortex

is lower than in other mammals, and neuron densitydeclines with increasing brain size, as was earlierhypothesized (Tower, 1954; Machail, 1982; Haug, 1987).Since neurons need axonal connectivity to neurons inother parts of the brain, neuron density cannot exceedbelow a certain value. In Figure 7A, it is shown that theneuron density in Minke whales is about the same as infin whales, which are twice as large. Therefore, it is pos-sible that the lower limit for neuron density is around60–85 3 106/cm3, at least for larger cetaceans. The glialcell density, however, was earlier thought to be inde-pendent of brain mass (Haug, 1987), but as is shown inFigures 6D and 7B, it seems to be fairly stable around60–80 3 106/cm3, disregarding the rat.Prothero and Sundsten (1984) hypothesized that there

is an upper limit for brain mass, and as the brain massincreases, so does the cortical surface, resulting in an in-crease in gyrification (gyral-window hypothesis). Hence,an increase in brain mass and cortical surface is onlypossible by increasing the cortical fissures and thicken-ing the neocortex. The Minke neocortex is thicker(2.78 mm) than most mammalians’, including that ofodontocetes (Tursiops 1.2–1.76 mm) (Morgane et al.,1980; Ridgway and Brownson, 1984), but it is about thesame thickness as the human neocortex (2.63 mm) (Pak-kenberg and Gundersen, 1997). This does not supportthe gyral-window hypothesis, as a large brain would beexpected to have a thicker cortex than a smaller brain.It is seemingly important not to increase cortical thick-ness above a certain limit. If volume grows and corticalthickness is kept stable, cortical surface must thenincrease in area. Therefore, not surprisingly, as brainsize increases, so does neocortical volume, with increaseof surface area and cortical fissures in the large cetaceanbrain. The Minke neocortex is highly gyrified; the levelof gyrification is about the same in cetaceans, with atendency for dolphins to be a bit larger, but it is higherthan in humans. That part of the gyral-window hypothe-sis holds for the cetacean brain; nevertheless, it mightalso be an aquatic trait instead of only a ‘‘large brain’’ trait.

The auditory cortex contained more cells and had alarger volume than the visual, and the highest glia/neu-ron ratio was seen in the auditory cortex. This is notsurprising as cetaceans are much more dependent onsound than on vision, as the aquatic environment haspoor visibility. They use sound as their primary commu-nication channel; the aquatic environment is very con-ductive to sound: sound travels about five times faster inwater than in air (Urick, 1973). Minke whales, like allmysticetes, are assumed to use sound for communication(Winn and Perkins, 1971; Mellinger et al., 2000). To-gether with other balaenopterids (fin, blue, and hump-back whales), they use sequences of sounds in a hier-archical organization in which individual utterances areproduced in a regular pattern that is repeated at regularintervals. Possibly, the mysticete auditory structure isrelatively complex compared to other mammals, whichare less dependent on sound communication. However,we only measured the primary auditory cortex, which isonly 3.5% of the entire neocortex. Possibly there areother neocortical areas of higher-level integrative proc-essing that employ information from the primary audi-tory cortex. Since Minke whales do not echolocate, as doodontocetes, their auditory cortex is most likely lessdeveloped than would be expected of the odontocete au-ditory cortex. Mysticetes do use their vision to a greaterextent than odontocetes (Oelschlager and Oelschlager,2002), which means that they may have a more complexvisual system. However, in a recent study, Poth et al.(2005) found decreasing neuron number per neocortexunit (the number of perikarya below a defined area ofcortex) with increasing brain mass in sensory neocorti-ces of delphinids, which seem to be equally reliable onaudition. More knowledge on visual and auditory struc-tures is needed to address this topic.As mysticetes have reverse sexual dimorphism, it is

unsurprising that the female brain is also larger; how-ever, it is surprising that female Minkes do not possessmore brain cells than males despite their larger brainsize. This is in contrast to humans, where males havelarger brains and more neurons than females (Pakken-berg and Gundersen, 1997). Additionally, there was nosexual dimorphism in cell density, volume, or thicknessof the Minke neocortex. There was, however, some sex-ual dimorphism in the functional areas of the neocortex,since females had a larger volume of auditory cortex andmore glia, and in the visual cortex males had a largerneuron density. The larger volume of auditory cortex infemales is most likely because of the larger brain size.The higher neocortical neuron number in males in thevisual cortex compared to females is most probably aresult of the low sample size. Because of the high biolog-ical variation, all of these findings need to be replicatedin a larger sample.In conclusion, the Minke whale neocortex is complex;

it has more neocortical neurons than other mammals,but fewer than humans, despite its much larger bodysize. Minkes possess many more glial cells in their neo-cortex than do other mammals. They have a large neo-cortical volume and surface area, with a neuron densityas that of larger mysticetes, but less than other mam-mals, including small odontocetes. There was no sexualdimorphism in either the neocortex or the functionalareas. The auditory cortex is larger than the visual cortexand contains more cells, as expected from the acoustic


behavior of the Minke, possibly because of an adaptation tothe aquatic environment. The evidence of considerablecomplexity in the mysticetes’ neocortex is consistent withtheir behavioral and social complexity.

LITERATURE CITED

Breathnach AS. 1955. The surface structures of the humpbackwhale brain. J Anat 89:343.

Christensen I. 1980. Catch and effort in Norwegian Minke whale fish-ery in the 1978 whaling season. Rep Int Whal Comm 30:209–212.

Christensen I. 1981. Age determination of Minke whales, Balaenop-tera acutorostrata, from laminated structures in tympanic bullae.Rep Int Whal Comm 31:245–253.

Dorph-Petersen KA, Nyengaard JR, Gundersen HJG. 2001. Tissueshrinkage and unbiased stereological estimation of particle num-ber and size. J Microsc 204:232–246.

Gingerich PD, Wells NA, Russel DE, Ibrahim Shah SM. 1983. Ori-gins of whales in epicontinental remnant seas: new evidence fromthe Eocene of Pakistan. Science 220:403–406.

Glezer II, Morgane PJ, Jacobs MS. 1988. Implications of the ‘‘initialbrain’’ concept for the brain evolution in Cetaceans. Behav BrainSci 11:75–116.

Glezer II. 2002. Neural morphology. In: Hoezel R, editor. Marine mam-mal biology: an evolutionary approach.Oxford: Blackwell. p 98–115.

Gundersen HJG. 1977. Notes on the estimation of the numericaldensity of arbitrary profiles: The edge effect. J Microsc 111:219–223.

Gundersen HJG. 1978. Estimators of the number of objects per areaunbiased by edge effects. Microsc Acta 81:107–117.

Gundersen HJG. 1986. Stereology of arbitrary particles: a review ofunbiased number and size estimators and the presentation of somenew ones, in memory of William R. Thompson. J Microsc 143:3–45.

Gundersen HJG, Jensen EB. 1987. The efficiency of systematic sam-pling in stereology and its prediction. J Microsc 147:229–263.

Gundersen HJG, Jensen EB, Kieu KL, Nielsen J. 1999. The effi-ciency of systematic sampling in stereology reconsidered. J Microsc193:199–211.

Haug H. 1987. Brain sizes, surfaces, and neuronal sizes of the cor-tex cerebri: a stereological investigation of man and his variabili-ty and a comparison with some mammals (primates, whales, mar-supials, insectivores and one elephant). Am J Anat 180:126–142.

Hof PR, Chanis R, Marino L. 2005. Cortical complexity in cetaceanbrain. Anat Rec 287:1142–1152.

Jelsing J, Nielsen R, Olsen AK, Grand N, Hemmingsen R, Pakken-berg B. 2006. The postnatal development of neocortical neuronsand glial cells of the Gottingen minipig and the domestic pigbrain. J Exp Biol 209:1454–1462.

Jerison HJ. 1973. Evolution of the brain and intelligence. New York:Academic Press.

Jerison HJ. 1985. Animal intelligence as encephalization. Phil TransR Soc B 308:21.

Korbo L, Pakkenberg B, Ladefoged O, Gundersen HJG, Arlien-Søborg P, Pakkenberg H. 1990. An efficient method for estimatingthe total number of neurons in rat brain cortex. J Neurosci Methods30:93–100.

Krutzen M, Mann J, Heithaus MR, Connor RC, Bejder L, SherwinWB. 2005. Cultural transmission of tool use in bottlenose dolphins.Proc Natl Acad Sci USA 102:8939–8943.

Macphail E. 1982. Brain and intelligence in vertebrates. Oxford:Clarendon Press.

Marino L. 2002. Brain size evolution. In: Perrin WF, Wursig B, The-wissen JGM, editors. Encyclopedia of marine mammals. SanDiego, CA: Academic Press. p 158–162.

Marino L. 2004. Cetacean brain evolution: multiplication generatescomplexity. Int J Comp Psychol 17:1–16.

Marino L, Uhen MD, McShea DW. 2005. Encephalization in odonto-cetes: what’s being aquatic got to do with it? Akron, OH: FourthTriennial Convention on Evolution on Aquatic Tetrapods. p 50.

Mellinger DK, Carson C, Clark CW. 2000. Characteristics of Minkewhale (Balaenoptera acutorostrata) pulse trains recorded nearPuerto Rico. Mar Mam Sci 16:739–756.

Mooney SM, Napper RM. 2005. Early postnatal exposure to alcoholreduces the number of neurons in the occipital but not the parie-tal cortex of the rat. Alcohol Clin Exp Res 29:683–691.

Morgane PJ, Jacobs MS, McFarland WL. 1980. The anatomy of thebrain of the bottlenose dolphin (Tursiops truncates): surface con-figurations of the telencephalon of the bottlenose dolphin withcomparative anatomical observation sin four other cetacean spe-cies. Brain Res Bull 5(Suppl 3):1–107.

Morgane PJ, Glezer II. 1990. Sensory neocortex in dolphin brain.In: Thomas JA, Kastelein RA, editors. Sensory abilities of ceta-ceans: laboratory and field evidence. New York: Plenum Press.p 101–137.

Morgane PJ, Glezer II, Jacobs MS. 1990. Comparative and evolution-ary anatomy of the visual cortex of the dolphin. In: Jones EG, PetersA, editors.Cerebral cortex, vol. 8B, comparative structure and evolu-tion of cerebral cortex, part 2. New York: Plenum Press. p 215–258.

Nishiyama A, Yang Z, Butt A. 2005. Astrocytes and NG2-glia:what’s in a name? J Anat 207:687–693.

Oelschlager HHA, Oelschlager JS. 2002. Brain. In: Perrin WF,Wursig B, Thewissen JGM, editors. Encyclopedia of marine mam-mals. San Diego, CA: Academic Press. p 133–158.

Pakkenberg B, Gundersen HJG. 1988. Total number of neurons andglial cells in human brain nuclei estimated by the disector andthe fractionator. J Microsc 150:1–20.

Pakkenberg B, Gundersen HJG. 1997. Neocortical neuron numberin humans: effect of sex and age. J Comp Neurol 384:312–320.

Payne K, Payne RS. 1985. Large scale changes over 19 years insongs of humpback whales in Bermuda. Zietschrift Tierpsych 68:89–114.

Pelvig DP, Pakkenberg H, Regeur L, Oster S, Pakkenberg B. 2003.Neocortical glial cell number in Alzheimer’s disease. Dement Ger-iatr Cogn Disord 16:212–219.

Pilleri G. 1966a. Morphologie des Gerhirnes des Buckelwhals, Meg-aptera novaeangliae Borowski (Cetacea, Mysticeti, Baleopteridae).Experienta 22:849–851.

Pilleri G. 1966b. Morphologie des Gerhirnes des Seiwals, Balenop-tera borealis Lesson (Cetacea, Mysticeti, Baleopteridae). J Hirn-forschung 8:437–491.

Poth C, Fung C, Gunturkun O, Ridgway SH, Oelschlager HHA.2005. Neuron numbers in sensory cortices of five delphinids com-pared to a physeterid, the pygmy sperm whale. Brain Res Bull66:357–360.

Prothero JW, Sundsten JW. 1984. Folding of the cerebral cortex inmammals: a scaling model. Brain Behav Evol 24:152–167.

Reiss D, Marino L. 2001. Self-recognition in the bottlenose dolphin:a case of cognitive convergence. Proc Natl Acad Sci USA 98:5937–5942.

Rendall L, Whitehead H. 2001. Culture in whales and dolphins.Behav Brain Sci 24:309–382.

Ridgway SH, Brownson RH. 1984. Relative brain sizes and corticalsurface areas in odontocetes. Acta Zool Fennica 172:125–149.

Supin AY, Mukhametov LM, Ladygina TF, Popov VV, Mass AM, Pol-yakova IG. 1978. Electrophysiological studies of the dolphin’sbrain. In: Sokolor RE, editor, Izdatel’stro Nauka, Moscow, pp 7–85.

Talwar SK, Musial PG, Gerstein GL. 2001. Role of mammalian au-ditory cortex in the perception of elementary sound properties.J Neurophysiol 85:2350–2358.

Tower DB. 1954. Structural and functional organizations of mam-malian cerebral cortex: the correlation of neuron density withbrain size. Cortical neuron density in the fin-whale (Balaenopteraphysalus L.) with a note on the cortical neuron density in the In-dian elephant. J Comp Neurol 101:19–51.

Urick J. 1973. Principals of underwater sounds. New York: McGraw-Hill.

Winn HE, Perkins PJ. 1971. Distribution and sound of the Minkewhale, with a review of mysticete sounds. Cetology 19:1–12.


Total neocortical cell number in the mysticete brain

Documents

Transcript of Total neocortical cell number in the mysticete brain