R E S EA R C H A R T I C L E
The Cellular Composition of the Marsupial Neocortex
Adele M.H. Seelke,1 James C. Dooley,1 and Leah A. Krubitzer1,2*
1
2
Center for Neuroscience, University of California, Davis, Davis, California, 95618
Department of Psychology, University of California, Davis, Davis, California, 95618
ABSTRACT
In the current investigation we examined the number
and proportion of neuronal and non-neuronal cells in
the primary sensory areas of the neocortex of a South
American marsupial, the short-tailed opossum (Monodelphis domestica). The primary somatosensory (S1),
auditory (A1), and visual (V1) areas were dissected
from the cortical sheet and compared with each other
and the remaining neocortex using the isotropic fractionator technique. We found that although the overall
sizes of V1, S1, A1, and the remaining cortical regions
differed from each other, these divisions of the neocortex contained the same number of neurons, but the
remaining cortex contained significantly more nonneurons than the primary sensory regions. In addition,
the percent of neurons was higher in A1 than in the
remaining cortex and the cortex as a whole. These
results are similar to those seen in non-human primates. Furthermore, these results indicate that in some
respects, such as number of neurons, the neocortex is
homogenous across its extent, whereas in other
aspects of organization, such as non-neuronal number
and percentage of neurons, there is non-uniformity.
Whereas the overall pattern of neuronal distribution is
similar between short-tailed opossums and eutherian
mammals, short-tailed opossum have a much lower cellular and neuronal density than other eutherian mammals. This suggests that the high neuronal density
cortices of mammals such as rodents and primates
may be a more recently evolved characteristic that is
restricted to eutherians, and likely contributes to the
complex behaviors we see in modern mammals.
J. Comp. Neurol. 522:2286–2298, 2014.
C 2014 Wiley Periodicals, Inc.
V
INDEXING TERMS: evolution; Monodelphis; isotropic fractionation
The six-layered neocortex is a general feature of the
mammalian brain in most (but not all) mammals, and
has been observed and studied in species as diverse as
platypus, capybaras, and humans (DeFelipe et al., 2002;
Hutsler et al., 2005; Krubitzer et al., 1995). One of the
major functions of the neocortex is to process and integrate sensory signals coming from sensory receptor
arrays in the skin, muscles, joints, ears, and eyes to
effect context-appropriate behavior. In all mammals
examined, these specific sensory modalities have at
least one neocortical area that contains a map of the
sensory receptor array, and is defined by dense myelination, a koniocellular layer 4, and a homologous pattern
of thalamocortical connections (Kaas, 1983; Krubitzer,
2009). However, these primary sensory areas can also
vary in a number of parameters including relative size,
connectivity, and their number of sublaminae, to name a
few. Although these traditional views of the cortical field
have become textbook knowledge, important questions
regarding the cellular composition of the neocortex and
the evolution of basic processing circuitry persist.
C 2014 Wiley Periodicals, Inc.
V
2286
The first question centers on the extent to which the
neocortex has a basic composition of neurons and glial
cells that is ubiquitous across its extent and across
species. This question was first addressed by Rockel
and colleagues in 1980. They posit (with the exception
of area 17) that independent of cortical thickness, laminar specialization, or function, the absolute number of
cells is the same across the cortical sheet regardless of
the cortical field in question. Furthermore, they argue
that this number is constant regardless of brain size or
species. Although subsequent studies seem to refute
this appealing hypothesis (Haug, 1987; HerculanoHouzel et al., 2008; Prothero, 1997), a recent study
suggests that this early supposition is correct and that
Grant sponsor: National Institutes of Health; Grant number: F32
NS064792 (to A.M.H.S.), R21 NS071225 and R01 EY022987 (to
L.A.K.), and T32 EY015387 (to J.C.D.).
*CORRESPONDENCE TO: Leah Krubitzer, Center for Neuroscience,
1544 Newton Ct., Davis, CA 95616. E-mail: lakrubitzer@ucdavis.edu
Received October 1, 2013; Revised November 22, 2013;
Accepted January 7, 2014.
DOI 10.1002/cne.23534
Published online January 11, 2014 in Wiley Online
(wileyonlinelibrary.com)
The Journal of Comparative Neurology | Research in Systems Neuroscience 522:2286–2298 (2014)
Library
Cellular composition of the marsupial neocortex
other studies that contest this idea suffered from methodological or quantification problems (Carlo and Stevens, 2013).
The second question addresses the evolution of the
basic circuitry of the neocortex and seeks to uncover
both the rules of construction as well as the constraints
imposed on evolving brains. Although fossil records provide information on the size of the brain and gross morphological characteristics of the neocortex, the only
way to appreciate the cortical networks that were present in early mammals and the types of cellular and systems level changes that have been made to these
networks is to perform a comparative analysis. These
types of studies reveal both fundamental features of
processing as well as derivations that generate the
remarkable diversity in behavior observed in extant
species.
Unfortunately, most studies that address these questions of both basic cortical composition and evolution
only consider a few species of eutherian mammals
such as monkeys, cats, and rats (or mice). As a result,
there are gaping holes in our knowledge of two major
branches of mammals, monotremes and marsupials, the
latter of which provides a better reflection of the ancestral state more than the commonly used eutherian models (Frost et al., 2000; Kaas, 2011; Karlen and
Krubitzer, 2007). In the present investigation we utilized
the isotropic fractionator method to examine the cellular composition of the neocortex of a marsupial, the
South American short-tailed opossum, Monodelphis
domestica. Like other mammals, the opossum has a
six-layered cortex and primary sensory areas that can
be clearly differentiated by their architectonic appearance, functional organization, and neuroanatomical connections (Catania et al., 2000; Kahn et al., 2000; Karlen
et al., 2006; Saunders et al., 1989). Furthermore,
because of their dense myelination, primary fields can
be visualized in raw cortical tissue that is properly illuminated, and these areas can then be carefully dissected from the rest of the cortex (Fig. 1). In this
experiment we dissected the neocortex into the three
primary sensory areas, auditory (A1), somatosensory
(S1), and visual (V1) cortices, as well as the remaining
cortical areas and determined the number and density
Abbreviations
A1
AF 647/700
DAPI
NeuN
PBS
Rem Ctx
S1
V1
RCtx
primary auditory cortex
AlexaFluor 647/700
40 ,6-diamidino-2-phenylindole
neuronal nuclear protein
phosphate-buffered saline
remaining cortical areas
primary somatosensory cortex
primary visual cortex
sum of V1, A1, S1, and Rem Ctx
of neurons and non-neurons, as well as the percentage
of neurons within both the entire neocortical hemisphere and a given structure.
MATERIALS AND METHODS
As is the case with most methodologies, the isotropic
fractionator technique has both costs and benefits
associated with it, and we have addressed these points
previously (Seelke et al., 2013).
The isotropic fractionation procedure consists of multiple stages. First, tissue is dissected into major structures. Next, tissue is processed, which includes
homogenization, 40 ,6-diamidino-2-phenylindole (DAPI)
staining and NeuN immunohistochemistry. The third
stage involves quantifying the number of DAPI-labeled
nuclei within a sample, and the fourth stage involves
determining the proportion of NeuN-labeled nuclei
within that same sample. Finally, in the last stage we
use these values to calculate the total number of cells,
total number of neurons, total number of non-neurons,
cell density, neuronal density, and non-neuronal density.
A number of cell types fall under the grouping of “nonneuronal cells,” including endothelial, mesothelial, ependymal, and glial cells. Endothelial cells form the thin lining of blood vessels and compose the blood–brain
barrier, mesothelial cells comprise the pia mater, and
ependymal cells line the ventricles, and of these nonneuronal cell types, the glia are most prevalent (Morest
and Silver, 2003; Temple, 2001). Thus, for the purposes
of this study we will consider the non-neuronal cells to
be predominantly glial in nature.
Subjects
Five adult South American short-tailed opossums
(Monodelphis domestica) were used in these experiments (see Table 1 for ages, weights, and sexes). Subjects were born and raised in the Psychology
Department Vivarium at the University of California,
Davis. Animals were housed in standard laboratory
cages with ad libitum access to food and water. All animals were maintained on a 14-hour light/dark cycle
with the lights on at 7 AM. All experiments were performed under National Institutes of Health guidelines
for the care of animals in research and were approved
by the Institutional Animal Care and Use Committee of
the University of California, Davis.
Tissue dissection
Animals were euthanized with an overdose of sodium
pentobarbital (Beuthanasia; 250 mg/kg) and transcardially perfused with phosphate-buffered saline (PBS) followed by 4% paraformaldehyde. The brain was
The Journal of Comparative Neurology | Research in Systems Neuroscience
2287
A.M.H. Seelke et al.
primary sensory fields
were visualized by placing
the tissue on a light box.
This back-illuminated tissue was then dissected
into the primary sensory
fields, V1, A1, S1, and the
remaining cortex. These
regions were photographed
and weighed, and then
placed in 5% paraformaldehyde for storage.
Tissue processing
Samples were prepared
as described previously
(Campi et al., 2011; Seelke
et al., 2013). Briefly, tissue
was homogenized in a 15ml glass KONTES* Tenbroek tissue grinder (Kimble Chase, Vineland, NJ)
with Triton X-100 and
sodium citrate in distilled
water. This process broke
down cell membranes to
produce a suspension of
isolated nuclei. The samples were centrifuged and
resuspended in a solution
of PBS and DAPI. In some
cases dissected tissue was
stored in fixative for more
than 4 weeks. This tissue
was homogenized and suspended in a boric acid
Figure 1. Dissection of the opossum brain for isotropic fractionation. A,B: The whole brain (A) is separated into the left and right cerebral hemispheres, the cerebellum, and subcortical structures
solution then placed in an
(including the midbrain, thalamus, hypothalamus, and brainstem; B). C: The cerebral hemispheres are
oven at 70 C for 1 hour
further dissected, removing the hippocampus and basal ganglia, until only the neocortex remains (left
for epitope retrieval. In all
image). The darker, more densely myelinated regions correspond to the primary sensory areas (right
cases a subsample of the
image). D: The primary sensory areas can be clearly seen on section of flattened cortical tissue that
main
suspension
was
has been stained for myelin. A1, primary auditory cortex; S1, somatosensory cortex; V1, visual cortex;
stained for neuronal nuclei
Rem Ctx, remaining cortex. Scale bar 5 5 mm in A (applies to A,B); 1 mm in C,D.
using immunocytochemical
extracted, photographed, weighed, and dissected; the
techniques with the anti-NeuN antibody (Millipore, Bedtwo cortical hemispheres, the subcortical structures,
ford, MA). Alexa Fluor 647 or Alexa Fluor 700 goat antiand the cerebellum were separated (Fig. 1). The neomouse IgG secondary antibody (Invitrogen, Carlsbad,
cortex was isolated by removing the hippocampus,
CA) was used to fluorescently visualize NeuN-labeled
basal ganglia, pyriform cortex (defined as all tissue latnuclei.
eral to the rhinal sulcus, including the amygdala), and
olfactory bulbs from both cerebral hemispheres. In
Antibody characterization
each case, one neocortical hemisphere was kept intact
The NeuN antibody (NEUronal Nuclei; clone A60)
and the other neocortical hemisphere was dissected
specifically recognizes the DNA-binding, neuron-specific
into primary sensory fields. The densely myelinated
protein NeuN, which is present in most central and
2288
The Journal of Comparative Neurology | Research in Systems Neuroscience
Cellular composition of the marsupial neocortex
TABLE 1.
Characteristics of the Study Subjects
Case no.
Age (days)
Weight (g)
11–151
11–152
11–153
11–155
11–243
696
610
476
511
429
148
121
107
134
109
TABLE 2.
Antibody Used in This Study
Sex
M
F
F
M
M
peripheral nervous system neuronal cell types of all vertebrates tested. In a western blot analysis, this antibody recognized two to three bands in the 46–48-kDa
range and possibly another band at approximately 66
kDa (adapted from product information). Because NeuN
specifically stains neuronal nuclei, staining of nonneuronal tissue was used as a negative control (see Table 2
for details).
Antigen
NeuN
Immunogen
Maunfacturer,
species, mono- vs.
polyclonal,
cat. no.
Purified cell nuclei
Millipore (Billerica, MA),
from mouse brain
mouse monoclonal,
#MAB377
Dilution
1:300
of neuronal to non-neuronal nuclei was estimated from
this gated population.
Equations
Estimates of cellular composition for a given cortical
region were derived from the following equations.
total nuclei 5 ½ðnumber of DAPI 1 nucleiÞ
Nuclei quantification
For cell counting, samples were vortexed, and 10lL aliquots were immediately loaded into a Neubauer
cell-counting chamber (Labor Optik, Bad Homburg,
Germany) and placed on a fluorescence microscope
for visualization and counting of nuclei. Standard stereological protocols were used (Mouton, 2002). DAPIlabeled nuclei within 10 distinct 8 square by 8
square sections of the Neubauer chamber were
counted (for details, see Campi et al., 2011; Seelke
et al., 2013). The mean number of DAPI1 nuclei in
each 8 3 8 section was then calculated, and was
later used to calculate the total number of cells
within a given sample.
Determining NeuN1 percent
To determine the ratio of neuronal to non-neuronal
nuclei within a sample, a flow cytometer was used (UC
Davis Flow Cytometry Shared Resource Center). This
allowed us to automate the detection and counting of
neuronal and non-neuronal nuclei in a faster and more
reliable manner than visual inspection under a fluorescent microscope (Collins et al., 2010b). The proportion
of neuronal nuclei was quantified by using a Becton
Dickinson (San Jose, CA) 5-Laser LSRII flow cytometer.
Specific lasers were used to excite DAPI-positive nuclei
(50 mW, 405 nm) and Alexa Fluor 647- and Alexa Fluor
700–labeled nuclei (50 mW, 635 nm). For all samples,
1,000–10,000 DAPI-positive nuclei were evaluated for
Alexa Fluor 647 and Alexa Fluor 700 label. Samples
that were run on the flow cytometer were forced
through a 35-lm mesh cell filter, and then vortexed
and immediately taken into the LSRII. Selection gates
were determined by a flow cytometry expert who was
blind to the cortical areas of the samples, and the ratio
= volume of suspension counted in mm3
3 total suspension volume in cm3 3 1; 000
percent neurons 5 ðnumber of NeuN 1 nucleiÞ
=ðnumber of DAPI 1 nucleiÞ
total neurons 5 percent neurons 3 total nuclei
total non-neurons 5 total nuclei 2 total neurons
cell density 5 number of cells=weight of structure
neuron density 5 number of neurons=weight of structure
non-neuron density 5 number of non-neurons
=weight of structure
Analysis
In each case, one neocortical hemisphere was left
intact and the other was dissected into the primary
sensory fields and remaining cortical areas. The intact
neocortical hemisphere was compared against the
summed values obtained from the dissected neocortical
hemisphere to ensure consistency across samples. The
weights of these regions were compared by using analysis of variance (ANOVA; JMP; SAS, Cary, NC), as were
differences in the % neurons, total number of cells, total
number of neurons, total number of non-neurons, cell
density, neuronal density, and non-neuronal density. Differences between specific regions were determined by
using Student’s t-tests. For all tests, alpha 5 0.05.
RESULTS
In the following results we dissected different portions
of the cortical sheet (Fig. 1) and quantified the cellular
composition of the whole neocortical sheet, the primary
sensory regions of the neocortex and the remaining cortex. We compared numbers, density and percentage of
all cells, neurons and non-neurons, within a cortical field
as well as across cortical fields. To ensure the reliability
The Journal of Comparative Neurology | Research in Systems Neuroscience
2289
A.M.H. Seelke et al.
TABLE 3.
Cortical Field Weights
Area
Whole neocortex
R neocortex
Rem Ctx
V1
S1
A1
Weight (g)
% of Rneocortex
0.073 6 0.003
0.072 6 0.003
0.039 6 0.003
0.015 6 0.002
0.011 6 0.001
0.007 6 0.001
54.1 6 2.5
20.7 6 2.3
15.3 6 1.1
9.8 6 1.2
For abbreviations, see list.
summed neocortex displayed nearly identical values
(RCtx 5 0.072 6 0.003 g). Together, the primary sensory fields comprised approximately half of the weight
of the neocortex (V1 5 0.015 6 0.002 g; A1 5 0.007 6
0.001 g; S1 5 0.011 6 0.001 g) with the balance consisting of the remaining cortex (0.039 6 0.003 g; Fig.
2A). In terms of size of the different divisions of the
neocortex, the remaining cortex was the largest and
weighed significantly more than V1 and S1, and V1
weighed significantly more than A1 (which was the
smallest field examined). The weight of S1 did not differ
from V1 and A1 (F5,29 5 173.49, P < 0.0001; Fig. 2A).
Similarly, the largest proportion (percentage) of the
neocortex was comprised of the Rem Ctx, which was
significantly larger than V1, which was in turn significantly larger than A1. The proportion of neocortex
devoted to S1 significantly differed from Rem Ctx, but
not V1 and A1 (F3,19 5 110.86, P < 0.0001; Fig. 2B).
Figure 2. A: The weight (in grams) of the whole neocortex, the
primary sensory areas, and the remaining cortical areas. The
weight of the intact neocortical sheet is equal to the sum of the
weight of V1, S1, A1, and Rem Ctx. B: The percentage of neocortex comprised by the primary sensory areas and the remaining
cortical areas. Mean 6 SEM. Values with different letters are significantly different. A1, primary auditory cortex; S1, somatosensory cortex; V1, visual cortex; Rem Ctx, remaining cortex.
of these results, we compared the values obtained from
intact neocortical hemispheres with the summed values
for the primary sensory regions and remaining cortical
regions, which we identify as the summed neocortex.
Animal information can be found in Table 1.
Cortical field weights
We first compared the weights of the intact neocortical hemisphere (neocortex), the summed weight of the
dissected neocortical hemisphere (RCtx), and the individual cortical fields, including the A1, S1, and V1 cortices, and the Rem Ctx (Fig. 2). The intact neocortical
hemisphere was small and weighed 0.073 g, with little
variability across animals (6 0.003 g; Table 3), and the
2290
Cellular composition
One intact neocortical hemisphere contained
3.03 6 0.21 million cells, and the RCtx contained
3.02 6 0.21 million cells (Table 3). V1, S1, and A1 contained 0.57 6 0.09 million cells, 0.50 6 0.03 million
cells, and 0.30 6 0.03 million cells, respectively, and
Rem Ctx contained 1.66 6 0.18 million cells. The total
number of cells significantly differed across cortical
regions (F5,29 5 73.53, P < 0.0001; Fig. 3A). The number
of cells in the intact neocortex and RCtx did not differ
from each other. The Rem Ctx contained more cells than
V1, S1, and A1. However, there was no significant difference between the numbers of cells in V1, S1, and A1.
We next determined the proportion of neurons contained within each cortical region. The intact neocortex
contained 25.6 6 4.9% neurons, and the RCtx contained
28.4 6 6.4% neurons (Table 4). The Rem Ctx consisted of
16.6 6 6.2% neurons, and V1, S1, and A1 contained
38.7 6 11.2%, 43.2 6 12.4%, and 60.9 6 11.5%, respectively. There was a significant difference between the proportion of neurons in different cortical regions
(F5,29 5 2.86, P < 0.05; Fig. 3B). Whereas the percent neurons did not differ between V1, S1 and the remaining
The Journal of Comparative Neurology | Research in Systems Neuroscience
Cellular composition of the marsupial neocortex
Figure 3. The cellular composition of the intact neocortical hemisphere (neocortex; gray), summed neocortical hemisphere (RCtx; white), and the primary sensory and remaining cortical regions (Rem Ctx,
V1, S1, A1; black). A: The total number of cells in millions. The number of cells varies with the size of
each cortical region, with larger regions having more cells and smaller regions having fewer cells. The
number of cells in the intact neocortical sheet is equal to the sum of the number of cells in V1, S1,
A1, and Rem Ctx. B: The percentage of neurons in the entire neocortex and each cortical region. In
general, the primary sensory regions contain a higher proportion of neurons than the remaining cortical
areas. The intact neocortical sheet contains the same proportion of neurons as the weighted sum of
V1, S1, A1, and Rem Ctx. C: The total number of neurons in millions. Despite their smaller size, the primary sensory areas contain the same number of neurons as the remaining cortical regions. The number of neurons in the intact neocortical sheet is equal to the sum of the number of neurons in V1, S1,
A1, and Rem Ctx. D: The total number of non-neuronal cells in millions. The primary sensory regions
contain significantly fewer non-neuronal cells than the remaining neocortical regions. The number of
non-neuronal cells in the intact neocortical sheet is equal to the sum of the number of non-neuronal
cells in V1, S1, A1, and Rem Ctx. Mean 6 SEM. Values with different letters are significantly different.
A1, primary auditory cortex; S1, somatosensory cortex; V1, visual cortex; Rem Ctx, remaining cortex.
cortex, the percent neurons in A1 was significantly higher
than in the Rem Ctx as well as RCtx and the intact neocortical hemisphere.
By multiplying the total number of cells by the percentage of neurons within a structure, we determined
the total number of neurons within a structure The
intact neocortex contained 0.80 6 0.20 million neurons
and
RCtx
contained
0.88 6 0.22 million neurons
(Table 4). The remaining
cortex contained 0.25 6
0.07 million neurons, and
V1, S1, and A1 contained
0.25 6 0.08 million neurons, 0.21 6 0.07 million
neurons, and 0.18 6 0.04
million neurons, respectively. The total numbers
of neurons in V1, A1, S1,
and the Rem Ctx did not
significantly differ from
each other (Fig. 3C).
The total number of
non-neurons within a cortical region was determined by subtracting the
total number of neurons
from the total number of
cells. The intact neocortex
contained 2.22 6 0.12 million non-neuronal cells and
RCtx contained 2.14 6 0.22
million non-neuronal cells
(Table 4). The remaining cortex contained 1.41 6 0.21
million non-neuronal cells.
V1, S1, and A1 contained
0.34 6 0.08 million, 0.28 6
0.07 million, and 0.11 6
0.03 million non-neuronal
cells, respectively. The total
number of non-neuronal
cells significantly differed
between cortical regions
(F5,29 5 46.64, P < 0.0001;
Fig. 3D). The Rem Ctx contained more non-neuronal
cells than V1, S1, and A1.
However, there was no significant difference between
the number of nonneuronal cells in V1, S1,
and A1.
Cellular density
Cellular density was determined by dividing the total
number of cells in a given cortical structure by the
weight of the given cortical structure. The cellular density of the intact neocortical hemisphere was
41.70 6 2.07 million cells/g of tissue, and the cellular
The Journal of Comparative Neurology | Research in Systems Neuroscience
2291
A.M.H. Seelke et al.
TABLE 4.
Proportion of Neurons Contained Within Each Cortical Region
Area
No. of cells
(in millions)
% Neurons
No. of neurons
(in millions)
No. of non-neurons
(in millions)
Whole neocortex
R neocortex
Rem Ctx
V1
S1
A1
3.03 6 0.21
3.02 6 0.21
1.66 6 0.18
0.57 6 0.09
0.50 6 0.03
0.30 6 0.03
25.6 6 4.9
28.4 6 6.4
16.6 6 6.2
38.7 6 11.2
43.2 6 12.4
60.9 6 11.5
0.80 6 0.20
0.88 6 0.22
0.25 6 0.07
0.23 6 0.08
0.21 6 0.07
0.18 6 0.04
2.22 6 0.12
2.14 6 0.22
1.41 6 0.21
0.34 6 0.08
0.28 6 0.07
0.11 6 0.03
For abbreviations, see list.
TABLE 5.
Cellular Density
Area
Whole
neocortex
R neocortex
Rem Ctx
V1
S1
A1
Rem Ctx as well as RCtx and the intact neocortical
hemisphere.
Cells/g
(in millions)
Neurons/g
(in millions)
Non-neurons/g
(in millions)
41.70 6 2.07
10.92 6 2.54
30.78 6 1.68
42.39 6 3.01
42.52 6 2.42
40.98 6 8.13
46.34 6 4.77
44.04 6 4.44
12.28 6 2.89
6.73 6 2.21
17.31 6 6.32
20.29 6 7.66
28.05 6 5.76
30.11 6 3.36
35.79 6 3.97
23.68 6 5.84
26.05 6 7.28
15.99 6 3.15
For abbreviations, see list.
density of the RCtx was the same (42.39 6 3.01 million
cells/g of tissue; Table 5). The cellular densities of the
Rem Ctx, V1, S1, and A1 did not significantly differ
from each other (F5,29 5 0.17, P 5 NS; Fig. 4A).
Neuronal density was calculated by dividing the
total number of neurons in a given cortical structure
by the weight of that structure. As with the total
number of cells, the neuronal density of the intact
neocortical hemisphere was not significantly different
from RCtx (Table 5). In addition, there were no significant differences in the neuronal density of the Rem
Ctx, or the primary sensory regions, V1, S1, and A1
(Table 5). Whereas there was no significant difference
between cortical regions (F5,29 5 2.30, P 5 0.076; Fig.
4B), a preplanned comparison indicated that A1 had
a significantly higher neuronal density than the Rem
Ctx as well as RCtx and the intact neocortical
hemisphere.
The density of non-neuronal cells was determined by
dividing the number of non-neuronal cells in a given
cortical region by the weight of a given cortical region.
The non-neuronal density of the intact neocortical hemisphere was 30.78 6 1.68 million cells/g, as was the
density of the RCtx (Table 5). There was no significant
difference in the non-neuronal density of the Rem Ctx,
V1, S1, and A1. Whereas there was no significant difference between cortical regions (F5,29 5 2.21, P 5 0.086;
Fig. 4C), a preplanned comparison indicated that A1
had a significantly lower non-neuronal density than the
2292
DISCUSSION
In the following discussion we provide comparative
evidence indicating that there is a non-uniformity in the
cellular composition of the neocortex within and across
species. This is not surprising, because our own and other
laboratories have used multiple criteria to subdivide the
neocortex in a variety of species and have found similar
features of organization as well as clear heterogeneity in
structure, function, and connectivity. What is extraordinary is that despite years of debate, there is still no consensus on this fundamental issue in neuroscience. In
1980, Rockel, Hiorns, and Powell used stereological techniques to count the absolute number of cells in a specific
volume of tissue in the brains of rats, cats, humans, and
several non-human primates. These investigators sampled
six cortical regions, including the frontal, parietal, temporal, motor, and somatosensory areas, as well as area 17,
which is coextensive with the primary visual area. They
found that, with the exception of area 17 in primates, the
number of cells did not differ between cortical areas or
mammalian species. The thickness of cortical layers did
vary between species, which led to the conclusion that
cells were more densely packed in smaller brains than in
larger brains. These results (excluding the area 17 analysis) were recently replicated by Carlo and Stevens
(2013), and are shown in Figure 5C.
Although the data from the original study of Rockel
et al. (1980) are intriguing, they did not provide a thorough description of their counting methods. A larger
issue, and one that is inherent in many comparative
studies, is the accurate and consistent identification of
cortical field boundaries within a species, and making
valid comparisons of homologous cortical fields across
species. Unfortunately, this crucial piece of data was
lacking in Rockel et al. (1980), so it is difficult to make
valid comparisons with our own, or other modern studies that examine the cellular composition of the
The Journal of Comparative Neurology | Research in Systems Neuroscience
Cellular composition of the marsupial neocortex
neocortex. As described above, the only cortical region
they explicitly identified was area 17, which is readily
identified with a variety of techniques in most, if not all
mammals examined. Furthermore, area 17 contained
2.5 times the number of neurons as any other cortical
region. These results comport with recent findings in
primates, mice, and now opossums, which show that
non-primary and association regions contain a smaller
number of neurons than primary sensory areas (Collins
et al., 2010a; Herculano-Houzel et al., 2008, 2013).
This important issue of accurately defining cortical
field boundaries within and across species is raised in
the more recent study by Carlo and Stevens (2013).
However their resolution of this issue is a post hoc statistical analysis rather than a more direct anatomical
method of cortical field segregation. Their analysis
assumes that the composition of a given cortical area
will be homogenous, and any variation between counting columns will be normally distributed. They took multiple samples from a given cortical region and
calculated the variance of those samples. They then
compared the observed variance with a predicted variance distribution. If counting columns with nonhomogenous properties were grouped together, the
observed variance would be greater than the predicted
variance. Because, in all cases, the distribution of the
predicted and observed variance matched, Carlo and
Stevens concluded that their identification of cortical
areas was correct. Ultimately, regardless of the method
by which areal boundaries were confirmed, the important point is that cortical areas be accurately and consistently defined both within and across species.
There have been other studies that used similar stereological methods to examine differences in neuronal
density across the cortical sheet; however, counter to
the studies described above, these studies report that
the neocortex does not exhibit uniform neuronal density
(Beaulieu and Colonnier, 1989; Charvet et al., 2013;
Figure 4. The cellular density of the intact neocortical hemisphere (neocortex; gray), summed neocortical hemisphere (RCtx;
white), and the primary sensory and remaining cortical regions
(Rem Ctx, V1, S1, A1; black). A: The cellular density of each cortical region, in millions of cells per gram of tissue. The total cellular density does not vary across different cortical regions. The
cellular density of the intact neocortical sheet is equal to the cellular density of the summed neocortical regions. B: The neuronal
density of each cortical region, in millions of cells per gram of tissue. Although there is not a significant difference in neuronal
density across cortical regions, the data suggest that the primary
sensory regions contain a higher density of neurons than remaining cortical regions. The neuronal density of the intact neocortical
sheet is equal to the neuronal density of the summed neocortical
regions. C: The non-neuronal density of each cortical region, in
millions of cells per gram of tissue. Although there is not a significant difference in non-neuronal density across cortical regions,
the data suggest that the primary sensory regions contain a lower
density of non-neuronal cells than remaining cortical regions. The
non-neuronal density of the intact neocortical sheet is equal to
the non-neuronal density of the summed neocortical regions.
Mean 6 SEM. Values with different letters are significantly different. A1, primary auditory cortex; S1, somatosensory cortex; V1,
visual cortex; Rem Ctx, remaining cortex.
The Journal of Comparative Neurology | Research in Systems Neuroscience
2293
A.M.H. Seelke et al.
Collins, 2011; Collins et al., 2010a; Herculano-Houzel
et al., 2013; Leuba and Garey, 1989; Ribeiro et al.,
2013; Schuz and Palm, 1989). Although they used different methodologies, ranging from traditional stereology (Beaulieu and Colonnier, 1989; Charvet et al.,
2013; Leuba and Garey, 1989; Schuz and Palm, 1989)
to isotropic fractionation (Collins et al., 2010a;
Herculano-Houzel et al., 2013; Ribeiro et al., 2013), and
examined different species, including mice (HerculanoHouzel et al., 2013; Schuz and Palm, 1989), cats
(Beaulieu and Colonnier, 1989), non-human primates
(Charvet et al., 2013; Collins et al., 2010a), and
humans (Leuba and Garey, 1989; Ribeiro et al., 2013),
each of these studies reached the same general conclu-
sion: cellular composition varies between different cortical regions. Significantly, each of these studies also
found that the primary sensory areas (especially V1)
had a greater neuronal density than nonprimary sensory
areas.
Recently, the isotropic fractionator technique has
been used to investigate the cellular composition of
large heterogeneous brain regions, but to date only two
other studies have examined differences in neuronal
density in different portions of the cortical sheet. Collins and colleagues (2010a) examined the number of
total cells, neurons, and neuronal density in the neocortex of four primate species including galagos, owl monkeys, macaques, and baboons. In all cases they found
a great deal of variation in the number and density of
neurons across the cortex, and in all cases the neuronal density was greatest in visual areas, followed by S1
and A1, and lowest in the other cortical areas. Similarly,
Herculano-Houzel and colleagues (2013) examined the
distribution of neurons across the cerebral cortex of
the mouse. They found that, much like in primates, visual areas exhibited the highest neuronal density, followed by sensory areas and remaining cortical regions.
Figure 5. Comparative studies of cortical cellular composition. A:
Changes in the neuron–glia ratio across the cortical sheet. The
number of neurons in a specific cortical region was divided by
the number of glia (or non-neurons) in that same region. In primates and Monodelphis the neuron–glia ratio was higher in the primary sensory areas than in remaining cortical areas, indicating
that the primary sensory areas have a larger number of neurons
that are more densely packed than the remaining cortical areas.
Within the primary sensory areas, however, the neuron–glia ratio
varies between primates and Monodelphis. In all of the primates
examined, the ratio is highest in V1 and lower in S1 and A1, but
in Monodelphis primary sensory regions the glia–neuron ratio is
highest in A1 and lowest in V1. This indicates that the distribution of neurons, and possibly the overall organization and function
of the neocortex, fundamentally differs between primates and
Monodelphis. B: The number of neurons in both cortical hemispheres versus the weight of both cortical hemispheres in different primates (gray circles), insectivores (white squares), rodents
(black diamonds), and Monodelphis (black star). Strikingly, Monodelphis does not appear to conform to the patterns of the other
species, instead showing a lower than expected number of cortical neurons for its cortical weight. C: Data adapted from Carlo
and Stevens (2012) showing the number of neurons under 1
mm2 of cortical surface as a function of cortical thickness. Neuron counts were taken from mice (diamonds), rats (black
squares), cats (triangles), and monkeys (gray circles), and the
mean for all data points, represented by the dashed line, is
97,780 neurons per mm2. Carlo and Stevens claim that these
data show that the neuronal composition of the cortex does not
vary between species, although the exact anatomical location
from which each sample was taken was not provided. Data
adapted from Carlo and Stevens, (2013), Collins et al. (2010b),
Herculano-Houzel et al. (2006, 2011), and Sarko et al. (2009).
2294
The Journal of Comparative Neurology | Research in Systems Neuroscience
Cellular composition of the marsupial neocortex
Interestingly, the data presented in the present study
indicate that the conclusion of homogeneity versus heterogeneity depends on the metric examined. For example,
we saw no difference in cellular density or the total number of neurons in the primary versus nonprimary areas of
cortex. However, there were fewer non-neurons in primary areas, and a greater neuron/glia cell ratio in primary
areas (particularly A1) in opossums compared with the
remaining cortex (Fig. 5A). Furthermore, A1 had a larger
percentage of neurons as well as a greater neuronal density, and a similar trend was observed in V1 and S1.
Comparative analysis of neuron number and
density across species
In addition to similarities and differences across the
cortical sheet within a species, different species also
show tremendous variability in neocortical cellular composition (Figs. 5B, 6). For example, the combined
weight of the cerebral hemispheres in the short-tailed
opossum (0.15 g) is similar to that of the mouse (0.17
g), naked mole rat (0.18 g), and short-tailed shrew
(0.18 g; Fig 6B) (Herculano-Houzel et al., 2011; Sarko
et al., 2009). However, the total number of cells in both
hemispheres is much lower in the short-tailed opossum
(6 million) than in the mouse (25.8 million), shorttailed shrew (25 million), and naked mole rat (14.5 million; Fig. 6E). Thus, the absolute number of cells (both
neurons and non-neurons) is different in animals with
comparably sized neocortices.
In terms of cellular density, the short-tailed opossum
neocortex has an overall cellular density of 42 million
cells/g, and 11 million neurons/g (Table 5, Fig. 4A,B).
In contrast, the mouse neocortex has 149 million cells/
g, and 79 million neurons/g, the short-tailed shrew neocortex has 139 million cells/g, and 59 million neurons/
g, and the naked mole rat neocortex has 79 million
cells/g, and 33 million neurons/g (Fig. 6F). Thus, by all
measures the short-tailed opossum has a lower number
of cells, lower cellular density, lower proportion of neurons, and higher glia-to-neuron ratio than would be
expected for an animal with a comparably sized neocortex (Fig. 5B).
In addition to differences in cellular composition of
the neocortex, there are radical differences in the relative size of the neocortex across species. Although the
combined weight of both neocortical hemispheres is
similar in short-tailed opossums, mice, naked mole rats,
and short-tailed shrews, the proportion of the brain
comprised by the neocortex is different in different
species. In short-tailed opossums, the combined
neocortical hemispheres assume 16% of the entire brain
(Seelke et al., 2013), 43% in mice, 46% in naked mole
rates, and 48% in short-tailed shrew (Fig. 6C) (Hercu-
lano-Houzel et al., 2011; Sarko et al., 2009). Thus,
despite a similar overall brain size, both the proportion
of the brain assumed by the neocortex and the number
and composition of cells are different for different species. It has been argued that there are within-order consistencies in cellular composition for rodents,
insectivores, and primates (Herculano-Houzel et al.,
2006, 2007, 2011; Sarko et al., 2009); however,
dramatic differences in cortical sheet size, relative size
of cortical fields, and cellular composition are observed
between orders.
It should be noted that each study described here
isolated the cortex in a slightly different manner. We
removed the olfactory bulb, pyriform cortex, and hippocampus to isolate the neocortex. Sarko and her collaborators (2009) excluded the hippocampus and olfactory
bulb but included the pyriform cortex in their neocortical analysis, and Herculano-Houzel and colleagues
(2011) included everything caudal to the olfactory tract,
including the pyriform cortex and hippocampus. However, these methodological differences do not substantially change the overall conclusion that short-tailed
opossums’ neocortex contains fewer total cells and
fewer neurons, and has a lower cellular and neuronal
density and a lower proportion of neurons than other
similarly sized animals.
The present study is the most quantitative measure
of the number of cortical neurons in a marsupial species to date, and is in agreement with previous observations suggesting that marsupials (including short-tailed
opossums) exhibit a low density of cortical neurons
compared with other mammals, as well as a lower proportion of neurons, despite a prolonged period of cell
division (Cheung et al., 2010; Haug, 1987; Nudo et al.,
1995; Saunders et al., 1989). Although this would suggest that short-tailed opossums have a prolonged
period of gliogenesis compared with the eutherian
mammals studied, short-tailed opossums also have a
low number and density of non-neuronal cells compared
with other mammals (Collins et al., 2010a; HerculanoHouzel et al., 2011; Sarko et al., 2009). This prolonged
period of cell division could be due to a number of factors such as a slower rate of cell division, fewer numbers of cells that re-enter the cell cycle, reduced
numbers of intermediate progenitor cells, or some other
feature of cell cycle kinetics that may be different in
marsupials than in eutherian mammals.
The lower number of neurons and glia, as well as the
smaller proportion of neurons observed in opossums
indicates that the metabolic requirements of the marsupial cortex are significantly lower than those of their
eutherian counterparts (Attwell and Laughlin, 2001;
Belanger et al., 2011; Magistretti, 2006). For example,
The Journal of Comparative Neurology | Research in Systems Neuroscience
2295
A.M.H. Seelke et al.
Figure 6. The cellular composition in small mammals with similarly sized cortices. A: Side views of the brains of four small mammals: the
short-tailed opossum, mouse, naked mole rat, and short-tailed shrew. In each brain the region studied is shaded in gray. B,C: Although
the cortices are all of a similar size (B), the short-tailed opossum neocortex comprises less of the brain than the cortices of the eutherian
species (C). D–F: The short-tailed opossum has a lower proportion of cortical neurons (D) and fewer total cells (E) than the mouse, naked
mole rat, and short-tailed shrew. The short-tailed opossum accordingly has a lower cellular density (black) and neuronal density (white)
than the mouse, naked mole rat, and short-tailed shrew (F). Mouse and naked mole rat data were adapted from Herculano-Houzel et al.
(2011), and short-tailed shrew data were adapted from Sarko et al. (2009). Scale bar 5 2 mm in A.
a single rat cortical neuron consumes 3.42 3 108 molecules of ATP each second to maintain its resting
potential, whereas a glial cell consumes 1.02 3 108
molecules of ATP each second (Attwell and Laughlin,
2001). When we apply these numbers to a mouse
(Herculano-Houzel et al., 2011), which is a eutherian
mammal that has a neocortex of a similar size to that
of short-tailed opossums, we find that the neurons and
glial cells within the mouse cortex require a total of
59.1 3 1014 molecules of ATP per second (46.8 3
1014 for neurons and 12.3 3 1014 for glial cells). In
contrast, the neurons and glial cells within the opossum
cortex only consume a total of 5.0 3 1014 molecules
of ATP per second (2.74 3 1014 for neurons and 2.26
3 1014 for glial cells), less than 10% of the metabolic
requirement of the mouse cortex. This massive difference is due to both the lower number of total cells and
the lower proportion of neurons found within the cortex,
and clearly has important implications for neural processing and synaptic transmission (Seelke et al., 2013).
If the short-tailed opossum is an accurate reflection of
the ancestral state, these data suggest that the neocortex of early mammals was relatively smaller and contained many fewer neurons and relatively more glial cells
2296
than modern eutherian mammals. Furthermore, these
data imply that both temporal and mechanical aspects
of cortical development have been altered in eutherians.
The notion that early mammals had brains that
required significantly less energy is intriguing. Early
monotremes radiated from the ancestral mammalian
branch between 166 and 240 million years ago, and
marsupials radiated somewhat later (between 148 and
180 million years ago; (Bininda-Emonds et al., 2007;
Cifelli and Davis, 2003; Grutzner et al., 2003; Murphy
et al., 2004). At these times the atmospheric oxygen levels were significantly lower and carbon dioxide levels
were significantly higher than those found today (Berner,
2006; Rothman, 2002). Under these conditions animals
that consumed less oxygen due to a lower metabolic
rate would have a competitive advantage. Similarly, animals with a lower metabolic rate would require less food
to maintain the body’s basic functions. In fact, monotremes have a lower metabolic rate than marsupials,
which have a lower metabolic rate than eutherian mammals (Bennett, 1988). This trait would be particularly
adaptive in areas that contain a low availability of food
resources. Over the course of time atmospheric oxygen
levels increased and resources became more plentiful.
The Journal of Comparative Neurology | Research in Systems Neuroscience
Cellular composition of the marsupial neocortex
During this period the early eutherians underwent a massive evolutionary radiation (Archibald, 2003), and some
of these new species evolved higher metabolic rates,
which allowed for the expansion of a metabolically
expensive structure such as the neocortex. This in turn
allowed for a larger repertoire of complex and likely
highly adaptive behaviors.
ACKNOWLEDGMENTS
Thanks to Carol Oxford for her assistance at the UC
Davis Flow Cytometry Shared Resource. Thanks also to
Cindy Clayton, DVM, and the rest of the animal care staff
at the UC Davis Psychology Department Vivarium.
CONFLICT OF INTEREST STATEMENT
The authors have no conflicts of interest.
ROLE OF AUTHORS
All authors had full access to all of the data in the study
and take responsibility for the integrity of the data and the
accuracy of the data analysis. Study concept and design:
AMHS, JCD, LAK. Acquisition of data: AMHS. Analysis and
interpretation of data: AMHS. Drafting of the manuscript:
AMHS, LAK. Critical revision of the manuscript for important
intellectual content: AMHS, JCD, LAK. Statistical analysis:
AMHS. Obtained funding: LAK. Administrative, technical,
and material support: JCD. Study supervision: LAK.
LITERATURE CITED
Archibald JD. 2003. Timing and biogeography of the eutherian
radiation: fossils and molecules compared. Mol Phylogenet Evol 28:350–359.
Attwell D, Laughlin SB. 2001. An energy budget for signaling
in the grey matter of the brain. J Cereb Blood Flow
Metab 21:1133–1145.
Beaulieu C, Colonnier M. 1989. Number of neurons in individual laminae of areas 3B, 4 gamma, and 6a alpha of the
cat cerebral cortex: a comparison with major visual
areas. J Comp Neurol 279:228–234.
Belanger M, Allaman I, Magistretti PJ. 2011. Brain energy
metabolism: focus on astrocyte-neuron metabolic cooperation. Cell Metab 14:724–738.
Bennett AF. 1988. Structural and functional determinates of
metabolic rate. Am Zool 28:699–708.
Berner RA. 2006. GEOCARBSULF: a combined model for Phanerozoic atmospheric O2 and CO2. Geochim Cosmochim
Acta 70:5653–5664.
Bininda-Emonds OR, Cardillo M, Jones KE, MacPhee RD, Beck
RM, Grenyer R, Price SA, Vos RA, Gittleman JL, Purvis A.
2007. The delayed rise of present-day mammals. Nature
446:507–512.
Campi KL, Collins CE, Todd WD, Kaas J, Krubitzer L. 2011.
Comparison of area 17 cellular composition in laboratory
and wild-caught rats including diurnal and nocturnal species. Brain Behav Evol 77:116–130.
Carlo CN, Stevens CF. 2013. Structural uniformity of neocortex, revisited. Proc Natl Acad Sci U S A 110:1488–1493.
Catania KC, Jain N, Franca JG, Volchan E, Kaas JH. 2000. The
organization of somatosensory cortex in the short-tailed
opossum (Monodelphis domestica). Somatosens Motor
Res 17:39–51.
Charvet CJ, Cahalane DJ, Finlay BL. 2013. Systematic, crosscortex variation in neuron numbers in rodents and primates. Cereb Cortex. doi: 10.1093/cercor/bht214.
Cheung AF, Kondo S, Abdel-Mannan O, Chodroff RA, Sirey
TM, Bluy LE, Webber N, DeProto J, Karlen SJ, Krubitzer L,
Stolp HB, Saunders NR, Molnar Z. 2010. The subventricular zone is the developmental milestone of a 6-layered
neocortex: comparisons in metatherian and eutherian
mammals. Cereb Cortex 20:1071–1081.
Cifelli RL, Davis BM. 2003. Paleontology. Marsupial origins.
Science 302:1899–1900.
Collins CE. 2011. Variability in neuron densities across the
cortical sheet in primates. Brain Behav Evol 78:37–50.
Collins CE, Airey DC, Young NA, Leitch DB, Kaas JH. 2010a.
Neuron densities vary across and within cortical areas in
primates. Proc Natl Acad Sci U S A 107:15927–15932.
Collins CE, Young NA, Flaherty DK, Airey DC, Kaas JH. 2010b.
A rapid and reliable method of counting neurons and
other cells in brain tissue: a comparison of flow cytometry and manual counting methods. Front Neuroanat 4:5.
DeFelipe J, Alonso-Nanclares L, Arellano JI. 2002. Microstructure of the neocortex: comparative aspects. J Neurocytol
31:299–316.
Frost SB, Milliken GW, Plautz EJ, Masterton RB, Nudo RJ.
2000. Somatosensory and motor representations in cerebral cortex of a primitive mammal (Monodelphis domestica): a window into the early evolution of sensorimotor
cortex. J Comp Neurol 421:29–51.
Grutzner F, Deakin J, Rens W, El-Mogharbel N, Marshall
Graves JA. 2003. The monotreme genome: a patchwork
of reptile, mammal and unique features? Comp Biochem
Physiology A 136:867–881.
Haug H. 1987. Brain sizes, surfaces, and neuronal sizes of
the cortex cerebri: a stereological investigation of man
and his variability and a comparison with some mammals
(primates, whales, marsupials, insectivores, and one elephant). Am J Anat 180:126–142.
Herculano-Houzel S, Mota B, Lent R. 2006. Cellular scaling
rules for rodent brains. Proc Natl Acad Sci U S A 103:
12138–12143.
Herculano-Houzel S, Collins CE, Wong P, Kaas JH. 2007. Cellular scaling rules for primate brains. Proc Natl Acad Sci
U S A 104:3562–3567.
Herculano-Houzel S, Collins CE, Wong P, Kaas JH, Lent R.
2008. The basic nonuniformity of the cerebral cortex.
Proc Natl Acad Sci U S A 105:12593–12598.
Herculano-Houzel S, Ribeiro P, Campos L, Valotta da Silva A,
Torres LB, Catania KC, Kaas JH. 2011. Updated neuronal
scaling rules for the brains of Glires (rodents/lagomorphs). Brain Behav Evol 78:302–314.
Herculano-Houzel S, Watson C, Paxinos G. 2013. Distribution
of neurons in functional areas of the mouse cerebral cortex reveals quantitatively different cortical zones. Front
Neuroanat 7:35.
Hutsler JJ, Lee DG, Porter KK. 2005. Comparative analysis of cortical layering and supragranular layer enlargement in rodent
carnivore and primate species. Brain Res 1052:71–81.
Kaas JH. 1983. What, if anything, is S1? Organization of first
somatosensory area of the cortex. Physiol Rev 63:206–
231.
Kaas JH. 2011. Reconstructing the areal organization of the
neocortex of the first mammals. Brain Behav Evol 78:7–
21.
Kahn DM, Huffman KJ, Krubitzer L. 2000. Organization and
connections of V1 in Monodelphis domestica. J Comp
Neurol 428:337–354.
The Journal of Comparative Neurology | Research in Systems Neuroscience
2297
A.M.H. Seelke et al.
Karlen SJ, Krubitzer L. 2007. The functional and anatomical
organization of marsupial neocortex: evidence for parallel
evolution across mammals. Prog Neurobiol 82:122–141.
Karlen SJ, Kahn DM, Krubitzer L. 2006. Early blindness results
in abnormal corticocortical and thalamocortical connections. Neuroscience 142:843–858.
Krubitzer L. 2009. In search of a unifying theory of complex
brain evolution. Ann N Y Acad Sci 1156:44–67.
Krubitzer L, Manger P, Pettigrew J, Calford M. 1995. Organization of somatosensory cortex in monotremes: in search
of the prototypical plan. J Comp Neurol 351:261–306.
Leuba G, Garey LJ. 1989. Comparison of neuronal and glial
numerical density in primary and secondary visual cortex
of man. Exp Brain Res 7:31–38.
Magistretti PJ. 2006. Neuron-glia metabolic coupling and plasticity. J Exp Biol 209:2304–2311.
Morest DK, Silver J. 2003. Precursors of neurons, neuroglia,
and ependymal cells in the CNS: what are they? Where
are they from? How do they get where they are going?
Glia 43:6–18.
Mouton PR. 2002. Principles and practices of unbiased stereology: an introduction for bioscientists. Baltimore, MD:
Johns Hopkins University Press.
Murphy WJ, Pevzner PA, O’Brien SJ. 2004. Mammalian phylogenomics comes of age. Trends Genet 20:631–639.
Nudo RJ, Sutherland DP, Masterton RB. 1995. Variation and
evolution of mammalian corticospinal somata with special reference to primates. J Comp Neurol 358:181–205.
2298
Prothero J. 1997. Scaling of cortical neuron density and white
matter volume in mammals. J Hirnforsch 38:513–524.
Ribeiro PF, Ventura-Antunes L, Gabi M, Mota B, Grinberg LT,
Farfel JM, Ferretti-Rebustini RE, Leite RE, Filho WJ,
Herculano-Houzel S. 2013. The human cerebral cortex is
neither one nor many: neuronal distribution reveals two
quantitatively different zones in the gray matter, three in
the white matter, and explains local variations in cortical
folding. Front Neuroanat 7:28.
Rockel AJ, Hiorns RW, Powell TP. 1980. The basic uniformity
in structure of the neocortex. Brain 103:221–244.
Rothman DH. 2002. Atmospheric carbon dioxide levels for the
last 500 million years. Proc Natl Acad Sci U S A 99:
4167–4171.
Sarko DK, Catania KC, Leitch DB, Kaas JH, Herculano-Houzel
S. 2009. Cellular scaling rules of insectivore brains.
Front Neuroanat 3:8.
Saunders NR, Adam E, Reader M, Mollgard K. 1989. Monodelphis domestica (grey short-tailed opossum): an accessible model for studies of early neocortical development.
Anat Embryol 180:227–236.
Schuz A, Palm G. 1989. Density of neurons and synapses in the
cerebral cortex of the mouse. J Comp Neurol 286:442–455.
Seelke AMH, Dooley JC, Krubitzer L. 2013. Differential
changes in the cellular composition of the developing
marsupial brain. J Comp Neurol 52:2602–2620.
Temple S. 2001. The development of neural stem cells.
Nature 414:112–117.
The Journal of Comparative Neurology | Research in Systems Neuroscience