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Neocortical and hippocampal neuron and glial cell numbers in the rhesus monkey.

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THE ANATOMICAL RECORD 290:330–340 (2007)
Neocortical and Hippocampal Neuron
and Glial Cell Numbers
in the Rhesus Monkey
JEPPE ROMME CHRISTENSEN,1* KAREN BONDE LARSEN,1
SARAH H. LISANBY,2,3 JASON SCALIA,2,4 VICTORIA ARANGO,2,4
ANDREW J. DWORK,2,4,5 AND BENTE PAKKENBERG1
1
Research Laboratory for Stereology and Neuroscience, Bispebjerg University Hospital,
Copenhagen, Denmark
2
Department of Psychiatry, Columbia University, New York, New York
3
Brain Stimulation and Therapeutic Modulation Division, New York State Psychiatric
Institute, New York, New York
4
Department of Neuroscience, New York State Psychiatric Institute, New York, New York
5
Department of Pathology, Columbia University, New York, New York
ABSTRACT
The rhesus monkey is widely used as an experimental animal model
in the study of brain function and disease. While previous quantitative
studies have provided knowledge of regional numbers, little is known of
the total neocortical neuron and glial cell numbers in this species. The
aim of this study is to establish quantitative norms. We use the optical
fractionator and Cavalieri principle to examine the right hemisphere of
eight young rhesus monkeys taken from the control group of an ongoing
study. Applying these methods to agar-embedded and vibratome-sectioned
tissue, we generate estimates of cell numbers and regional volumes of
neocortical and hippocampal regions with coefficients of variance (CV)
around 10%. The mean unilateral neocortical neuron number is 1.35 3
109 (CV 6 0.10) and the mean unilateral neocortical glial cell number is
0.78 3 109 (CV 6 0.17). Mean unilateral neocortical volume is found to
be 8.5 (CV 6 0.10) cm3 after processing, or 19 cm3 when correcting for
shrinkage. The neuron/glia ratio is 1.77. The neurons are distributed
with 18% in the frontal cortex, 57% in the temporal and parietal cortices,
and 25% in the occipital cortex. In the hippocampal subregions, we found
unilateral neuron number of 1.72 3 106 (CV 6 0.13) and glial number of
2.25 3 106 (CV 6 0.17) in CA1, and 0.80 3 106 (CV 6 0.27) neurons and
1.05 3 106 (CV 6 0.26) glial cells in CA2–3. Comparisons with related
studies show quantitative variation, but also variations in methods and
applications. The results are phylogenetically consistent, apart from the
neuron/glia ratio, which is remarkably higher than what is found in other
species. Anat Rec, 290:330–340, 2007. Ó 2007 Wiley-Liss, Inc.
Key words: stereology; primate brain; cell numbers and volume
Grant sponsor: the Copenhagen Hospital Corporation Research
Council, Hovedstadens Sygehusfaellesskab; Grant sponsor:
National Institute of Mental Health; Grant number: MH60884.
*Correspondence to: Jeppe Romme Christensen, Laboratory
for Stereology and Neuroscience, Bispebjerg University Hospital, Bispebjerg Bakke 23, DK-2400 Copenhagen NV, Denmark.
Fax: 45-35-31-64-34. E-mail: jepperomme@get2net.dk
Ó 2007 WILEY-LISS, INC.
Received 29 June 2006; Accepted 13 November 2006
DOI 10.1002/ar.20504
Published online 15 February 2007 in Wiley InterScience (www.
interscience.wiley.com).
NEOCORTICAL AND HIPPOCAMPAL NEURON
The rhesus monkey (Macaca mulatta) has been the
species of choice for many experimental models of aging,
brain diseases, and new treatment strategies, since it
shares with humans many aspects of neuroanatomy and
cognitive function (Gallagher and Rapp, 1997; O’Donnell
et al., 1999; Peters, 2002). Until now, only a few studies
have estimated standards for neuronal and glial cell
numbers in the rhesus monkey neocortex. Stereological
studies on the rhesus monkey have been either interventional models or focused on specific regions (Peters et al.,
1998). Total neocortical neuronal and glial cell numbers
have been assessed in only one previous study for a control group of four individuals (Lidow and Song, 2001).
Ethical and economical considerations make rhesus
monkey tissue very valuable; therefore, it is of concern
to optimize the study design to employ the tissue as efficiently as possible. In an ongoing study modeling clinical
interventions, we examined the prefrontal cortex and
hippocampus of 24 rhesus monkeys, 8 of which constituted a control group. In the present study, we used an
optical fractionator design to examine all cerebral cortical tissue from the control group to establish estimates
for the normal neocortical and hippocampal cell numbers
and regional volumes.
Finally, we point out advantages and disadvantages
of different techniques such as the optical fractionator
for cell counting and the Cavalieri method for volume
estimation in different regions of interest.
MATERIALS AND METHODS
The sample comprised eight rhesus monkeys forming
the control group of an interventional study in which all
animals, including the controls, received general anesthesia. Half of the sample was female. Mean weight was
3.7 6 0.6 kg. Mean age was 2.8 6 0.46 years.
Interventions and sacrifice were conducted at New
York State Psychiatric Institute in accordance with an
approved Institutional Animal Care and Use Committee
protocol. All subjects were pathogen-free and were bred
and raised at Covance Laboratories, a National Institutes of Health breeding colony in the United States.
The animals were housed in the New York State Psychiatric Institute animal care facility. Following standard
10-week quarantine, they were moved into a colony room
and socially housed in groups of three. The light cycle
was 12 hr a day of light and 12 hr a day of dark. All
monkeys were fed a high protein commercial Monkey
Chow diet (LabDiet High Protein Monkey Diet Jumbo;
Purina Mills), along with daily supplements of fresh
fruit.
In preparation for daily anesthesia sessions, subjects
were sedated in the home cage with intramuscular injections of ketamine (2.5 mg/kg) and xylazine (0.125 mg/
kg). Following transportation into the treatment room,
hair on the head was shaved and an intravenous line
was placed in the leg. Physiological monitoring at each
treatment session included ECG, scalp EEG, pulse oximetry, end-tidal Pco2, and noninvasive blood pressure.
Subjects then received methohexital (0.5 mg/kg intravenous bolus) to induce anesthesia. Each subject received
a total of 6 weeks of anesthesia sessions once a day,
5 days/week, for a total of 30 sessions. Once a week, subjects also received intramuscular atropine, 0.4 mg/kg.
331
5-bromo-20 -deoxyuridine (BrdU) was administered to
the anesthetized monkey through a series of six injections (100 mg/kg, intravenous) over a period of 8 days to
label dividing cells for postmortem analysis. Half of the
sample received BrdU injections once daily for 5 days
during the final intervention week, followed by a final
injection 2 hr prior to sacrifice to examine acute effects
on proliferation. The other half of the sample received
the same number of injections during the 5th intervention week, 6 weeks prior to sacrifice, to examine the
survival and differentiation of labeled cells using cell
type-specific markers.
The animals were sacrificed 72 hr following the last
session in the treatment phase. Subjects were sedated in
the home cage with intramuscular injections of ketamine
(2.5 mg/kg) and xylazine (0.125 mg/kg) and were then
transported to the perfusion laboratory. Subjects were
anesthetized to a surgical depth with sodium pentobarbital (40 mg/kg, intravenous) and heparinized (15 units/kg).
After the induction of deep anesthesia and immediately
prior to perfusion, a small burr hole was drilled in the
skull, providing access to the left prefrontal cortex.
Through the burr hole, a 5 mm diameter core of tissue
was taken from prefrontal cortex and frozen for later
genetic testing.
The right hemispheres had a mean weight of 41 g
(SD 6 4). As part of the interventional study, we had
examined three subdivisions of the right frontal cortex
and two subdivisions of the hippocampus (four rightsided and four left-sided). The remaining tissue was preserved for further examination, with the parietal and
temporal cortices dissected out together and sectioned in
slabs of either 2 or 3 mm. The left hemisphere underwent neuropathological examination in which no abnormal changes were found (Dwork et al., 2004).
Tissue Processing and Stereological Design
In this study, we use the optical fractionator design
and the Cavalieri principle. The optical fractionator
design provides a direct and simple method to estimate
the total cell number and is in principle unaffected by
tissue shrinkage (West and Gundersen, 1990; West
et al., 1991; Howard and Reed, 1998; Dorph-Petersen,
2001). The basic principle is to count every cell in a systematic and uniform random sample (SURS) that constitutes a known fraction of the region of interest. In this
study, this known fraction is composed of three fractions,
namely, a known fraction of the sections of the region of
interest, a known fraction of sectional area, and a
known fraction of the section thickness.
The optical fractionator design was practically applied
in a three-step procedure. In step 1, all brains were
perfusion-fixed with sodium sulfide (0.37%) followed by
phosphate-buffered formalin (10%) or paraformaldehyde
(4%). After removal from the skull and dura mater,
the brains were stored for variable intervals in 10%
phosphate-buffered formalin.
After delineation (Fig. 1) of the regions of interest and
careful dissection, the selected brain region was embedded in agar and cut in the coronal plane into 2 or 3 mm
slabs with a random start point within the slab thickness (Fig. 2). A 100 mm thick section was taken from
the top of the slab from every second of the frontal
slabs, from every second or third of the 2 or 3 mm thick
Fig. 1.
Regions of interest delineated on the pial surface.
Fig. 2. Exhaustive sectioning of the tissue was done in the coronal plane (A). Resulting tissue slabs
from a temporal and parietal lobe are shown in B. From the top of every second slab, a 100 mm thick
section was cut on a vibratome. Since the tissue slabs were 2 mm thick, ssf ¼ (1/2) 3 (100/2,000) ¼ 1/40.
333
NEOCORTICAL AND HIPPOCAMPAL NEURON
TABLE 1. Stereological parameters
1/ssf
Ventral prefrontal
Dorsal prefrontal
Posterior frontal
Temporal and parietal 2 mm.
Temporal and parietal 3 mm.
Occipital
CA1
CA 2-3
40
40
40
40
90
80
20
20
Step-length
mm2
R sections
Area
(counting frame) mm2
R disectors
R Qneuron
R Qglial
3
3
3
3
3
3
3
3
7
8
9
10
6
7
9
9
1554
1545
1546
1328
1327
1326
1301
1344
82
134
210
68
69
23
146
99
155
288
391
235
221
139
185
160
136
196
364
116
166
84
258
224
6000
6000
6000
6000
4000
4000
500
350
6000
6000
6000
6000
4000
4000
500
350
temporal and parietal tissue slabs, and from every
fourth of the occipital neocortical tissue slabs, starting
randomly at slab 1–2, 1–3, and 1–4, respectively.
Every section thus represents a known fixed fraction
of the tissue, the fraction called the section sampling
fraction (ssf; Fig. 2), in this case respectively 1/40, 1/90,
or 1/80 (see Table 1 for further fractionator parameters).
For the hippocampal region, a section was cut from
every tissue slab, giving an ssf of 1/20. To monitor the
block advance on the vibratome, one tissue block from
each animal was chosen at random to be cut exhaustively into 100 micron thick sections, which confirmed
that a 2 mm block provided 20 sections.
In step 2, all sections were mounted on glass slides
(Superfrost Plus) coated with an aqueous solution of
gelatin (4.5%) and chromealum (chromium potassium
sulfate; 4.0%) and air-dried at room temperature. This
procedure was necessary to improve adhesion of the
100 mm thick sections to the slides. Staining was done
with a modified Vogt Cresyl Violet, which provided the best
staining of the relevant cells. Subsequently, the stained
sections were dehydrated in graded concentrations of
alcohol, followed by xylenes, and cover-slipped with
Pertex glue.
Microscopic examination was done using a high-resolution microscope (1003 oil immersion, NA ¼ 1.4, and
final magnification ¼ 3,2003) connected to a computer
via a video camera. A motor stepper measured the movements in the x – y directions while a Heidenhain microcator measured the movements in the z-direction with a
precision of 0.5 mm. A counting frame was applied to the
tissue using CAST software (Fig. 3A).
The counting frame constitutes two of the three
dimensions of the optical dissector. Its area (Table 1)
represents a fraction of the area made up of the step
lengths in the x- and y-directions (Fig. 3B). The area
sampling fraction (asf) is calculated from:
asf ¼
aðframeÞ
aðx; y stepÞ
Hsf is calculated as the q weighted mean section thickness to compensate for differences in section thickness
in and among sections and correlated to the local amount
of particles sampled (Dorph-Petersen et al., 2001):
h
hsf ¼ tQ
where
tQ
P
ðti q
i Þ
i
¼ P qi
i
where ti is the local section thickness centrally in the ith
counting frame with a dissector count of qi.
The total cell number estimate (N) is calculated from
the equation
N¼
X 1
1
1
3
3
3
Q
ssf
asf
hsf
where SQ is the sum of all cells counted in all dissectors in a region.
Counting Principles
For all stereological methods, it is critical that all
particles in each sample are counted only once and with
the same probability, which is provided by the dissector
(Sterio, 1984). With the optical dissector, it is possible to
dissect optically the chosen sample using the focal plane,
which is moved through the thick section in the z-axis.
After having established a constant density within the
dissector height, all sampled particles that come into
focus inside the counting frame are counted and added
to SQ, provided they do not touch the exclusion lines.
An upper guard area of 5 mm was used in order to avoid
loss of sampled particles due to tissue preparation.
Cavalieri Principle
where a(frame) is the area of the counting frame and
a(x,y-step) is the area represented by the step length in
the x–y direction.
In step 3, the mean thickness (t) of the sections was
determined from measurements made in every fourth
dissector measured with the microcator. The height (h)
forms the third dimension of the optical dissector and is
chosen as a predetermined constant, 15 mm in this study.
The height of the dissector relative to the mean section
thickness is the height sampling fraction (hsf; Fig. 4).
To estimate the formalin-fixed nonprocessed volume of
the frontal cortex, a counting grid was laid randomly
over the tissue slabs:
X
Volref ¼ t 3 aðpÞ 3
P
where t is the slab thickness, a(p) is the unit area of the
x–y grid, and SP is the sum of counted points within the
evaluated region.
334
CHRISTENSEN ET AL.
Fig. 3. A shows a schematic application of the optical fractionator
and Cavalieri method to the cortex of a section. All counting frames
were included, but only corner points hitting cortex were included in
the calculation of the processed tissue volume. B shows a screen
shot with the counting frame applied to the tissue. Red lines are exclusion lines, and green lines are inclusion lines. Each counting frame
applied to the tissue constitutes a known fraction of the section. A
fixed step length (big squares in A), chosen in accordance with the
desired precision of the estimates, determines the number of counting
frames (small squares in A) generated from each sample. The area section fraction (asf) is the area of the counting frame divided by the area of
the squares made up of the step length in the x- and y-directions.
335
NEOCORTICAL AND HIPPOCAMPAL NEURON
Fig. 4. The height sample fraction (hsf) is the fraction of the height of the optical dissector (predetermined 15 mm) related to the mean thickness of the sections.
Fig. 5. Coronal section through the hippocampal body showing the regional structures and the
bilaminar nature of hippocampus. The picture was taken with a 23 objective, while the actual delineation
was done with a 103 objective.
The Cavalieri estimate of the processed volume was
obtained by counting the upper right corner of all counting frames touching the region of interest. When estimating the fixed but otherwise unprocessed volume, the
actual section thickness was substituted with the unprocessed section thickness (100 mm). Volume estimates
based on counting points from counting frames are thus
given by
Volref ¼ t 3 aðx; y stepÞ 3
X
1
3
P
ssf
336
CHRISTENSEN ET AL.
Delineation
The neocortical regions were painted on the pial surface before dissection. Boundaries of the frontal region
were defined as the central sulcus and Sylvian fissure,
while the dorsal prefrontal and ventral prefrontal
regions were defined by the principal and arcuate sulci
(Fig. 5) (Barbas and Pandya, 1989; Geyer et al., 2000;
Dombrowski et al., 2001). The temporal and parietal
cortices were counted together. Their boundaries were
defined as the central sulcus, the anterior part of
the Sylvian fissure, the parietal-occipital sulcus, and the
lunate sulcus. Occipital boundaries were the parietaloccipital and lunate sulci.
Archicortical and neocortical transition zones are found
in the cingulate gyrus, uncus, and entorhinal cortex.
Delineation was done in every examined slice with a
43 objective according to cytoarchitectonic criteria
(Amaral et. al., 1987; Vogt et al., 1987; Suzuki and
Amaral, 1994, 2003a, 2003b; Gazzaley et al., 1997; Merrill
et al., 2000).
In the hippocampus, we examined the subregions CA1
and CA2–3 as part of the original study. The definition
of the borders CA1 and CA2–3 was based on criteria
from studies on humans (Duvernoy, 1988; West et al.,
1988, 1994; Simic et al., 1997; Harding et al., 1998) and
rhesus monkeys (Keuker et al., 2003). In most respects,
the cytoarchitectonical organization of these fields are
the same within these species (Amaral and Inausti,
1990). Delineation was done under 23 and 103 objectives (Fig. 5).
Differentiation of Neurons and Glial Cells
While it is usually straightforward to distinguish
large- and middle-sized neurons from glial cells, the distinction between small neurons and large glial cells can
be challenging, a situation that especially is encountered
in the occipital cortex. The following criteria were used
as characteristic for neurons: a centrally located nucleolus, a distinctive nucleus, visible cytoplasm, presence of
dendritic processes, and larger cell body size. Glial cells
were identified by the following criteria: heterochromatin clumps, sparse cytoplasm, and smaller cell body size
(Selemon et. al., 1999; Lidow and Song, 2001; Stark
et al., 2004; Jelsing et al., 2006).
Statistical Analysis
Coefficient of error (CE) for estimates of cell numbers
of the individual cortices was calculated from the
formula
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
CEðNÞ ¼ CE2 þ CEðtÞ2
where CE is obtained from the formula
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
Varsurs þ Noise
P CE ¼
Q
where noise is the sum of counted particles and VarSURS
is the estimator variance under (SURS) (Gundersen and
Jensen, 1987; Gundersen et al., 1999). The VarSURS(N)
is obtained from the formula
VarSURS ðNÞ ¼
ð3ðA NoiseÞ 4B þ C
240
where the systematic section series of particle count are
denoted f1,f2 . . . fn, and
A¼
n
X
f 2i ; B ¼
i¼1
n1
X
f i f iþ1 and C ¼
i¼1
n2
X
f i f iþ2
i¼1
The CE for the volume estimates is a function of the
point-counting noise and the variance of Sarea for a
given direction of sectioning under SURS:
X X
CE
P ¼ Noise þ VarSURS
area ;
where
Noise ¼ 0:07247 3
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
X
b
pffiffiffi 3 n3
P;
a
and (b/Ha) is a constant reflecting average profile shape,
n is the number of sections, and SP is the sum of points.
VarSURS
¼
X
area
ð3 3 ðPi 3 Pi NoiseÞ 43Pi 3 Piþ1 þ Pi 3 Piþ2 Þ
240
where Pi is the number of points counted in one section
and Piþ1 is the number of points counted on the following section and so forth.
The interindividual variability is shown as the standard deviation (SD) and the coefficient of variation (CV).
In favor of optimizing the efficiency and precision of
the study, we adjusted the step length in order to get a
CE of approximately 10%. On average, we counted 242
neurons and 179 glial cells per cortical region, resulting
in coefficients of error for the cell estimates ranging
from 6% to 12%, with averages of 8.3% and 10.7% for
neurons and glial cells, respectively.
A precision in this range is reasonable since the interindividual variation, the CV, ranged from 11% to 29%.
The biological variance of the individual volume estimates of the different regions showed variation in the
range of CV ¼ 8%–27%, the variation in the frontal subregions being somewhat higher (CV ¼ 21%–29%).
RESULTS
Unilateral neocortical numbers are presented in
Table 2 and unilateral hippocampal numbers in Table 3.
Note that processed volumes are listed, which is reflected
in the densities.
The mean frontal cortical volume estimated from point
counting on the fixed but unprocessed tissue was
7,196 mm3 (SD 6 878). The volume calculated from the
sum of corner points in the processed tissue multiplied
by the tissue thickness of 100 mm was 6,522 mm3 (SD 6
508). The difference of about 10% is a product of a
comparison of two estimates and some tissue deformation in the x – y axes. Note that this has no influence on
the cell number estimates.
1,77
0,16
0,077
1,73
0,32
0,04
0,113
2,15
0,16
0,02
0,061
1,01
0,08
0,02
0,027
0,032
1,68
1,14
0,09
0,02
0,18
0,10
0,02
0,049
1,21
0,09
0,01
2679
545
0,20
452
97
0,21
908
266
0,29
1319
293
0,22
4875
582
0,12
1061
84
0,08
8499
807
0,10
0,037
Neuron/glia
ratio
Neuron density
(106/mm3)
337
Tissue shrinkage in the z-axis was calculated to be
54% on the basis of mean section thickness and the original section thickness of 100 mm. Accordingly, when
correcting for tissue shrinkage, we find total neocortical
volume of about 18,500 mm3 and a corrected neuronal
density of approximately 73,000 neurons/mm3.
Total neocortical neuron number was approximately
10% greater in males than in females (Table 4), but this
was not statistically significant (t ¼ 1.8; df ¼ 6; P ¼ 0.13).
DISCUSSION
Stereological Design
The optical fractionator provides an efficient method
for estimating neocortical and hippocampal cell numbers
and the Cavalieri principle a method for estimation of
regional volumes. The methods were easily applied in an
agar and vibratome design, with the purpose of saving
tissue for future evaluation by maintaining as much of
the tissue integrity as possible. The sampling in each
region was optimized according to the precision of the
estimate and the required work load.
0,097
0,108
0,105
0,059
0,072
0,091
0,109
0,120
0,122
0,060
0,079
0,093
0,084
0,094
0,085
0,058
0,063
0,089
Total neocortex
Occipital
Temporal and
parietal
Posterior
frontal
Ventral
prefrontal
Dorsal
prefrontal
Average
St Dev
CV
Average
St Dev
CV
Average
St Dev
CV
Average
St Dev
CV
Average
St Dev
CV
Average
St Dev
CV
Average
St Dev
CV
233
31
0,13
41
9
0,23
85
13
0,15
106
19
0,18
782
131
0,17
334
44
0,13
1349
140
0,10
0,071
196
40
0,21
36
6
0,17
52
13
0,24
108
26
0,24
380
94
0,25
200
57
0,29
776
129
0,17
0,078
429
67
0,16
77
14
0,18
138
23
0,17
214
42
0,20
1162
170
0,15
534
94
0,18
2125
202
0,10
0,075
Considerations on Tissue Processing
Frontal
CE
Processed
Volume (mm3)
CE
Total
cell (106)
CE
Glia
(106)
CE
Neurons
(106)
TABLE 2. Unilateral estimates of cell numbers, volume, density and neuron/glia ratio in neocortical regions
NEOCORTICAL AND HIPPOCAMPAL NEURON
Generally, final section thicknesses of about 25 mm
or more are sufficient in optical dissector designs. Due
to substantial tissue shrinkage in the z-axis after
sectioning, vibratome sections should typically be cut at
70–100 mm.
The agar and vibratome design was chosen because it
gives wider possibilities for further investigations, e.g.,
cell volume or immunohistochemical staining, on the
unused slabs. Cryostat preparations have similar properties to the agar and vibratome preparation.
In the pilot phase, one brain was cut into consecutive
paraffin sections. This method offers less laboratory work
and the opportunity for applying the physical dissector
on thin sections. However, paraffin preparations exclude
the possibilities of future examinations of, e.g., cell size,
since it results in substantial shrinkage in all three axes
and is only recommendable for cell counting. Finally, we
found paraffin unsuitable for hippocampal preparations,
since its appendage-like morphology combined with the
small cracks sometimes seen in paraffin sections resulted
in artifacts that made several sections unusable.
Methacrylate resin preparations result in only limited
tissue shrinkage in all three dimensions, but impose
limitations on the size of the sections and the use of
immunohistochemical staining.
Anatomical Considerations
The prefrontal regions are heterogeneous, with subregions whose borders are defined cytoarchitectonically,
but map descriptions vary considerably (Barbas and
Pandya, 1989; Dombrowsky et al., 2001). In the present
study, the boundaries were macroscopically defined by
the principal sulcus and arcuate sulci, which vary more
than the central sulcus and Sylvian fissure delimiting
the frontal lobe. Our results reflect this circumstance,
with higher coefficients of variance for cell numbers
in each subregion than in the total frontal region. The
volume of the prefrontal cortices varies with coefficients
of variance between 20% and 29%, which is consistent
with the findings of O’Donnell et al. (1999).
338
CHRISTENSEN ET AL.
TABLE 3. Unilateral estimates of cell numbers, volume, density and neuron/glia ratio in hippocampal
subregions CA1 and CA2-3
CA1
CA2-3
Neurons (106)
CE
Glial cells (106)
CE
Volume (mm3)
CE
Density (106/mm3)
1,72
0,23
0,13
0,80
0,22
0,27
0,080
2,25
0,39
0,17
1,05
0,27
0,26
0,072
23,45
3,76
0,16
7,40
2,76
0,37
0,037
0,07
0,033
0,11
Average
St Dev
CV
Average
St Dev
CV
0,052
0,046
TABLE 4. Neocortical estimates of cell numbers, volume, and neuron/glia ratio In relation to gender
Gender
Neuron (mill.)
Glia (mill.)
Total (mill.)
Volume (mm3)
Neuron/glia ratio
F
F
F
F
Average
M
M
M
M
Average
1446
1304
1202
1136
1272
1373
1545
1302
1479
1425
898
620
628
839
746
748
758
958
758
806
2344
1924
1830
1975
2018
2121
2303
2260
2237
2230
–
8270
8458
8448
8392
7548
8854
7862
10154
8604
1,61
2,10
1,91
1,35
1,75
1,84
2,04
1,36
1,95
1,80
The occipital region was also delineated according
to macroscopic criteria. In the examination of caudal
temporal sections, we occasionally (one or two dissectors
in a few brains) encountered microscopically characteristic occipital cortex, reflecting that the macroscopic boundaries are not always entirely precise. Since it would
contribute only marginally to the occipital cell number,
in order to maintain simple criteria, we attributed the
cells to the temporal region.
Comparisons With Related Studies
In an interesting study, Lidow and Song (2001) examined neocortical cell numbers in the rhesus monkey.
Here the authors found a mean of 295 3 107 (SD 6 90)
neurons and 241 3 107 (SD 6 68) glial cells in the left
hemisphere neocortex of the monkeys forming the control group. These numbers are greater than our estimates by a factor of 2 to 3. Neocortical volume was
calculated on data from celloidin processed tissue, with
an estimated tissue shrinkage of 10%–16%, and was
reported to be approximately 21 cm3 (SD 6 2), similar to
what we find. The neuron/glia ratio was 1.2, compared
with a ratio of 1.8 in the present study, possibly reflecting differences in application of differentiation criteria
or a difference between the populations.
Although the Lidow and Song (2001) study used
modern stereological principles, the optical dissector and
point counting, we find differences in the applied methods that might explain some of the discrepancy in the
cell numbers. First, counting was done with a counting
frame extending the whole depth of the neocortex, while
it is unclear how the whole cortical depth can always
be identified in the tissue bars. One would expect, for
example, that some of the bars are tangential to the
cortical surface in an SURS sample. Second, the cell
densities were obtained without guard areas on both
sides of the optical dissector, which may result in a
small bias. Further, the application of the original formula of CE of Gundersen and Jensen (1987) cannot have
been applied appropriately, since counting literally hundred thousands of cells will result in a smaller CE than
reported. Finally, the surface area was not calculated
from unbiased stereological principles (Howard and Reed,
1998). However, these methodological differences are
unlikely to explain a two- to three-fold discrepancy in the
cell numbers. The possibility of differences between
breeding strains of the monkeys would be an interesting
subject for further investigation.
Dombrowski et al. (2001) found, in a cryosection
design, densities in different prefrontal areas ranging
from 39,000 to 59,000 neurons/mm3 and 43,000 to
57,000 glia/mm3 calculated on the basis of fixed unprocessed volume. They found a neuron/glia ratio of about 1.
Concordantly, we find mean unprocessed densities (by
correcting for shrinkage) of 43,000 neurons/mm3 and of
30,000 glia/mm3 in the prefrontal cortex and a neuron/
glia ratio of 1.4.
Selemon et al. (1999) examined area 46 of prefrontal
cortex in rhesus monkey brains and found densities of
133,000 neurons/mm3 and 92,000 glia/mm3 in an optical
dissector design, where the y-axis of the counting frame
extended the whole cortical depth. The tissue was celloidin-embedded, and no correction for tissue shrinkage is
reported (Selemon et al., 1995). We find mean prefrontal
densities in processed tissue of approximately 95,000
neurons/mm3 and 70,000 glia/mm3 markedly lower than
the findings of Selemon et al. Dombrowski et al. (2001)
report an unprocessed density of about 55,000 neurons/
mm3 in area 46. Although celloidin processing, used by
Selemon et al. (1995), is subject to tissue shrinkage, this
is limited, and failure to correct for shrinkage is unlikely
to account for the whole discrepancy. Biological variation, which might be increased by the use of different
NEOCORTICAL AND HIPPOCAMPAL NEURON
strains, also may explain some of the discrepancy. The
use of different stereological designs can contribute to
the discrepancy, as noted above. Sampling the whole
cortical depth might give methodological problems that
are difficult to evaluate. Finally, the study by Selemon
et al. (1995) examines only probes located in gyral crests,
which, according to a recent study from Hilgetag and
Barbas (2005), contain significantly more neurons than
sulcal areas. This way of sampling, while potentially systematic and random, is certainly not uniform, and it can
result in bias.
Keuker et al. (2003) examined the hippocampus of the
rhesus monkey using stereological methods for quantifying the neurons, but not the glial cells. The investigators
found a mean of 1.18 3 106 (CE 5.5%) in CA1 and 0.6 3
106 (CE 6.2%) in CA2–3. These numbers are lower than
the present findings. The difference may be due to biological variance or to problems in distinguishing small
neurons from glia.
Comparing the present study with studies on humans
(Pakkenberg and Gundersen, 1997; Pakkenberg et al.,
2003) suggests that the rhesus monkey has about 8 times
fewer neocortical neurons and 25 times fewer glial cells
distributed in a neocortical volume 13 times smaller.
Analogous to the human studies, our study finds a tendency toward sex difference in cell numbers and volume.
Considering the small population of the present study,
this finding would be interesting to confirm in future
studies.
From a phylogenetic perspective, the results give rise
to some considerations. Frontal neurons constitute 18%
of the neurons in the rhesus monkey neocortex, whereas
this part is 34% in the human neocortex, an expected
finding since frontal cortex is phylogenetically the
youngest part of the neocortex. Human hippocampus
has approximately four times as many neurons in CA1
and twice as many in CA2–3. The relatively small difference in neuron number between human and rhesus
monkey hippocampus is phylogenetically consistent with
hippocampus being part of the archicortex.
The neocortical neuron/glia ratio is 1.7 in rhesus
monkeys, compared with 0.6 in humans (Pakkenberg
et al., 2003), 0.45 in Göttingen minipig (Jelsing et al.,
2006), and 0.13 in the minke whale (Eriksen and Pakkenberg, unpublished data). The Göttingen minipig has
a similar brain weight to the rhesus monkey (80–100 g),
but fewer neocortical neurons by a factor of 8 (Jelsing
et al., 2006). In the rat, Mooney and Napper (2005)
found a ratio of 2.0 in neocortex. Herculano-Houzel and
Lent (2005), using the novel approach of counting nuclei
in a homogenate of whole rat brain, obtained a ratio of
neurons to other cells of 0.7; since white matter was
included, the lower value is not surprising.
The animals in this report were exposed, as controls
for an intervention study, to repeated episodes of general
anesthesia. While this exposure is unlikely to have affected our results, we cannot definitively rule out that
possibility, since the impact of daily anesthesia on neuronal numbers has never been evaluated. However, neuronal loss from anesthesia is unlikely in the present study.
Ventilation and monitoring of vital signs and oxygenation were performed continuously during anesthesia,
and thorough neuropathological examination, reported
previously (Dwork et al., 2004) and extended to include
all of the animals in this study, revealed no evidence of
339
neuronal damage or its aftermath. The anesthesia sessions were distributed over the 10 weeks prior to sacrifice; had they resulted in significant neuronal loss, this
would have been accompanied by a correspondingly significant cortical gliosis, which was not observed qualitatively by staining many sections from each case for glial
fibrillary acidic protein, nor quantitatively in the current
study [e.g., by comparison with the glial counts of Lidow
and Song (2001)].
In summary, our findings provide new knowledge
about the quantitative structure of the normal young
rhesus monkey brain. Though based on a small population, our material suffices to generate estimates of the
mean cell numbers and regional volumes with reasonable coefficients of variance, taking the normal biological
variation of these quantities into account. A remarkable
finding is a neuron/glia ratio of 1.7, which differs from
other species, primates as well as nonprimates. The implication of this finding remains unclear. Another finding, though not statistically significant, is the tendency
toward a difference in neuron number between the
sexes. Comparing our results with previous studies, we
find considerable variations in the results, but also a
considerable degree of methodological variation.
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