Download Inhibitory interneurons in a cortical column form hot zones of

Inhibitory interneurons in a cortical column form
hot zones of inhibition in layers 2 and 5A
Hanno S. Meyer1, Daniel Schwarz, Verena C. Wimmer2, Arno C. Schmitt3, Jason N. D. Kerr3, Bert Sakmann1,4,5,
and Moritz Helmstaedter5
Max Planck Institute for Medical Research, D-69120 Heidelberg, Germany
Although physiological data on microcircuits involving a few inhibitory neurons in the mammalian cerebral cortex are available,
data on the quantitative relation between inhibition and excitation
in cortical circuits involving thousands of neurons are largely missing.
Because the distribution of neurons is very inhomogeneous in the
cerebral cortex, it is critical to map all neurons in a given volume
rather than to rely on sparse sampling methods. Here, we report the
comprehensive mapping of interneurons (INs) in cortical columns of
rat somatosensory cortex, immunolabeled for neuron-specific nuclear protein and glutamate decarboxylase. We found that a column
contains ∼2,200 INs (11.5% of ∼19,000 neurons), almost a factor of 2
less than previously estimated. The density of GABAergic neurons
was inhomogeneous between layers, with peaks in the upper third
of L2/3 and in L5A. IN density therefore defines a distinct layer 2 in
the sensory neocortex. In addition, immunohistochemical markers of
IN subtypes were layer-specific. The “hot zones” of inhibition in L2
and L5A match the reported low stimulus-evoked spiking rates of
excitatory neurons in these layers, suggesting that these inhibitory
hot zones substantially suppress activity in the neocortex.
barrel cortex
| parvalbumin | somatostatin | calretinin
F
or a quantitative understanding of the interaction between
excitatory and inhibitory synaptic transmission in the neocortex, it is crucial to obtain data on the absolute numbers and
the relative distribution of excitatory and inhibitory (mostly
GABAergic) neurons [interneurons (INs)] in a cortical column.
Only on the basis of such prevalence numbers is it possible to
interpret data on single-cell physiology (1–8) and synaptic connections of pairs of neurons (9–12) at the circuit level. The distribution of cortical neurons and INs has therefore been the
objective of several studies over the past decades (13–15). Statistical sampling methods were used because mapping tens of thousands of neurons was not feasible. Although the nominal error
bounds of such methods are in the range of 10–20%, the reported
absolute numbers differed strongly among studies, especially for
sparse neuron populations, such as INs and their subtypes. The
ratio of INs reported for the somatosensory cortex varied between
15% and 25%, thus by almost a factor of 2 (13, 16, 17). Data on
possible differences in IN density between layers in a cortical
column were contradictory (13, 15, 16, 18, 19).
To resolve these substantial discrepancies, we undertook the
complete mapping of INs in entire cortical columns using the
cytoarchitectonic barrels in L4 as a reference frame for the thalamocortical innervation volume (20) in postnatal day (P) 25–36
rat vibrissal cortex. Our data show that the overall prevalence of
inhibitory neurons was previously overestimated by almost a factor
of 2. We find a unique substructure of the distribution of INs in a
cortical column that can explain the layer-specific differences in
the excitability in neocortex. The distribution of INs defines layer
2 as a distinct neocortical layer.
Results
datasets. We used the outlines of barrels in L4 of rat somatosensory cortex to define the lateral column borders (Fig. 1A). We had
found previously that the overall epifluorescence of tissue stained
against glutamate decarboxylase 67 (GAD67) showed barrelrelated patches in L4 (corresponding to a high density of GAD67positive boutons) and that these were aligned with the patches of
thalamic afferents originating from the ventral posterior medial
nucleus (21) (Fig. S1A). The column and layer borders derived
from cytochrome C oxidase (CO)- and GAD67-stained slices
agreed (average distance between corresponding column and layer
borders: 14 ± 8 μm, Fig. 1A). For the following analyses, we used
the column and layer borders derived from GAD67-stained slices.
Labeling of Neurons and INs. To identify somata of neurons and
putative GABAergic INs, we double-immunolabeled 50-μm-thick
slices against GAD67 and neuron-specific nuclear protein (NeuN).
Fig. 1B shows fluorescence images obtained from the same optical
section through L2/3 of a D2 column. Neurons were identified
by NeuN staining, showing strong fluorescence in the soma and
proximal dendrites (arrows in Fig. 1B, Left). Neurons were either
GAD67-positive (filled arrow in Fig. 1B) or GAD67-negative
(open arrow in Fig. 1 B and C). GAD67-positive neurons showed
strong fluorescence in the somatic cytosol, whereas the nuclei
remained unstained (filled arrow in Fig. 1B). GAD67-negative
somata were delineated by surrounding GAD67-positive puncta,
most likely representing GAD67-positive boutons (cf. 22) (open
arrow in Fig. 1B, Center).
GAD, the synthesizing enzyme of GABA, is thought to be a
reliable marker of GABAergic neurons (e.g., 22–24). We correlated GAD67 antigenicity with staining against GABA by immunolabeling 50-μm-thick slices for NeuN, GABA, and GAD67 (Fig.
1C). NeuN-positive neurons (Fig. 1C, arrows) were either clearly
GABA-negative (Fig. 1C, Upper Left, open arrow), clearly GABApositive (Fig. 1C, filled arrow), or neither clearly negative nor
clearly positive (Fig. 1C, dashed arrow). All clearly GABA-positive
neurons were positive for GAD67 (71 of 71). Eight of 96 GAD67positive neurons were clearly GABA-negative. We conclude that
GAD67 immunolabeling was highly sensitive to GABA-positive
Author contributions: H.S.M., B.S., and M.H. designed research; H.S.M., A.C.S., and J.N.D.K.
performed research; V.C.W. contributed new reagents/analytic tools; H.S.M., D.S., and M.H.
analyzed data; and H.S.M. and M.H. wrote the paper.
The authors declare no conflict of interest.
Freely available online through the PNAS open access option.
1
Present address: Department of Digital Neuroanatomy, Max Planck Florida Institute,
Jupiter, FL 33458.
2
Present address: Florey Neuroscience Institutes, University of Melbourne, Parkville 3010,
Victoria, Australia.
3
Present address: Network Imaging Group, Max Planck Institute for Biological Cybernetics, 72076 Tubingen, Germany.
4
Present address: Research Group Cortical Column in Silico, Max Planck Institute for Neurobiology, D-82152 Martinsried, Germany.
5
Delineation of Cortical Columns. For the measurement of IN dis-
To whom correspondence may be addressed. E-mail: bert.sakmann@maxplanckflorida.
org or [email protected].
tribution with reference to cortical columns, it was critical to define
the borders of columns precisely for each of the neuron count
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.
1073/pnas.1113648108/-/DCSupplemental.
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Contributed by Bert Sakmann, August 24, 2011 (sent for review April 21, 2011)
Fig. 1. Identification of columns, neurons, and INs. (A) (Left) Bright-field
image of a CO-stained semicoronal barrel cortex slice (100-μm thickness,
right hemisphere, P27 rat). Note barrels as dark patches in L4. Borders of
cortical columns were extrapolated from the lateral barrel borders (dashed
lines). (Center) Epifluorescence image of the subsequent slice (50 μm),
immunolabeled for GAD67. Note clearly visible barrels (Fig. S1). (Right)
Column and layer outlines from the CO staining (black) and GAD67 staining
(green). (B) Fluorescence images of a slice immunolabeled for NeuN and
GAD67 and an overlay. A GABAergic IN (filled arrow) and GAD67-negative
(excitatory) neuron (open arrow) are indicated. (C) Fluorescence images of a
slice immunolabeled for GABA in addition to NeuN and GAD67. The filled
arrow shows a GABA- and GAD67-positive neuron; the open arrow shows
a GABA- and GAD67-negative neuron; and the dashed arrow shows a
GAD67-positive and GABA-ambiguous neuron. All images in B and C show
one confocal imaging plane. (Scale bar: 50 μm.)
neurons and that the following analyses using GAD67 antigenicity
yield an upper estimate of GABA-positive neuron densities. In the
following, we use the term “interneuron” for GAD67-positive
GABAergic neurons.
Distribution of the Somata of INs in Putative Cortical Columns. We
first analyzed the IN distribution in five slices cut at a thickness of
50 μm through the center of the D2 column. Five slices from five
hemispheres of four animals (P25–P36, both sexes) were analyzed.
All the slices contained the center of D2 (n = 5) and either C2 (n =
3) or E2 (n = 2). Markers were manually placed in somata of
neurons and INs [details, especially the correction for doublecounting between slices, are discussed in the article by Meyer et al.
(21) and SI Materials and Methods]. Fig. 2 A and B shows the neuron
and IN markers from one of the slices (9,911 neuron somata in Fig.
2A and 1,334 IN somata in Fig. 2B). For quantification, we computed 2D neuron and IN density maps in the plane of the slice (Fig.
S2). Finally, to calculate average density maps, the soma markers
from the five slices were registered to a standard D2 column 2 mm
in height aligned at the L4 barrel center, with the vertical column
axis approximately perpendicular to the pial surface. Density maps
were smoothed and interpolated (SI Materials and Methods and Fig.
S3). Fig. 2 C and D shows the resulting average smoothed interpolated density maps of excitatory neuron (Fig. 2C) and IN (Fig.
2D) somata centered on the D2 barrel. The projection of these
maps onto the vertical column axis is shown in Fig. 2 E and F.
The density of IN somata was highest at a depth of 180–210 μm
in upper L2/3 (18,400 per mm3, Fig. 2 D and F) and at a depth of
800–1,100 μm in infragranular layers (14,000 per mm3). IN density
dropped by a factor of 1.9 from upper L2/3 to lower L2/3 (17,400
vs. 9,000 per mm3, Fig. 2 D and F and Table 1). The IN density
profile thus suggested a distinction of L2 and L3 that was not
observed previously based on either the excitatory neuron density
[Fig. 2 C vs. D and Fig. 2 E (black line) vs. F] or bright-field images
of CO-stained slices (Fig. 1). The depth dependence of the soma
density as seen in the Z-profiles (Fig. 2 E and F) allowed a quantitative delineation of the L2-to-L3 border. We determined the
steep drop in IN density within L2/3 to be at 240 μm from the pia
(i.e., at 37% of the layer 2/3 height; Fig. 2F). This thus defines a
division of “L2/3” into layer 2 and layer 3 with a relative thickness
of approximately one-third (L2) vs. two-thirds (L3).
In the tangential plane, lateral column borders could be delineated at the level of layer 4 based on neuron soma density (Fig. 2
A and C). The delineation of lateral column borders by NeuNpositive soma density was not observed in supra- or infragranular
layers (21) (Fig. 2C). The distribution of IN somata, however,
showed an outline of the lateral border between the D2 column
and its neighboring columns at a depth of 200–300 μm in lower L2
and upper L3 (Fig. 2D, arc-like shaped band of high soma density;
Fig. 3; and as discussed below). Thus, the distribution of INs may
suggest a cytoarchitectonic columnar pattern even in supragranular layers.
Neuron and IN Distribution in Complete Cortical Columns. We next
counted INs in three complete cortical columns (C2, D2, and D3)
to obtain a reliable measurement of the absolute number of INs in
Fig. 2. Distribution of excitatory neurons and INs in
cortical columns. (A) Distribution of NeuN-positive
somata in one semicoronal slice (thickness of 50 μm,
9,801 manually placed markers). Dashed lines show
column and layer borders determined by GAD67
staining (Fig. 1A). Note the barrel-aligned patches of
high neuron density in L4 (Fig. S2A). (B) Distribution
of GAD67-positive somata in the same slice (1,209
markers; Fig. S2B). Maps of average excitatory neuron density (C) and GAD67-positive IN density (D)
from five slices centered at the D2 column, aligned
to the D2 barrel center (Materials and Methods and
Fig. S3). Note the two IN “hot zones” in L2 and
upper L5 defined by high IN density, whereas IN
density in L3, L4, and lower L6 is low. (Color scale bar
range: C, 0–140,000 per mm3; D, 0–18,500 per mm3.) (E) IN density distribution along the D2 vertical column axis (red), mean excitatory neuron density (black),
and individual density profiles from the five slices (gray). Layer borders were determined by differences in excitatory neuron density (dashed horizontal lines).
(F) Mean IN density profile (as in E), with a sharp peak in supragranular layers defining a cytoarchitectonic layer 2 (Inset). (G) IN-to-neuron ratio along the
vertical column axis (D2 column). Red markers in A and B indicate a blood vessel.
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Meyer et al.
Table 1. Number and density of INs in the layers of a cortical column
Slices (3 × C2, 3 × D2)
Entire columns (C2, D2, D3)
Layer No. excitatory neurons
1
2
3
4
5A
5B
6A
6B
L1–6B
10
1,701
3,398
4,089
1,394
1,873
3,449
976
16,889
±
±
±
±
±
±
±
±
±
7
484
807
425
247
53
165
155
423
No. INs
53
338
338
358
343
362
337
90
2,220
±
±
±
±
±
±
±
±
±
6
40
109
15
65
62
31
17
198
3
IN density, 10 per mm * IN-to-neuron ratio (%) IN density, 10 per mm3* IN-to-neuron ratio (%)
5.5
14.5
9.1
10
10.9
9.7
8.2
3.5
9.2
±
±
±
±
±
±
±
±
±
3
2.2
0.7
1.5
1.1
3
1.9
0.8
0.4
0.9
3
84.3
17
9
8.1
19.9
16.2
8.9
8.4
11.6
±
±
±
±
±
±
±
±
±
9.5
2.4
1.1
0.5
4.1
2.1
0.9
0.6
1
4.6
14.5
8.9
9.2
13.4
11.4
8.7
4.8
9.8
±
±
±
±
±
±
±
±
±
1.9
3.2
2.1
1.4
1.8
2.2
0.5
1.2
0.8
96.8
20.8
9.5
6.4
20.5
18.3
9.7
8.7
12.1
±
±
±
±
±
±
±
±
±
5.1
2.7
1.7
0.7
3
2.8
0.8
2.7
0.6
All numbers are mean ± SD.
*The volume density is sensitive to tissue shrinkage. Calibration in the living brain (Fig. S7) yielded a shrinkage estimate of up to 20% per spatial dimension.
whole-column analysis (Fig. 3F), whereas it appeared at a depth of
approximately 200–300 μm in the semicoronal slice data (Fig. 2D)
because the latter were normalized to a standard column with a
height of 2 mm.
Molecular Markers of INs in a Cortical Column. Parvalbumin (PV),
somatostatin (SOM), and calretinin (CR) are widely used as molecular markers of INs (e.g., 25–28). We triple-immunolabeled
slices of D2 and C2 for NeuN and GAD67 as well as for either PV,
SOM, or CR. Virtually all marker-positive neurons were also
positive for GAD67 (97.4% for SOM, 97.8% for PV, and 98.1%
for CR), supporting the assumption that GAD67 immunohistochemistry (IHC) labels almost all inhibitory INs. Density maps
showing the distributions of immunoreactive somata are shown in
Fig. 4 (also in Figs. S4 and S5). We found that PV-positive INs
were most abundant in lower L4 and infragranular layers (Fig. 4 A
and D); SOM-positive INs were most abundant in L3, L5A, and
L6A (Fig. 4 B and D); and CR-positive INs showed highest densities in L2 and L5B (Fig. 4 C and D). In all cortical layers, with the
exception of L6B, the density of PV-positive INs was higher than
the density of SOM- or CR-positive INs (Fig. 4D). On average,
PV-positive INs, SOM-positive INs, and CR-positive INs ac-
Fig. 3. IN distribution in three complete cortical columns. Projection in a semicoronal plane of 66,422 NeuN-positive (A) and 7,389 GAD67-positive (B) soma
markers in a region comprising the entire D2 and C2 columns. Dashed lines represent barrel outlines in the tangential plane. Note the high density of INs in L2
and L5A. (C) Neuron distribution (Left) and IN distribution (Right) in the C2 column, rotated to the vertical column axis. (D) IN distribution in three complete
columns (C2, D2, and D3: red, green, and blue, respectively). Dashed lines represent vertical column axes, and white lines represent barrel outlines. a.l.,
anterior-lateral; b., basal; c.l., caudal-lateral. (E) Overlay of the 6,686 INs counted in three columns (D), aligned to the column axis and the pial surface and
centered (in the tangential plane) to the barrel center. (F) Distribution of INs in the tangential plane. Density maps at varying depths from the pia (dashed
white lines in E). Note the ring-like distribution of INs at 50–150 μm from the pia (corresponding to the “arcs” seen in the semicoronal plane; Fig. 2D). (Scale
bars: 200 μm.)
Meyer et al.
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a cortical column (because these results were not affected by tissue
shrinkage, as discussed below; Table 1). These data also allowed us
to investigate the IN distribution in the tangential plane further.
The number and distribution of all neurons in these three columns
have been reported previously (21). Fig. 3 A and B shows the
neuron and IN somata detected in consecutive tangential slices at
a thickness of 50 μm containing D2 and C2 in the right hemisphere
of a P27 animal. The high IN density in L2 and L5A is visible (Fig.
3B). Together with a mapping of all INs in the D3 column (Fig.
3D), these data permitted the analysis of IN distributions in the
tangential plane (parallel to the surface of the cortex). We determined the vertical column axes for each of the three columns
(Fig. 3D) and then rotated the three datasets to the common axis
and aligned them to the barrel center in the tangential plane (Fig.
3E). We then computed IN density maps in the tangential plane
(Fig. 3F) at increasing depths from the pia. The arc-like shaped
band of high IN soma density seen in the supragranular layers in
the average semicoronal slice of the center of the D2 column
(compare with Fig. 2D) was indeed indicative of a circular distribution of high IN soma density in lower L2 and upper L3 (Fig. 3F,
Upper Middle). Note, however, that this putative columnar distribution appeared at a depth of 50–150 μm from the pia in the
counted for 76% of GAD67-positive INs (Fig. 4E). Note, however,
that in L2 and lower L6, the total of the three markers did not
account for more than 50% of all INs (as little as ∼40% in L2),
leaving at least half of the IN population unaccounted for. In L1,
where all neurons are INs (Fig. 2G), virtually no marker-positive
neurons were found.
Absolute Number of INs in a Cortical Column. We finally calculated
the absolute number of INs in the layers of an average barrel
column (Table 1; for INs in the white matter, see Fig. S6). When
based on extrapolations from volume densities and column geometry, such absolute numbers are very sensitive to tissue
shrinkage (attributable to fixative-mediated dehydration) and the
precise definition of column borders. Using two-photon laser
scanning microscopy, we measured the density of neurons in upper
layer 2 in the D2 barrel column in vivo, yielding a lower bound
estimate of the volume density of 53,000 neurons per mm3 (29)
(Fig. S7). Comparing this with the average L2 neuron density in
fixed tissue (Table 1), we found that tissue volume shrinkage is
significant: up to 20% per spatial dimension. We therefore counted all INs in completely reconstructed columns (Fig. 3) to obtain
absolute numbers of INs per layer in a cortical column that were
unaffected by shrinkage, as we reported previously for absolute
numbers of all neurons in a cortical column (21). Comparing the
density measurements obtained from semicoronal slices of the D2
column center (Fig. 2) with data from entire column counts (Fig.
3) yielded no significant differences in any of the layers (Table 1).
Both measurements agreed on the estimated IN ratio (11.6% vs.
12.1%, respectively; Table 1).
In summary, we find that a cortical column contains ∼2,200
INs. All layers comprise ∼300–400 INs, with the exception of
layers 1 and 6B (50 and 90 INs, respectively). The fraction of
neurons that is GABAergic is, on average, 11–13%; it approaches
20% only in layers 2 and 5A.
Discussion
By counting IN distributions with reference to the geometrical
landmarks of cortical columns, we found that (i) the fraction of
INs is lower than previous estimates (∼11–12%, totaling ∼2,200
INs per cortical column); (ii) the distribution of INs is more inhomogeneous along the vertical column axis than previously
reported (“hot zones” of IN density are located in upper L2/3 and
in L5A); (iii) the density and fraction of GABAergic INs define
a genuine cytoarchitectonic layer 2 in vibrissal cortex, with L2
comprising the upper one-third and L3 comprising the lower twothirds of L2/3; and (iv) the IN distribution in the tangential plane
indicates column borders in supragranular layers.
Fraction and Density of INs: Comparison with Previous Reports.
Previous reports of the fraction of INs in rat somatosensory cortex yielded estimates between 15% (13) and 25% (16), thus differing by a factor of 1.7. Our data show that the fraction of INs is,
in fact, lower (12%, Table 1). Notably, this low IN fraction was
confirmed both by the whole-column counts (12.1% ± 0.6%,
obtained from tangential slices; Fig. 3) and the center-column
counts (11.6% ± 1%, obtained from coronal slices; Fig. 2).
Data on the inhomogeneity of IN density between cortical
layers has been most controversial, even for the same species
(rat) and cortical area (somatosensory cortex): Beaulieu (13)
reported only moderate differences between layers; Ren et al.
(16) reported strong differences, with the highest IN density in
layer 4; Esclapez et al. (19) reported the highest densities for
infragranular layers; and Chmielowska et al. (18) reported the
highest densities for supragranular layers. Our data show that the
IN volume densities are, in fact, highest in L2 and L5A and that
they are almost 50% lower in L4 (Table 1). Moreover, the
fraction of INs is lowest in L4 (only 8.1 ± 0.5%).
Methodological Considerations. Methodological differences (cf. 21)
may explain the discrepancies from previous reports. Analysis of
the number and distribution of less prevalent neuronal populations (e.g., INs, subtypes of INs) in small cortical volumes (e.g.,
single cortical columns, layers and sublayers of a single cortical
column) requires the localization of a large number of neurons,
preferably in the complete volume of interest, as was done in the
present study. Previous studies, however, used Nissl staining and
GABA IHC of very thin slices and random statistical sampling of
only a few somata (disector method), which may have hampered
these analyses, as indicated by their disagreeing results (13, 16). In
the present study, using IHC of consecutive thick sections in
combination with confocal microscopy, mosaic scanning, visualization software, and computer-aided data analysis, the actual
counting of tens of thousands of neurons and differentiation of
columns from the surrounding cortex were feasible (21, 30). The
data presented here are from adolescent rats. It is unknown
whether the IN distribution that we found is species-specific, which
will be an important topic for future studies.
IN Density Defines a Genuine Layer 2 in Cortex. Historically, the basis
of the laminar subdivision of isocortex is the Nissl preparation
(31), mainly revealing differences in size, shape, and packing
density of the pyramidal cells as a basis for the distinction of cortical layers (32–34). L2 has been described as the “corpuscular
layer” and L3 as the “pyramidal layer” (33, 35, 36). Many attempts
were made to identify specific anatomical features distinguishing
L2 and L3 in specific cortical areas [e.g., higher density of stellate
and small pyramidal cells in L2 vs. fewer stellate cells and a sparser
Fig. 4. Distribution of IN somata immunoreactive for
PV, SOM, and CR. Average density maps of PV-positive
(A), SOM-positive (B), and CR-positive (C) INs in slices from
the D2 and C2 columns (compare with Fig. S4). (D) Distribution of the IHC IN types along the vertical column
axis (D2 column; variability between individual slices is
shown in Fig. S5). Note that PV-positive INs are most
dense in lower L4; SOM-positive INs are most dense in
L5A, L3 and upper L6; and CR-positive IN density has
a peak in L2 and L5B. (E) Vertical profile of the fraction of
IHC IN types (compared with all INs in the D2 column).
Note that in all layers except for L6B, PV-positive INs are
most abundant and the majority of INs are negative for
all three tested markers (sum of ratios, black line) in L2,
although IN density is highest (Fig. 2 D–G). Only in lower
L3, L4, and upper L6A can the three IN markers account
for all INs. (Color scale bar, neuron density range: A, 0–
11,000 per mm3; B, 0–6,000 per mm3; C, 0–4,000 per mm3.)
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Meyer et al.
IN Distribution Within Columns. In the tangential plane, lateral
borders of cortical columns could be delineated in neuron density
maps within L4 and in IN density maps within L2 (Figs. 2 and 3).
The column delineation based on IN density corresponded to an
“arc-like” surround in the upper supragranular layers with an increased IN density in the septa within L2, and it could also be seen
in the whole-column count experiments (Fig. 3F). The width between the high IN density “arcs” in L2 corresponded roughly to the
barrel width (Fig. 2D), which would also indicate a cylindrical
outline of a cortical column in supragranular layers. This finding
can also be taken as supporting the assumption that cortical columns are relevant functional units in neocortex beyond the cortical
input layer 4 (50–52) [a different view on cortical columns is presented elsewhere (53, 54)].
Molecular Markers PV, SOM, and CR. Several molecular markers
have been used to label putatively distinct subgroups of INs (25, 26,
55, 56). Our data suggest that the coverage of the overall IN
population by PV, SOM, and CR is, at most, ∼75% (Fig. 4). This
number represents an upper estimate, because we labeled for one
marker at a time and coexpression of a second marker is likely to
occur (55). Coverage was extremely low in L1, L2, lower L6A, and
L6B. The PV-, SOM-, and CR-negative INs may be immunoreactive for ionotropic serotonin receptors, which have recently been
shown to be expressed in virtually all SOM- and PV-negative INs
in mouse neocortex (57).
Functional Interpretation. Juxtacellular recordings in vivo from
excitatory neurons in all layers of cortical columns during stimulation of a rat’s whiskers have shown that evoked action potential
firing is extremely low in layers 2 and 5A (5). We argue that our
finding of high IN soma densities in these layers provides evidence for an inhibitory origin of this suppression of activity.
However, we have only quantified IN soma density, and to obtain
correct quantitative predictions of inhibitory innervation density,
the axonal distributions have to be taken into account (58). Although this remains an important issue for future studies, it can
be noted that most INs have a very high perisomatic axon density,
in addition to their specific projection patterns (59). This high
perisomatic axon density predicts strong inhibitory effects in those
layers that have a high density of IN somata.
Outlook. To build detailed mechanistic models of cortical function
(50), single cells representative of distinct anatomically and functionally defined groups of excitatory and inhibitory neurons have
to be placed throughout the layers of a cortical column at sufficient
spatial precision and in the correct quantity. The data on the
number of inhibitory neurons within the layers of a barrel column
reported here, together with data on innervation probabilities and
Meyer et al.
axonal projection patterns (10, 58, 59), will serve as a basis for
reconstructing the inhibitory synaptic circuits within and between
cortical columns.
Materials and Methods
Preparation. Experimental procedures were conducted in accordance with the
German Animal Welfare Act. Wistar rats (aged 25–36 d) of both sexes were
perfused transcardially, and brains were removed and fixed with paraformaldehyde (PFA) as described previously (21). For experiments that included
GABA immunolabeling, animals were perfused with 1 mL/g body weight of
50 mM cacodylic acid and 1% Na-bisulfite (pH 6.2), followed by 0.5 mL/g body
weight of 100 mM cacodylic acid, 1% Na-bisulfite, 4% (g/l) PFA, and 0.3%
glutaraldehyde (postfixation for 2 h). Semicoronal slices of the posteromedial
barrel subfield were cut at a thickness of 50 μm as described previously (21).
Histological Procedures. Slices were double-immunolabeled for the 67-kDa
isoform of GAD67 and NeuN using monoclonal mouse primary antibodies and
isotype-specific secondary anti-mouse IgG antibodies, as described previously
(21). In some experiments, GAD67 and NeuN immunolabeling was combined
with immunolabeling for PV, SOM, or CR; both the 65- and 67-kDa isoforms of
GAD; or GABA. Primary antibodies (all from Chemicon) were used at the following concentrations: 1:800 mouse anti-GAD67 (IgG2a subtype), 1:500 mouse
anti-NeuN (IgG1 subtype), 1:2,000 rabbit anti-PV, 1:4,000 rabbit anti-CR, 1:500
rabbit anti-GAD65/67, or 1:200 rat anti-SOM, treated with an Alexa 488
monoclonal antibody labeling kit (Invitrogen). For PV, CR, and GAD6567
experiments, the following secondary antibodies (all from Invitrogen) were
used: 1:500 goat anti-mouse IgG2a Alexa 488, 1:500 goat anti-mouse IgG1
Alexa 350 or 647, or 1:100 goat anti-rabbit Alexa 555. For SOM experiments,
secondary antibodies (both from Invitrogen) were 1:500 goat anti-mouse
IgG2a Alexa 555 and 1:500 goat anti-mouse IgG1 Alexa 647. They were
incubated at room temperature in phosphate buffer (PB) containing 1.5%
normal goat serum (NGS) for 2–3 h. For GABA experiments, slices were permeabilized and blocked in 0.5% Triton X-100 (TX) (Sigma-Aldrich) in 50 mM
Tris and 1% Na-bisulfite (pH 7.5) containing 4% (vol/vol) NGS for 1.5 h. Primary antibodies (1:800 mouse anti-GAD67, 1:500 mouse anti-NeuN, and 1:250
rabbit anti-GABA; Chemicon) were incubated at 4 °C in 50 mM Tris and 1% Nabisulfite (pH 7.5) containing 1% NGS and 0.5% TX for 42 h. Secondary antibodies (1:500 goat anti-mouse IgG2a Alexa 488, 1:500 goat anti-mouse IgG1
Alexa 647, and 1:100 goat anti-rabbit Alexa 555) were incubated at room
temperature in 50 mM Tris and 8.5 g/L NaCl (pH 7.5) containing 3% NGS and
0.3% TX for 2 h. Slices were mounted on slides, embedded with SlowFade
Gold (Invitrogen), and enclosed with a coverslip.
In some experiments, selected slices were cut at a thickness of 100 μm
and stained for CO (60).
Image Acquisition. Slices were imaged using a BX51 (Olympus) microscope at
a magnification of 4× (N.A. of 0.10). Confocal microscopy using TCS SP2 and
SP5 confocal laser scanning microscopes equipped with a 40× (N.A. of 1.25) oil
immersion objective (Leica Microsystems) and mosaic scanning were conducted as described previously (21). Details are provided in SI Materials
and Methods.
Manual Placement of Soma Markers and Delineation of Cortical Columns and
Layers. 3D soma positions of NeuN-positive neurons were obtained as described
previously (21). Briefly, markers were placed in the center of the somata. To
correct for edge effects at the borders between slices, somata were only
counted if more than half of the soma was imaged (as judged by the diameter
change). We had previously found the systematic error attributable to these
effects to be less than 5% (21). Somata of inhibitory INs were marked in the
GABA and the GAD67 fluorescence channels accordingly, as were somata that
were immunoreactive for molecular markers (PV, SOM, and CR).
The horizontal borders of columns, and layer borders, were determined
based on GAD67 or CO staining, as described previously (21), with the exception
of the L2-to-L3 border. Details are provided in SI Materials and Methods.
Soma Densities and Absolute Soma Counts. Five slices from five hemispheres of
four animals were analyzed (P25: left hemisphere, D2 and C2; P26: right
hemisphere, D2 and C2; P27: right hemisphere, D2 and C2; and P36: right and
left hemisphere, D2 and E2). All the slices contained the center of D2 (n = 5) and
either C2 (n = 3) or E2 (n = 2). Soma distributions were analyzed using custommade software written in MATLAB (MathWorks), as discussed in SI Materials
and Methods.
PNAS Early Edition | 5 of 6
NEUROSCIENCE
population of larger pyramidal cells in L3 of visual cortex (37–39),
a density gradient from L2 to L3 of vertically projecting INs in an
3
H-GABA uptake study (40), or an indication of a density peak in
L2 found in some samples taken from monkey cortex (41, cf. 13,
16–18)]. However, because of the lack of clearly distinguishing
anatomical features under most experimental conditions, L2 and
L3 were treated as one layer (L2/3) in most physiological studies
(e.g., 8, 10, 11, 42–45). Recently, evidence for functional differences in electrical activity between L2 and L3 has accumulated
from different cortical areas, such as somatosensory barrel cortex
(2, 46, 47) and visual cortex (48). Here, we report data that provide
a quantitative basis for a clear anatomical separation of L2 and L3
based on the distribution of the cell bodies of inhibitory neurons.
In a recent counting study in mouse vibrissal cortex, layers 2 and
3 were reported to have almost equal IN density (49). The precise
geometrical alignment of the soma distribution may be critical for
finding distribution patterns of sparse neuron populations, although species difference remains a possible explanation.
ACKNOWLEDGMENTS. We thank Dr. K. L. Briggman for discussions;
M. Kaiser and H. Erdal for technical assistance; Dr. G. Giese for providing
the confocal imaging facility; and Dr. K. Rohm, W. Kaiser, and K. Bauer
for information technology support. We thank A. Ayache, Z. Aydin,
R. Kolibas, S. Moughal, H. Peykarjou, B. Pickard, and G. Quispe for neuron
counting.
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6 of 6 | www.pnas.org/cgi/doi/10.1073/pnas.1113648108
Meyer et al.
Supporting Information
Meyer et al. 10.1073/pnas.1113648108
SI Text
GAD67 vs. Overall GAD Distribution. We found that labeling of
barrels in vibrissal cortex is specific for the 67-kDa isoform of
GAD. Fig. S1A (Left) shows a fluorescence image of a semicoronal slice (50-μm thickness) of vibrissal cortex sliced approximately 2 wk after injection of mOrange-expressing attenuated
adenovirus in the ventral posterior medial nucleus (VPM) of the
thalamus. Barrels can be delineated as patches of dense thalamocortical axon arborization. The same slice was immunolabeled
for the 67-kDa isoform of GAD (Fig. S1A, Right), revealing the
same barrel pattern, as shown previously (1). The subsequent slice
was labeled using an antibody detecting both the 65- and the
67-kDa isoforms of GAD. Barrels in L4 could not be seen in the
GAD6567 stained slice (Fig. S1B, Left vs. Right).
To investigate the origin of GAD immunolabeling patterns
seen at low resolution further, we made confocal images of a slice
(50-μm thickness) that was double-immunolabeled for GAD67
and both isoforms of GAD (GAD65 and GAD67). Maximum
intensity projection images of confocal images recorded at the
L4-to-L5A border are shown in Fig. S1C, Left (GAD67, red) and
Fig. S1C, Right (GAD65/67, green). GAD immunolabeling is
mostly attributable to labeling of synaptic boutons (note the
small puncta of high fluorescence intensity, many of which surround immunonegative excitatory neuron somata; compare with
Fig. 1 B and C). Inhibitory synapses stained by the GAD67 antibody are most dense in barrels of L4, whereas those stained by
the GAD6567 antibody are distributed homogeneously in all
layers of vibrissal cortex except for L1, where inhibitory synapse
density is highest (Fig. S1B, Right).
Quantification of Soma Density Distribution. To quantify soma
density distributions with reference to cortical columns and layers,
landmarks from manual counts representing NeuN-positive (Fig.
2A) and GAD67-positive (Fig. 2B) neuronal somata detected in
single slices were sampled into a 2D matrix (bin size of 50 × 50
μm2), yielding 2D density distribution maps. Fig. S2 shows the
neuron (Fig. S2A) and IN (Fig. S2B) density maps from one slice,
corresponding to the data shown in Fig. 2 A and B. Given the slice
thickness (50 μm), soma density per bin (as illustrated by color in
Fig. S2) can be converted to soma volume densities. Fig. S3 shows
mean excitatory neuron (A) and IN (B) soma density maps (Left)
and the respective SD maps (Right). The sample comprised five
slices from five different hemispheres (5 different D2 columns and
the respective neighboring columns: C2, n = 3; E2, n = 2).
Mean soma density and SD maps of molecular IN markers in the
D2 and C2 columns are shown in Fig. S4 (Fig. S4A: PV, n = 2; Fig.
S4B: SOM, n = 3; and Fig. S4C: CR, n = 3).
The mean maps were smoothed and interpolated for visualization (as shown in Fig. 2 C and D for excitatory neurons and INs
and in Fig. 4 A–C for PV-, SOM-, and CR-positive INs; details
are provided in ref. 1 and SI Materials and Methods).
The molecular marker-positive soma density profiles from individual experiments underlying the smoothed mean profiles in
Fig. 4D are shown in Fig. S5A (thin lines, thick lines represent the
unsmoothed mean profiles). Fig. S5B shows individual (thin lines)
and mean (thick lines) profiles of the molecular marker-to-IN
ratio (analogous to Fig. 4E).
INs in the White Matter. Neurons in the white matter (WM), the socalled “interstitial neurons” (reviewed in 2), have been regarded as
remnants of the subplate zone (3). Three GAD67-stained 50-μmthick slices from three different animals (aged P25, P26, and P36)
Meyer et al. www.pnas.org/cgi/content/short/1113648108
were evaluated for neurons in the WM (Fig. S6). The border between L6 and the WM is visible as a steep drop in GAD67 fluorescence intensity (black arrow in Fig. S6A). The mean thickness of
the WM measured along the vertical column axis was ∼350 μm.
We found a sparse population of WM neurons in all three animals.
Positions of selected WM neurons are indicated (open arrows in
Fig. S6A; the distance from somata to L6 was 45–390 μm). Fig. S6B
shows confocal images (GAD67 antigenicity) of the neurons
marked in Fig. S6A (open arrows in Fig. S6B). All neurons in the
WM were GAD67-positive INs (93 of 93, Fig. S6B). The average
density was 2,554 ± 1,643 per mm3.
Measurement of Neuron Density in Vivo. For comparison of our
estimate of the volume density of neurons and INs with in vivo
neuron densities, tissue shrinkage (mostly attributable to aldehyde
fixation) has to be quantified. We therefore measured neuron
volume densities in L2 of the D2 barrel column in vivo using intrinsic optical imaging and two-photon laser scanning microscopy.
Fig. S7A shows an overview image recorded at the depth of the pial
surface after impregnation of the cortical surface with sulforhodamine. The D2 column outline as delineated based on intrinsic
optical imaging is shown in red. Fig. S7B shows the region outlined
in Fig. S7A (white dashed box) at a depth of 40 μm from the pial
surface. Astrocyte cell bodies are labeled intensely as a result of
sulforhodamine uptake (filled arrowhead in Fig. S7C). At a depth
of 250 μm (Fig. S7C), where neuron density is high (e.g., Fig. 2 A
and E), neuronal somata can be delineated as dark sulforhodamine-negative patches (open arrowhead in Fig. S7C), permitting
manual marking of cell bodies.
SI Materials and Methods
Delineation of Cortical Columns and Layers. In some experiments,
consecutive slices were stained alternately for GAD67 and CO.
CO-derived barrels overlapped with GAD67-derived barrels. In
both CO-stained and GAD67-stained images, the following
outlines were identified: the lateral barrel borders; the pial surface; the layer borders between L1 and L2/3, L2/3 and L4, L4 and
L5A, and L5A and L5B; and the border between L6 and the WM
(Fig. 1A). The 12 intersection points between the lateral barrel
borders, extrapolated to the pia and WM, and the layer borders
were used for further analyses (“column landmarks”).
Column landmarks derived from GAD67 staining varied only
minimally from column landmarks derived from CO staining. The
mean distance between corresponding GAD67 column landmarks
and CO column landmarks was 14 ± 8 μm (Fig. 1A). We routinely
used GAD67 column landmarks derived from the maximum intensity projections of GAD67 confocal scan images for further
analysis. The cytoarchitectonic layer borders were identified by
measuring the half-width at half-maximum of a Gaussian fit (Fig.
2F, Inset). The average depths from the pial surface (cortical
depth) of the GAD67-derived layer borders in the D2 barrel column were (n = 5): L1 to L2/3, 117 ± 16 μm; L2/3 to L4, 530 ± 2 μm;
L4 to L5A, 866 ± 1 μm; L5A to L5B, 1,092 ± 5 μm; and L6 to WM,
2,270 ± 6 μm. For quantification of cell counts (Table 1), layer
borders were defined based on the vertical neuron density profiles
as described previously (1).
The posteromedial edge of the posterior medial barrel subfield
was taken to be the first slice showing major barrels in a complete
series of consecutive slices through the barrel field. Thus, a relation between slicing depth and barrel arc could be established.
The slicing depth of the center of arc 2 was 4.8–4.9 mm.
1 of 6
Image Acquisition. Slices were imaged using a BX51 (Olympus)
microscope at a magnification of 4× (N.A. of 0.10). Confocal microscopy using TCS SP2 and SP5 confocal laser scanning microscopes equipped with a 40× (N.A. of 1.25) oil immersion objective
(Leica Microsystems) and mosaic scanning were conducted as
described previously (1). The voxel size was 0.366 × 0.366 ×
0.610 μm3. In some experiments, a 63× glycerol immersion objective (HCX PL APO CS, N.A. of 1.30; Leica) was used (voxel size:
0.245 × 0.245 × 0.610 μm3). Wavelength selection settings were
370–475 nm for Alexa 350, 495 to 535–550 nm for Alexa 488, 550–
555 to 655 nm for Alexa 555, and 640–660 to 720 nm for Alexa 647.
longitudinal axis of a cortical column, 2D density maps within the
column borders were summed perpendicular to the longitudinal
column axis.
Soma Densities and Absolute Soma Counts. To average data from
different slices, soma markers were rotated to align the mean
vertical D2 column axes, with the pia oriented approximately
horizontally. The markers were then registered to the barrel center
and scaled to a standard column height of 2,000 μm. Some soma
landmarks were flipped around the vertical axis, such that all
the respective neighboring columns (C2 or E2) were aligned to
the right of D2. 2D density maps (bin size of 50 μm2) were calculated and corrected for the scaling to the standard column
height. Density maps were then convolved with a rotationally
symmetrical Gaussian function (σ = 50 μm) and interpolated for
visualization. To calculate vertical soma density profiles along the
In Vivo Experiments. Animal preparation. All experimental procedures were carried out according to the German animal welfare
act. Methods are described in detail elsewhere (4). Briefly, rats
were anesthetized with urethane (i.p. injection, 1–2 g/kg of body
weight), and a 2- to 3-mm-wide craniotomy was opened above
barrel cortex and filled with agarose [type III-A, 1% in normal
rat ringer (NRR); Sigma] and then covered with an immobilized
glass coverslip.
Intrinsic optical imaging. Functional maps of the barrel cortex were
determined using intrinsic optical imaging (5). Images were acquired at a frame rate of 10 Hz (Cascade 512B camera, Photometrics, Roper Scientific). The surface blood vessel pattern was
imaged for reference.
Fluorescence labeling and two-photon imaging. Astrocytes were labeled
with sulforhodamine 101 (6). Two-photon imaging was performed
using a custom-built two-photon laser scanning microscope (870nm excitation wavelength, laser model MaiTai HP; Spectra-Physics). Fluorescence images of 256 × 256 pixels were acquired through
a 20× water-immersion objective lens (0.95 N.A.; Olympus).
1. Meyer HS, et al. (2010) Number and laminar distribution of neurons in a thalamocortical
projection column of rat vibrissal cortex. Cereb Cortex 20:2277e2286.
2. Suárez-Solá ML, et al. (2009) Neurons in the white matter of the adult human
neocortex. Front Neuroanat 3:7.
3. Kostovic I, Rakic P (1980) Cytology and time of origin of interstitial neurons in the
white matter in infant and adult human and monkey telencephalon. J Neurocytol 9:
219e242.
4. Kerr JN, et al. (2007) Spatial organization of neuronal population responses in layer 2/3
of rat barrel cortex. J Neurosci 27:13316e13328.
5. Grinvald A, Lieke E, Frostig RD, Gilbert CD, Wiesel TN (1986) Functional architecture of cortex revealed by optical imaging of intrinsic signals. Nature 324:361e
364.
6. Nimmerjahn A, Kirchhoff F, Kerr JN, Helmchen F (2004) Sulforhodamine 101 as
a specific marker of astroglia in the neocortex in vivo. Nat Methods 1:31e37.
Meyer et al. www.pnas.org/cgi/content/short/1113648108
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A
GAD67
VPM - mOrange
E
E
D
D
C
C
B
B
A
A
500µm
B
VPM - mOrange
E
GAD6567
E
D
C
D
C
B
B
A
A
500µm
C
GAD6567
GAD67
L4
L5A
50µm
Fig. S1. Comparison between GAD67, GAD65/67, and thalamic innervation. (A) (Left) Fluorescence image of a semicoronal slice (50-μm thickness) of vibrissal
cortex sliced approximately 2 wk after injection of mOrange-expressing attenuated adenovirus in the VPM. (Right) Same slice immunolabeled for the 67-kDa
isoform of GAD. (B) Subsequent slice was labeled as in A (Left) and using a GAD65/67 antibody (Right). (C) Slice double-immunolabeled using GAD67 and
GAD6567 antibodies. Maximum intensity projection confocal images at the L4-to-L5A border are shown.
A
B
NeuN
GAD
0
L1
L2/3
L4
1000
L5A
A / B
28 / 6
1500
L5B,
L6
Neuron density
[10³ per mm³]
Depth from pia [µm]
500
2000
0
Fig. S2. Unfiltered soma density maps. Neuron (A) and IN (B) density maps corresponding to the data shown in Fig. 2 A and B obtained from a single slice with
a thickness of 50 μm. Red asterisk indicates a blood vessel.
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A
Excitatory (NeuN-GAD; n=5 slices)
MEAN
S.D.
0
L1
L2/3
500
Depth from pia [µm]
D2
L4
D2
L5A
1000
L5B,
L6
1500
2000
B
Inhibitory (GAD; same slices as NeuN)
MEAN
S.D.
0
500
D2
1000
A / B
165 / 30
1500
2000
Neuron density
[10³ per mm³]
Depth from pia [µm]
D2
0
Fig. S3. Soma density map statistics. Mean excitatory neuron (A) and IN (B) soma density maps (Left) and the respective SD maps (Right) computed from five
slices from five different hemispheres.
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A
B
Parvalbumin (n=2 slices)
MEAN
Somatostatin (n=3 slices)
S.D.
MEAN
S.D.
0
L1
L1
L2/3
L2/3
Depth from pia [µm]
500
D2
C2 L4
D2
D2
C2
L5A
L5A
L5B,
L6
L5B,
L6
D2
C2
C2
1000
1500
2000
C
Calretinin (n=3 slices)
MEAN
S.D.
0
L1
L2/3
D2
C2
D2
C2
L5A
1000
22500 (A); 18000 (B);
12500 (C)
L5B,
L6
Neuron density
[per mm³]
Depth from pia [µm]
500
1500
2000
0
Fig. S4. Molecular IN marker map statistics. Mean soma density (Left) and SD maps (Right) of molecular IN markers in the D2 and C2 columns. PV (A), SOM (B),
and CR (C).
A
B
0
L1
Depth from pia [µm]
L2
PV
SOM
CR
sum
L3
500
L4
L5A
1000
L5B
1500
L6A
L6B
2000
0
10000
Neuron density [per mm³]
0
100
Ratio to all interneurons [%]
Fig. S5. Individual neuron density profiles. (A) Absolute vertical soma density profiles from individual experiments (thin lines) and average (thick lines) used to
compute the profiles in Fig. 4D. (B) Corresponding ratios. (Inset) Color code applies to A and B.
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A
B
0
L1
a
L2/3
c
Depth from pia [µm]
500
L4
b
L5A
d
1000
f
e
1500
L5B,
L6
g
i
2000
j
a
c
b
e
d
f
g
WM
i
h
STR
h
STR j
50µm
Fig. S6. INs in the WM. (A) Maximum intensity projection of a GAD67 immunofluorescence confocal image series (50-μm-thick slice). The black arrow indicates
the border between L6 and WM. Open arrows indicate selected WM neurons. (B) Single-plane confocal images of the neurons shown in A. STR, striatum.
A
pial surface
B
40µm depth
C
250µm depth
50 µm
Fig. S7. Measurement of neuron density in vivo. (A) Two-photon overview image recorded at the depth of the pial surface after impregnation of the cortical
surface with sulforhodamine. The red line represents the D2 column outline as delineated by intrinsic optical imaging. The dashed box shows the region of
interest (ROI) magnified in B and C. (B) ROI (dashed box in A) at a depth of 40 μm from the pial surface. (C) ROI as in B at a depth of 250 μm from the pial
surface. The filled arrowhead indicates an astrocyte cell body; the open arrowhead points to a neuron cell body visible as a sulforhodamine-negative patch.
(Scale bars: 50 μm.)
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