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Volume 17, Number 6,
Issue of March 15, 1997
pp. 2112-2127
Copyright ©1997 Society for Neuroscience
Orientation Selectivity and the Arrangement of Horizontal
Connections in Tree Shrew Striate Cortex
William H. Bosking,
Ying Zhang,
Brett Schofield, and
David Fitzpatrick
Department of Neurobiology, Duke University Medical
Center, Durham, North Carolina 27710
ABSTRACT
- INTRODUCTION
- MATERIALS AND METHODS
- RESULTS
- DISCUSSION
- FOOTNOTES
- REFERENCES
ABSTRACT 
Horizontal connections, formed primarily by the axon collaterals of
pyramidal neurons in layer 2/3 of visual cortex, extend for millimeters
parallel to the cortical surface and form patchy terminations. Previous
studies have provided evidence that the patches formed by horizontal
connections exhibit modular specificity, preferentially linking columns
of neurons with similar response characteristics, such as preferred
orientation. The issue of how these connections are distributed with
respect to the topographic map of visual space, however, has not been
resolved. Here we combine optical imaging of intrinsic signals with
small extracellular injections of biocytin to assess quantitatively the
specificity of horizontal connections with respect to both the map of
orientation preference and the map of visual space in tree shrew V1.
Our results indicate that horizontal connections outside a radius of
500 µm from the injection site exhibit not only modular specificity, but also specificity for axis of projection. Labeled axons extend for
longer distances, and give off more terminal boutons, along an axis in
the map of visual space that corresponds to the preferred orientation
of the injection site. Inside of 500 µm, the pattern of connections
is much less specific, with boutons found along every axis, contacting
sites with a wide range of preferred orientations. The system of
long-range horizontal connections can be summarized as preferentially
linking neurons with co-oriented, co-axially aligned receptive fields.
These observations suggest specific ways that horizontal circuits
contribute to the response properties of layer 2/3 neurons and to
mechanisms of visual perception.
Key words:
orientation selectivity;
topography;
optical imaging;
visual cortex;
surround effects;
tree shrew;
biocytin;
horizontal
connections
INTRODUCTION
Horizontal connections are a prominent feature of
the intrinsic circuitry of the visual cortex. These connections
originate primarily from pyramidal cells, extend for 2-5 mm parallel
to the cortical surface, and terminate in a highly selective and patchy
manner (Gilbert and Wiesel, 1979
, 1983; Rockland and Lund, 1982). A
number of experiments have focused on the relationship between the
patches formed by horizontal connections and well known modular
features of cortical organization such as orientation columns, ocular
dominance columns and cytochrome oxidase-rich blobs (Livingstone and
Hubel, 1984; T'so et al., 1986; Gilbert and Wiesel, 1989; Malach et
al., 1993). The results from these experiments suggest that the patchy
nature of horizontal connections can be explained by a simple rule:
horizontal connections link together select subsets of neurons that
share similar receptive field properties. Studies in both cat and
monkey visual cortex, for example, have shown that horizontal
connections selectively link patches of neurons that have similar
orientation preferences (Gilbert and Wiesel, 1989; Malach et al.,
1993).
The relationship of horizontal connections to another fundamental
aspect of cortical organization
the orderly map of visual spaceis
less clear. This issue is of interest because the axon arbors of
individual neurons are often elongated across the cortical surface,
extending further and giving rise to more terminals along one
axis of the map than others (Gilbert and Wiesel, 1983, 1989; Matsubara
et al., 1985, 1987; McGuire et al., 1991; Kisvarday and Eysel, 1992;
Amir et al., 1993, Malach et al., 1993). Furthermore, the results of
several physiological and perceptual studies have led to the suggestion
that the effects mediated by horizontal connections are not distributed
randomly about a point in visual space, but are aligned along an axis
that corresponds to a neuron's preferred orientation. For example, a
collinear arrangement of horizontal connections has been implicated in
the construction of the elongated receptive fields of layer 6 neurons
in cat striate cortex (Bolz and Gilbert, 1989). Likewise, perceptual
studies of contour integration and physiological studies of receptive field surround effects in layer 2/3 neurons have provided evidence for
facilitatory effects that are much stronger in regions of visual space
that lie along the axis of preferred orientation than in regions that
lie off this axis (Nelson and Frost, 1985; Fiorani et al., 1992; Field
et al., 1993; Polat and Sagi, 1993; Kapadia et al., 1995). Despite the
evidence for anisotropic physiological and psychophysical effects, the
relationship between the axis of elongation of horizontal connections
and the orientation preference of the neurons they interconnect has
never been systematically examined.
In the experiments described here, we have combined optical imaging of
intrinsic signals with small extracellular injections of biocytin to
quantitatively assess both the modular and axial arrangement of
horizontal connections established by neurons of known orientation
preference in layer 2/3 of tree shrew striate cortex. Our results
demonstrate a remarkable degree of specificity for both features of
horizontal connectivity, and suggest several ways that horizontal
connections could contribute to the response properties of layer 2/3
neurons.
MATERIALS AND METHODS
Experimental design. Small extracellular injections
of biocytin were made in 13 animals. Distributions of labeled boutons resulting from the injections were plotted and analyzed manually (3 cases) or with the assistance of a computer reconstruction system and
software routines written in our lab (10 cases, see below for details).
Analysis of modular specificity of the bouton distributions was
accomplished in 7 of these 10 cases by using optical imaging of
intrinsic signals to determine the map of orientation preference in V1
before injection of the biocytin. Analysis of the bouton distributions
with respect to the map of visual space was accomplished in all 13 of
the cases. Optical imaging was also used to investigate the geometry of
the map of visual space in three animals that were not used for
analysis of specificity of connections.
Animal surgery. Tree shrews were initially anesthetized with
a mixture of ketamine hydrochloride (200 mg/kg) and xylazine (4.7 mg/kg) given by intramuscular injection. Atropine sulfate (0.08 mg) was
given sub-cutaneously to reduce secretions. An intraperitoneal cannula
was inserted, the trachea intubated, and the animal was placed in a
modified stereotaxic frame allowing unobstructed viewing of the
stimulus monitor. During surgery, anesthesia was maintained with a 2:1
mixture of N2O/O2 supplemented with 2%
halothane. Body temperature was maintained with a thermostatically
controlled heating blanket. The eyes were kept moist by using planar
contact lenses. An incision was made in the scalp, muscle and fascia
reflected, and the bone overlying visual cortex was thinned by scraping
with a fine scalpel. Wound margins and incisions were treated with a
long-acting local anesthetic (bupivacaine) and pressure points were
treated with a lidocaine ointment. The animal was paralyzed using
pancuronium bromide (0.8 mg initial dose for first 1.5 hr, then 0.2 mg/hr) administered through the intraperitoneal cannula to prevent eye
movements, and artificially respired at a rate and volume sufficient to
maintain expired CO2 at 3-4%. During optical imaging,
halothane levels were reduced to 1%, and the N2O/O2 mixture to 1:1. Any signs of distress
evident in the electrocardiogram or expired CO2 were
treated by immediately increasing the level of halothane.
Optical imaging. Optical imaging of intrinsic signals was
accomplished using an enhanced video acquisition system (Optical Imaging Inc.) applying techniques similar to those of Grinvald and
colleagues (Grinvald et al., 1986; Bonhoeffer and Grinvald, 1991,
1993). Images were obtained directly through the thinned bone overlying
the V1 area. The cortex was illuminated with orange light (605 nm) and
visualized with a tandem lens macroscope attached to a low noise video
camera. Visual stimulation for optical imaging was provided by a
separate stimulus computer (386 PC with SGT+ graphics board and STIM
software provided by Kaare Christian). The stimuli used consisted of
high-contrast square wave gratings (6.25° dark phase, 1.25° light
phase, drifted at 22.5°/sec). Four gratings of orientation 0°,
45°, 90°, and 135° with respect to horizontal were used. Each
grating was moved back and forth along an axis that was orthogonal to
the orientation of the grating. Data were acquired during between 20 and 80 presentations of each stimulus. The summed images acquired
during the presentation of one grating were subtracted from the summed
images acquired during presentation of the orthogonal grating to create
differential maps of orientation preference (difference
images), (Blasdel, 1992). Difference images were 655 × 480 pixels in resolution, with either 62 or 75 pixels per millimeter
depending on the lens combination used. Resulting difference images
were smoothed using a 7 × 7 pixel mean filter kernel. Low
frequency noise was reduced by convolving the image with a 40 × 40 pixel mean filter kernel and subtracting the result from the
original image. Difference images were normalized by dividing the
deviation from the mean at each pixel by the average absolute deviation
across the entire image (Weliky et al., 1995). Finally, vector
summation of the difference images was done on a pixel by pixel basis
to create a color coded orientation preference map
(Bonhoeffer and Grinvald, 1991,1993; Blasdel, 1992).
Optical imaging of the geometry of the map of visual space in V1 was
accomplished using procedures similar to those developed by Campbell
and Blasdel (1995). The technique uses difference imaging for spatial
location to identify areas of cortex that respond preferentially to
stimulation of a particular line in visual space. The stimuli used
consisted of two gratings of the same orientation, each with a period
of 10° but differing in the width and spatial location of the light
phase of the grating (grating 1 = 1° light phase, 9° dark
phase; grating 2 = 3° light phase, 7° dark phase). The two
gratings were placed and moved in such a way that the light phases of
the gratings covered non-overlapping regions of the stimulus monitor
(grating 1 moved ±1° from original position, grating 2 moved ±2°
from original position). Images acquired during presentation of grating
2 were subtracted from images acquired during presentation of grating 1 for each orientation to create topographic difference
images. Topographic difference images were smoothed with a 7 × 7 pixel mean filter kernel for presentation.
At the conclusion of the optical imaging phase of the experiment, a
reference image of the surface blood vessels was acquired, while the cortex was illuminated with green (540 nm) light.
Biocytin injections. Injection sites were selected by
examining the difference images and orientation preference maps to find an area of relatively constant orientation preference. Selected sites
were located using blood vessels visible in the reference image and on
the cortical surface as seen under a surgical microscope. The
orientation tuning of the injection site was confirmed by recording
multi-unit activity through the injection micropipette. Tuning curves
were obtained by averaging responses from 5-8 trials of 9 oriented
stimuli. Iontophoretic injections were made with glass micro pipettes
with a tip diameter of ~10 µm containing 5% biocytin (Sigma, St.
Louis, MO) in saline using pulsed current (7 sec on, 7 sec off) of 2.5 µamps for 10-15 min. After the injection the animal was sutured,
recovered from paralytic and anesthesia, and returned to its cage.
Tissue processing. After a 16 hr recovery period, the animal
was deeply anesthetized with Nembutal (25 mg, i.p.) and transcardially perfused with 0.9% saline, followed by 10% formalin in 0.1 M sodium phosphate buffer. The brain was removed and a
block of cortex containing V1 was flattened while immersed in 20%
sucrose in 0.1 M sodium phosphate buffer and maintained at
4°C overnight. The following day 40 µm tangential sections were cut
from the block on a freezing microtome. Care was taken to collect a
first section that contained outlines of the surface vasculature, so
that the tissue sections could later be aligned with the reference
image. Our procedures for visualization of the biocytin label have been published (Usrey and Fitzpatrick, 1996). Briefly, goat anti-biotin and
biotinylated rabbit anti-goat antibodies (Vector Laboratories, Burlingame, CA) were used to amplify the signal before processing with
the standard avidin-biotin complex (Vectastain Kit PK-4000, Vector,
Burlingame, CA) reaction, and diaminobenzidine with nickel and cobalt
intensification. Visualization of the V1/V2 border was accomplished by
using a Nissl counterstain. Some sections were counterstained before
they were coverslipped, and some sections were counterstained after
bouton distributions were plotted.
Bouton plotting, alignment, and analysis. Blood vessel
outlines in the first tissue section, radial vessel profiles, and
labeled boutons from 2-6 sections were plotted using Neurolucida
software (Microbrightfield, Colchester, VT). In each case, enough
sections were plotted to assess the bouton distribution in the
superficial layers throughout the dorsal region of V1. The data were
stored as a series of x,y coordinates for each
bouton or each blood vessel reference point in the slice. These data
were aligned with the optical imaging data using software routines
written as an extension to the public domain National Institutes of
Health Image program [original version written by Wayne Rasband at
National Institutes of Health and available from Internet by anonymous
ftp from zippy.nimh.nih.gov or on floppy disk from NTIS (5285 Port
Royal Rd., Springfield, VA 22161, part number PB93-504868)]. The
first stage of the alignment was to align the computer drawing of the
first tissue section to the reference image acquired during optical
imaging. Global scaling, rotation, and x,y
translations were applied to the stored coordinates to achieve the best
overall alignment possible, with emphasis placed on the area of the
slice containing the injection and bouton data. The second stage of the
alignment was to align deeper tissue sections, containing labeled
boutons, to an overlay of the first section drawing and reference image
by using the profiles of blood vessels that course radially through V1.
As in the first stage, only global scaling, rotation, and translations were used to align the section. At the end of this procedure, the same
transformations used to align the blood vessel reference points in deep
sections were then applied to the bouton data (coordinates). This
allowed direct comparison of the bouton distributions with the map of
orientation preference, which was in the exact same field of view as
the reference image. Bouton distributions were not compared with the
map of orientation preference until the completion of the alignment
process.
Bouton tuning curves were obtained by counting the number of
boutons that contacted sites with various orientation preferences using
10° bins of orientation preference. Bouton tuning curves were
computed separately for boutons that were greater or less than 500 µm
from the injection site. Axial specificity was assessed by counting the
number of boutons within each 10° sector around the injection site,
excluding the boutons that were within 500 µm of the injection site.
Profiles showing the number of boutons versus distance were obtained
for both preferred and orthogonal axes (±30°). Maximum distance of
projection along the preferred and orthogonal axes were determined by
calculating the maximum distance that a minimum density of 40 boutons/0.01 mm2 could be found.
Three of the cases used for determination of axial specificity were
plotted using an alternative system that did not allow the use of the
extended National Institutes of Health Image routines for alignment and
analysis. For these cases, the bouton distribution was plotted from
superficial sections containing layer 2/3, and the V1/V2 border was
plotted in thionin stained sections from layer 4. The border was then
transferred to the layer 2/3 plots by using the position of radial
blood vessel profiles. The number of boutons within 10° sectors
around the injection site was then counted manually. Similar results
were obtained by both methods, but density, distance profiles, and
maximum distance calculations were not attempted using the manual
counting method.
RESULTS
In the next sections, we describe the results from experiments
designed to examine the distribution of biocytin-labeled terminals with
respect to the map of orientation preference and the map of visual
space in striate cortex (V1) of the tree shrew. In the first section we
begin by considering the basic features of the orientation preference
map that are relevant for understanding the quantitative assessment of
modular specificity.
Maps of orientation preference in tree shrew striate cortex
Previous studies demonstrated that neurons in the superficial
layers of tree shrew striate cortex are sharply tuned to the orientation of edges (Humphrey et al., 1980a); moreover, on the basis
of 2-deoxyglucose (2-DG) labeling, it was suggested that neurons with
similar orientation preferences were arranged in a series of parallel
bands or stripes that intersected the V1/V2 border at right angles
(Humphrey et al., 1980b). If the 2-DG experiments have provided an
accurate picture of the layout of iso-orientation domains, then the map
of orientation preference in the tree shrew would be considerably
different from what has been described in monkeys and cats (Bonhoeffer
and Grinvald, 1991, 1993; Blasdel, 1992). However, the difference could
also be attributed to the fact that the results in these other species
are based on more recently developed optical imaging techniques. These
techniques provide a more detailed assessment of the map because they
permit the comparison of the patterns of activity evoked by multiple stimulus orientations in the same region of cortex. A complete analysis
of the map of orientation preference in the tree shrew striate cortex
based on optical imaging techniques will be presented elsewhere; here
we simply describe the basic features of the map and emphasize that the
arrangement of orientation preference maps in the striate cortex of the
tree shrew, monkey, and cat are fundamentally similar. Orientation
selectivity was also observed in V2 of some animals, although the
signal strength in V2 was much weaker for reasons that remain unknown.
The functional organization of orientation selectivity and connections
in V2 are not explored in this paper.
Our optical imaging experiments confirm some of the features described
in the 2-DG experiments. For example, in almost all of the orientation
difference images, we found regions of the cortex that had the
appearance of parallel alternating dark and light stripes (Fig.
1A). These stripes were common in the
most caudal part of the exposed surface and along the V1/V2 border where they intersected the border at right angles. However, other parts
of the map were decidedly less stripe-like in appearance; in the center
of the exposed surface, for example, the stripes were often replaced by
a less regular and more punctate set of domains. Furthermore, a
comparison of the patterns of activity evoked by different stimulus
orientations revealed that even those regions of the map that had a
stripe-like appearance in images generated for one stimulus orientation
would often appear to break up into discontinuous patches in images
generated for other stimulus orientations. Taken together, these
observations suggested that the map of orientation preference in the
tree shrew is far more complex than was indicated by the earlier 2-DG
experiments.
Fig. 1.
Optical imaging of intrinsic signals in tree
shrew visual cortex. A, Difference images obtained for
four stimulus angles (0°, 45°, 90°, 135°, shown in
inset of each panel) from one animal. Black areas
of each panel indicate areas of cortex that were preferentially activated by a given stimulus, and light gray areas
indicate areas that were active during presentation of the orthogonal
angle. The dashed line in the 90° panel indicates the
approximate location of the V1/V2 border. B, Orientation
preference map obtained by vector summation of data obtained for each
angle. Orientation preference of each location is color-coded according
to the key shown below. C,
Common features of the orientation preference maps. Portions of the
orientation preference map shown in B have been enlarged
to demonstrate that the orientation preference maps contained both
linear zones (left) and pinwheel arrangements
(right).
[View Larger Version of this Image (109K GIF file)]
The fine-scale mapping of orientation preference is best appreciated by
combining the individual difference images using vector summation to
create an orientation preference map where colors are used to represent
the preferred orientation at each site (Fig. 1B).
This analysis confirms that the map of orientation preference in the
tree shrew has the same basic organizational features that have been
described previously in monkey and cat striate cortex (Bonhoeffer and
Grinvald, 1991, 1993; Blasdel, 1992). In many regions of the map,
commonly referred to as pinwheels, a continuous shift in orientation
preference is obtained by sampling around a point, or singularity.
Examples of two pinwheels from the orientation preference map shown in
Figure 1B are shown at higher magnification in Figure
1C. Linear zones, regions of the map in which a progressive change in orientation preference is obtained by sampling along a
straight line (Blasdel, 1992; Obermayer and Blasdel, 1993), are also a
prominent feature of orientation preference maps in the tree shrew. As
predicted from the difference images, linear zones are common along the
V1/V2 border and along the caudal edge of the dorsal portion of V1.
They can extend for 2-3 mm, a distance that covers several full
repeats of the orientation cycle. In Figure 1, A and
B, an especially large linear zone is visible in the caudal
portion of the map, and this same linear zone has been enlarged in the
left hand side of Figure 1C.
Modular specificity of horizontal connections
To assess the modular specificity of horizontal connections,
combined optical imaging and biocytin injection experiments were accomplished in seven animals. After the optical imaging phase of the
experiment, an injection site was selected and the orientation tuning
of the injection site was confirmed by recording multi-unit activity
through the injection pipette. Our biocytin injections resulted in the
labeling of a small number of cell bodies (12-65) that were confined
to sites that were typically less than 200 µm in diameter (average
diameter 176 µm, largest diameter 320 µm; see Fig.
2A,B). In two of our
cases, one or two retrogradely labeled cells could be found at some
distance from the injection site, but this did not hamper our ability
to detect the underlying specificity of the connections. The axonal
processes of the labeled neurons were well labeled (Fig. 2C)
and exhibited the characteristic bouton terminal swellings that have
been described in other species (Gilbert and Wiesel, 1983; Amir et al.,
1993; Kisvarday and Eysel, 1992). As seen in Figure
2A, labeled axons extended away from the injection
site for several millimeters and gave rise to prominent patches.
Borders of bouton patches were determined subjectively and by
thresholding a density plot of the bouton distributions. The two
methods were in good agreement and the average size of bouton patches
was determined to be ~400 µm × 250 µm. This information is
provided for comparison with other reports only; the borders of bouton
patches were not used in the analysis of modular or axial specificity.
The distribution of labeled boutons was plotted from between two and
six sections for each case.
Fig. 2.
Biocytin injections made into superficial layers
of V1. A, Low-power image showing an injection site,
labeled axons leaving the site, and several patches formed by axon
arbors. Radial vessel profiles used in aligning tissue sections are
also visible. Scale bar, 100 µm. B, The same injection
site seen in A shown at higher power. Individual cells
that have taken up the biocytin can be identified. Scale bar, 25 µm.
C, A patch of biocytin label shown at higher
magnification. Labeled boutons are visible on the axons. Scale bar, 25 µm.
[View Larger Version of this Image (104K GIF file)]
The interpretation of our findings rests on the accuracy with which we
are able to align plots of labeled boutons from the anatomical sections
with optical maps of orientation preference. For this reason, the steps
in the alignment process are illustrated in Figure 3.
This first stage of the alignment process was to align a drawing of the
blood vessels found in the first section (shown in yellow in
Fig. 3A) to the reference image taken during the optical
imaging session (grayscale image in the
background of Fig. 3A). The second stage
consisted of aligning deeper sections (shown in blue in Fig.
3A), that contained labeled boutons, to the first section
using profiles of blood vessels that course radially through the depth
of the cortex. Only global scaling, translation and rotation operations
were used during both stages of the alignment (no regional alignments
were made and no morphing of the data were used). Emphasis was placed
on getting the best alignment for the area of the sections that
contained the injection site and labeled boutons. The inset of Figure
3A demonstrates the degree of accuracy we were able to
achieve in this process. Based on overlays such as those in Figure 3 we
estimate errors in alignment of up to 50-100 µm at specific
locations far removed from the injection sites, but no systematic
errors throughout the section. After the alignment procedure,
difference images or orientation preference maps were substituted for
the reference image, and the actual bouton distribution was substituted
for the blood vessel pattern.
Fig. 3.
Alignment of bouton distributions to optical
imaging data (case 9509). A, The image in the
background is a reference image taken during the optical
imaging phase of the experiment. The yellow overlay is a
computer-assisted drawing of blood vessel outlines and radial vessel
profiles seen in the first tissue section. The drawing has been scaled,
rotated, and translated to align with the reference image. The
blue overlay is a computer-assisted drawing of radial
vessel profiles and the section outline from a deeper section that
contained labeled boutons. This section has been independently scaled,
rotated, and translated to align with the reference image and the first
tissue section. The precision of both stages of the alignment can be
seen in the inset. B, Same animal and
field of view as seen in A. The reference image has been
replaced with a difference image showing areas active for a 90°
stimulus in black. Bouton distribution information has been added
using the same transforms used to align the blue section in A. The green symbols indicate cells
that took up and transported the biocytin. Red symbols
indicate locations of labeled boutons. Scale bar, 400 µm for
inset in A.
[View Larger Version of this Image (131K GIF file)]
Figure 3B shows the results of the alignment process
presented in Figure 3A. The injection in this case was made
into a site that responded preferentially to edges with an orientation
near vertical. The tuning curve based on multi-unit activity showed a
peak at 80° and a half width at half height of 19°. The
distribution of labeled boutons that resulted from the injection is
shown superimposed on a difference image in which black regions
represent areas that were strongly activated by a vertical stimulus
(90°) and white regions represent areas that were strongly activated
by a horizontal stimulus (0°). Except for the region immediately
adjacent to the injection site, there is a striking correspondence
between the distribution of labeled terminals and the regions of the
orientation map that respond strongly to vertical edges.
A better appreciation of the range of orientation preferences of the
sites contacted by a given set of horizontal connections can be gained
by examining the bouton distributions displayed over a color-coded
orientation preference map. Figure 4A
illustrates this comparison for the same case that is depicted in
Figure 3 (preferred orientation of the injection site = 80°);
Figure 4B illustrates a case in which an injection
was made into a site with a preferred orientation near horizontal (peak
of tuning curve 160°, half-width at half-height 28.5°). In each
case, beyond the area immediately adjacent to the injection site, the
labeled boutons are clustered in regions that have orientation
preferences similar to that of the injection site.
Fig. 4.
Bouton distributions shown over orientation
preference maps for two cases. A, Bouton distribution
after an injection into a site with a preferred orientation of 80°,
determined by recording through the same tip used to make the injection
(same case as in Fig. 3). The white symbols indicate the
location of cells that took up the biocytin. Labeled boutons
(black symbols) are found at sites with all orientation
preferences near the injection site, but preferentially at sites with
the same orientation preference as the injection site at longer
distances. B, Results from an experiment in which an
injection was made into a site with an orientation preference of 160°
(case 9517). Color key and scale bar apply to both figures.
[View Larger Version of this Image (96K GIF file)]
To quantify the relationship between the bouton distributions and the
orientation preference maps, we generated "bouton tuning curves"
that show the number of labeled boutons that overlie a particular range
of orientation values in the orientation preference map. In each case
examined, the bouton tuning curves for boutons found at distances
greater than 500 µm from the injection site showed a clear peak at or
near the preferred orientation of the injection site (Fig.
5). In general, the tuning curves for boutons found at
distances less than 500 µm from the injection site were considerably
broader (Fig. 5A,B) but, in some
cases, specificity for sites that were at or near the preferred
orientation was still present (Fig. 5C).
Fig. 5.
Quantitative analysis of modular specificity of
bouton distributions. The number of boutons that overlie a particular
10° range of orientation preference is shown separately for boutons that are found <500 µm from the injection site (gray
curves) and those found at >500 µm distance (black
curves). In each case, for the boutons found at >500 µm, a
peak is seen at or near the preferred orientation of the injection
site.
[View Larger Version of this Image (23K GIF file)]
Modular specificity of long-distance horizontal connections (greater
than 500 µm from the injection site) is summarized for four cases in
Figure 6. For each case, the orientation tuning curve
based on multi-unit activity at the injection site is shown in Figure
6A, and the bouton tuning curve is shown in Figure
6B, plotted in the same color. In each case, there is
a striking correspondence between the peak in the injection site tuning
curve and the peak in the bouton tuning curves. This relationship is
even more apparent when the bouton tuning curves are expressed in terms
of the difference between the orientation preference of the sites
contacted by labeled boutons and the peak of the orientation tuning
curve for multi-unit activity at the injection site. This is done for
all seven of our cases in Figure 6C, where the gray lines
represent individual cases and the black line represents the median for
the group. Each of the bouton tuning curves is centered on or near the
preferred orientation of the injection site. By summing the percentage
of boutons found in the seven center bins of the median curve, we determined that 57.6% of the boutons contact sites with an orientation preference within ±35° of the preferred orientation of the injection site. For individual cases, between 48.2 and 72.6% of the boutons met
this restriction. This percentage of boutons is significantly different
from the percentage expected for an even distribution that would
contain ~5.56% of the boutons in each of the 18 bins (dashed
line in Fig. 6C), resulting in 38.9% of the boutons
found within ±35° (p < 0.02, Wilcoxon signed
rank test).
Fig. 6.
Correspondence between orientation tuning of
injection sites and specificity of bouton distributions for four cases.
A, Orientation tuning curves determined from recordings
of multiunit activity that were made through the biocytin-filled
pipettes at each injection site. Normalized responses are plotted
versus stimulus orientation. B, Bouton tuning curves for
the same cases shown in A, plotted in the same color as
A. For each case, the percentage of the total number of
boutons that overlie sites with a given orientation preference is
plotted. Only boutons found at distances >500 µm from the
injection site were used in this analysis. Each curve has a peak at or
near the peak of the physiologically determined tuning curve shown in
A. C, Data from all seven of our combined imaging and biocytin injection experiments. The bouton tuning curves
for each case are expressed as the percentage of the boutons that
contact sites that differ in orientation preference from the injection
site by a specified amount. Individual cases are shown in
gray, and the median is shown in black.
The dashed line shown at 5.56% reflects the percentage
of boutons expected in each of the 18 bins if the boutons were
distributed evenly over the map of orientation preference.
[View Larger Version of this Image (26K GIF file)]
Axial specificity of horizontal connections
Before describing our analysis of axial specificity of horizontal
connections it is necessary to describe the organization of the map of
visual space in tree shrew V1. As illustrated in Figure
7A, the tree shrew has a well developed
striate cortex with a prominent V1/V2 border that is clearly discerned
in Nissl-stained sections. An earlier physiological study by Kaas et
al. (1972) demonstrated that, as in other species, the V1/V2 border
corresponds to the representation of the vertical meridian in visual
space. The horizontal meridian, as well as other iso-elevation lines, intersects this border at approximately right angles (Kaas, 1980).
Fig. 7.
The map of visual space in tree shrew V1.
A, Photomicrograph of a Nissl-stained section of visual
cortex. V1 stands out clearly as the darkly stained
region of the section. B, Topographic difference images
for four stimulus angles. The dark bands and
light bands ~0.5-1.0 mm wide in each image reflect
areas of cortex that were differentially activated by the two grating
patterns for that stimulus angle (see Materials and Methods for
details). The distance between a pair of dark or light bands
corresponds to 10° in the map of visual space. The 0° and 90°
images represent iso-elevation and iso-azimuth lines. C,
Diagram of the right visual field and left visual cortex of the tree
shrew, modified from a figure by Kaas (1980). Lines at 45°
orientation (black line) and at 135° orientation
(gray line) are shown as they would appear in the visual field and in the cortex.
[View Larger Version of this Image (61K GIF file)]
To confirm the geometry of the map of visual space, we used optical
imaging with a stimulation paradigm similar to one developed by
Campbell and Blasdel (1995). The technique uses difference imaging for
spatial location with two gratings of the same orientation to identify
areas of cortex that respond preferentially to stimulation of a
particular line in visual space (see Methods for details). Data
obtained from one animal using this technique to visualize 0°, 45°,
90°, and 135° lines in the map of visual space are shown in Figure
8B. Similar results were obtained in
two other animals. Results from these experiments were in general
agreement with earlier mapping studies (Kaas et al., 1972; Kaas, 1980).
The map of visual space presented in Figure 7C has been
slightly modified from one originally presented by Kaas (1980) to
reflect the geometry and spacing of iso-azimuth and iso-elevation lines
as measured by optical imaging.
Fig. 8.
Bouton distributions from four cases. The
preferred orientation for each case is shown in the top
right of each panel. The axis in cortex corresponding to the
preferred orientation is indicated by the gray rectangle
underlying each distribution. Each point indicates an
individual bouton. Note the dense distribution of boutons found near
the injection site and more patchy distribution found at longer
distances. In each case, the distribution is elongated along an axis
that corresponds to the preferred orientation of the injection
site.
[View Larger Version of this Image (38K GIF file)]
Figure 7, B and C, confirms that the map of
visual space is largely isotropic near the center of V1, and all of our
injections were placed in this area. In addition, they illustrate that
it is possible to specify the axis in cortex that corresponds to a
particular axis in the visual field by simply rotating the appropriate number of degrees from the V1/V2 border axis. For example, Figure 7C depicts a 45° axis (black lines) and 135°
axis (gray lines) as they would appear in both the
right visual field and the left visual cortex. Thus, the presence of a
prominent V1/V2 border and the lack of large distortions in the map of
visual space greatly facilitate the examination of axial specificity of
horizontal connections in the tree shrew.
As described in other species, injections of biocytin into layer 2/3
resulted in a distribution of labeled terminals that was elongated
across the cortical surface. The axis of elongation was found to vary
from case to case and was systematically related to the orientation
preference of the injection site. This basic relationship can be
appreciated by examining the distribution of labeled terminals compared
to an outline of V1 as is done for four cases in Figure 8. In each
panel, the axis of elongation of the labeled terminals can be compared
to the V1/V2 border (vertical meridian). As illustrated in Figure
8A, an injection into a site with a preferred
orientation near vertical resulted in a distribution of labeled
terminals that was elongated parallel to the V1/V2 border. In contrast,
an injection into a site with a preferred orientation of near
horizontal (Fig. 8C) resulted in a distribution that was
elongated perpendicular to the V1/V2 border. In each of the cases that
we examined, we found a similar relationship: layer 2/3 neurons give
rise to horizontal connections that extend for longer distances, and
give rise to more boutons, along an axis of the visual field map that
corresponds to their preferred stimulus orientation.
Quantification of the systematic relationship between the axis of
elongation of the terminal distributions and the preferred stimulus
orientation of the biocytin injection sites is illustrated in Figures
9, 10, 11. The polar plots
in Figure 9 illustrate the number of labeled terminals found in
successive 10° sectors surrounding an injection site for the same
four cases shown in Figure 8. In these plots, the distance of each
point from the center of the circle indicates the relative number of
boutons found in that 10° sector. The 0° sector for each polar plot
was assigned by drawing a line through the center of the injection site
orthogonal to the V1/V2 border. Sectors were then assigned in a
clockwise manner, resulting in the 90° sector corresponding to an
axis that is parallel to the V1/V2 border. With this reference scheme,
the distribution of labeled terminals across the visual field map can
be compared directly to the preferred stimulus orientation recorded
from the units at the injection site (shown to the upper right of each
plot). In each case, the dominant axis of the terminal polar plot
matches the preferred stimulus orientation recorded from the site
before the injection.
Fig. 9.
Quantification of bouton distributions for four
cases. For each case, the number of boutons found in successive 10°
sectors around the injection is quantified. Distance from the origin
indicates the number of boutons found in a given sector normalized to
the maximum number of boutons found in any sector for that case. The 0° sector was assigned by drawing a line through the injection site
that was orthogonal to the V1/V2 border, and the remaining sectors were
assigned in clockwise manner. Only boutons outside of 500 µm were
used in this analysis. The preferred orientation of the injection site
for each case is indicated by the black bar in each
inset. The thin gray line in the visual
field diagrams and the gray dashed lines in the polar
plots correspond to the vertical meridian.
[View Larger Version of this Image (30K GIF file)]
Fig. 10.
Correspondence between preferred orientation of
injection sites and the axial specificity of the bouton distributions.
A, Polar plots are shown for all 13 cases examined for
axial specificity. Each polar plot was constructed as described in
Figure 9 and is color-coded according to the orientation preference of
the injection site for that case. The black curve is the
median of the 13 cases. B, Data from all 13 cases were
combined by rotating each curve by a number of degrees equal to the
orientation preference at the injection site for that case. Gray
lines indicate individual cases, and the black line
indicates the normalized median of all 13 cases.
[View Larger Version of this Image (154K GIF file)]
Fig. 11.
Quantification of elongation of bouton
distributions. A, Number of boutons versus distance in
100 µm bins along both the preferred (black curve) and
orthogonal (gray curve) axes (±30°). Preferred orientation for this case was 40°. B, Same information
shown for a case that had a preferred orientation of 160°.
C, Scatterplot showing the maximum distance at which
boutons were found to exceed a minimum density of 40 boutons/0.01
mm2 along the preferred and orthogonal axes (±30°) for
10 cases. Dashed lines indicate equal distance along
preferred and orthogonal axes.
[View Larger Version of this Image (17K GIF file)]
Our sample of injection sites from 13 cases included a wide range of
preferred stimulus orientations, and for each orientation we found a
corresponding bias in the axial distribution of labeled terminals.
Figure 10A shows the terminal polar plots for all 13 of our cases and illustrates that each injection resulted in a distribution with a distinct axial bias. The degree to which the variation among cases in the axial alignment of terminal distributions is a function of the preferred stimulus orientation of the injection site is illustrated in Figure 10B. In this figure,
the terminal polar plots have been aligned by rotating them by an angle
that corresponds to the difference between the preferred stimulus
orientation of the injection site and horizontal (0°). For example,
the bouton distribution for a site with a preferred stimulus
orientation of 22° was rotated clockwise by 22°. Individual
profiles are illustrated by the gray curves and the black curve
represents the median for all of the cases examined. On average,
neurons in layer 2/3 give rise to four times as many terminals along an
axis that corresponds to their preferred stimulus orientation (±35°)
than along the orthogonal axis (±35°).
The axial bias in the distribution of connections is reflected not only
in the number of labeled terminals, but in the distance of the labeled
terminals from the injection site. Labeled boutons were consistently
found to extend greater distances from the injection site along the
axis of the visual field map that corresponds to their preferred
stimulus orientation. This feature of the bouton distributions is
illustrated for two cases in Figure 11, A and B,
that plot the number of boutons versus distance along either the
preferred or orthogonal axes. To further quantify this relationship we
determined the maximum distance along the preferred and orthogonal axes
(±30°) at which a minimum density of 40 boutons/0.01 mm2
was exceeded for each case. For the case shown in Figure
11A, the maximum extension along the preferred axis
was 3.73 mm and the maximum extension along the orthogonal axis was
0.96 mm. This information is shown for all 10 cases for which the
required data were available in Figure 11C. The maximum
distance at which boutons were found along the preferred axis (median
1.77 mm) was significantly different from the maximum distance along
the orthogonal axis (median 1.16 mm; p < 0.004, Wilcoxon signed rank test).
DISCUSSION
The results of this study confirm the results of previous studies
in cats and monkeys showing that long-range horizontal connections selectively link patches of neurons that have similar orientation preferences (Gilbert and Wiesel, 1989; Blasdel et al., 1992; Malach et
al., 1993). In addition, our results reveal a new feature of long-range
horizontal connections that has not been described before:
orientation-specific anisotropy. Horizontal connections in the tree
shrew extend for greater distances and distribute more terminal boutons
along an axis of the visual field map that corresponds to the preferred
orientation of the injection site. In the next sections we relate these
results to those of previous studies and consider the implications of
modular and axial specificity for understanding the function of
horizontal connections.
Modular specificity of local and long-distance
horizontal connections
Our results demonstrate that long-distance horizontal connections
in V1 have a strong bias toward connecting regions with similar
orientation preferences, and a degree of specificity that is
commensurate with the orientation tuning of the neurons they interconnect. In several cases, for example, bouton tuning curves, constructed from an analysis of the position of boutons relative to the
orientation map, were remarkably similar in both their peak and
half-width to the physiologically defined orientation tuning curves for
multi-unit activity at the injection site (compare tuning curves in
Fig. 6A, B). In addition, the peak
of the median bouton tuning curve constructed from all of the cases was
centered on the preferred orientation of the injection site and 57.6%
of the labeled boutons contacted sites with a preferred orientation that was within 35° of the peak. This degree of specificity is comparable to that reported for long-range horizontal connections in
macaque V1 (Malach et al., 1993).
Although, for technical reasons, it proved more difficult to
characterize the orientation specificity of boutons located within 500 µm of the injection site, on the whole, these local connections appear less specific than their long-distance counterparts. In many
cases, for example, a nearly uniform halo of labeled terminals surrounded the biocytin injection site and the tuning curves for the
local bouton distribution were correspondingly flat. Because we did not
plot boutons inside the area of the injection site that contained
labeled cell bodies and dendrites, it is likely that we have
underestimated the degree of iso-orientation connectivity of local
connections. Nevertheless, unlike long-range connections, labeled
terminals near the injection site are located in regions of the
orientation preference map that include the full range of values.
Observations from macaque visual cortex also suggest a lower
specificity for local horizontal connections (Amir et al., 1993; Malach
et al., 1993).
The difference in specificity of local and long-distance connections
could reflect a difference in the relative contribution of excitatory
and inhibitory neurons. Previous studies have shown that, compared to
excitatory connections, inhibitory connections in layer 2/3 extend for
shorter distances (Albus et al., 1991; Matsubara and Boyd, 1992; Albus
and Wahle, 1994), are less specific for orientation domains (Kisvarday
and Eysel, 1993; Kisvarday et al., 1994;), and tend to be more
uniformly distributed around the injection site (Albus et al., 1991;
Matsubara and Boyd, 1992; Albus and Wahle, 1994). Thus, it is possible
that the distribution of boutons that we observe results from a
nonspecific ring of connections contributed by GABAergic neurons that
is superimposed upon the more specific connections established by
pyramidal neurons. Clearly, determining the actual contribution of
these two classes of neurons to the pattern of local connections will
require an analysis at the single cell level.
Axial specificity of horizontal connections
This is the first demonstration of an anisotropy in horizontal
connections which varies from site to site and is systematically related to the orientation selective responses of cortical neurons. Previous studies in visual cortex of cats and macaque monkeys have
noted that horizontal connections tend to form distributions that are
elongated along a particular axis, and in some cases the observed
anisotropy in horizontal connections was explained in terms of a
corresponding anisotropy in the map of visual space (McGuire et al.,
1991; Yoshioka et al., 1992; Amir et al., 1993; Malach et al., 1993;
Grinvald et al., 1994). These authors reported that horizontal
connections appear to consistently extend for longer distances along
the vertical axis of the map of visual space, corresponding to the fact
that cortical magnification factor (amount of cortical surface area per
unit visual space) is greatest along this axis. However, other
investigators have reported elongated distributions which could not be
explained by the anisotropy in the map of visual space (Gilbert and
Wiesel, 1983, 1989; Kisvarday and Eysel, 1992). Thus, the exact extent
to which anisotropies in the map of visual space, or other factors,
determine the distribution of horizontal connections has remained
unclear.
A global feature like magnification factor cannot explain the
consistent relationship between orientation preference and axis of
elongation in the tree shrew. Nevertheless, it might account for some
of the variability that we observed in the absolute amount of
elongation along the preferred axis. For example, some of the most
elongated distributions in the tree shrew had axes that ran parallel to
the V1/V2 border, whereas some of the least elongated ran perpendicular
to the border. We did not observe a consistent relation between map
anisotropy and degree of elongation, but this relationship might have
been obscured by other factors such as the size and placement of the
injection site, or variations in the quality of biocytin uptake and
transport.
An axial alignment of horizontal connections related to orientation
preference was first suggested by Mitchison and Crick (1982) as an
explanation for the observation that injections of tracers in V1
produce patchy labeling, even when the injection is large enough to
involve sites with a wide range of orientation preferences. Using
computer simulations, they showed that if the network of horizontal
connections was constrained by just one rule of "like connects to
like" then a continuous distribution of label would result from a
large injection. On the other hand, if two rules requiring axial and
modular specificity of horizontal connections were used to model
horizontal connectivity, then a patchy distribution of label would
result from a large injection. The demonstration of combined modular
and axial specificity in the tree shrew, and the observation of patchy
distributions of labeled neurons after large tracer injections in V1 of
many species, suggests that modular specificity alone might be
insufficient to explain the distribution of horizontal connections.
Indeed, preliminary results, using combined optical imaging and
biocytin injections, suggest that a combined modular and axial
specificity might be present in the squirrel monkey (Sincich and
Blasdel, 1995). It is possible that a relationship between preferred
orientation and axis of projection also exists in cats and other
primates but is difficult to demonstrate due to other factors such as
large anisotropies in the map of visual space.
Functional implications
Combined with the evidence that horizontal connections are largely
reciprocal (Kisvarday and Eysel, 1992), these results indicate that
individual neurons in layer 2/3 receive input from other neurons whose
receptive fields are co-oriented (of similar orientation preference)
and co-axial (displaced along an axis in visual space that corresponds
to their preferred orientation; Fig.
12A,B). This relationship raises the possibility that horizontal connections might
contribute to the orientation selectivity of layer 2/3 neurons. For
example, a neuron that responds best to a vertical stimulus might do
so, at least in part, because it receives input from a network of other
layer 2/3 neurons whose receptive fields are aligned along the vertical
axis of visual space. This arrangement could be viewed as the
intracortical equivalent of the Hubel and Wiesel model in which layer 4 neurons derive their orientation selectivity by sampling from a
population of lateral geniculate nucleus neurons whose receptive fields
are aligned along an axis in visual space (Hubel and Wiesel, 1962).
Presumably, the intrinsic circuitry in layer 2/3 acts in concert with
orientation selective inputs derived from layer 4 to generate the
orientation selectivity of layer 2/3 neurons. Indeed, the contribution
of axially aligned horizontal connections could explain why layer 2/3
neurons in the tree shrew and ferret are more tightly tuned for
orientation than those in layer 4 (Humphrey et al., 1980a; Chapman and
Stryker, 1993). It could also explain why many neurons exhibit sharper orientation tuning (a smaller half width at half height) when longer
stimuli are used to determine tuning (Henry et al., 1974).
Fig. 12.
Summary of specificity of horizontal connections
in V1. A, Example of axon arborizations from two cells
shown over a combined map of visual space and difference map of
orientation preference. The dark regions of the
difference map indicate regions that prefer 90°, and the
lighter areas indicate areas that prefer 0°. A neuron found in a dark region of the map projects to other areas of the map
with the same orientation preference and that lie along a line
corresponding to a vertical line in the map of visual space. A neuron
found in a light region of the map (orientation preference 0°)
projects to other parts of the cortex that prefer 0° and that lie
along a horizontal line in the map of visual space. B,
Input to layer 2/3 cells via horizontal connections. Because horizontal connections are largely reciprocal, cells in layer 2/3 will receive input from other layer 2/3 cells with the same orientation preference, the receptive fields of which are displaced along a line in visual space. The solid rectangles indicate the receptive
fields of the two cells shown in A. The open
rectangles indicate the receptive fields of cells that would
provide input to these two cells via horizontal connections. Nearby
cells with overlapping receptive fields are omitted for
clarity.
[View Larger Version of this Image (27K GIF file)]
Because of their extensive spread, horizontal connections have
been implicated as one of the potential substrates for receptive field
surround effectschanges in the response pattern of neurons produced
by visual stimulation of the region that lies outside of the receptive
field as defined by a small, simple stimulus (for review, see Gilbert,
1992). In the tree shrew, for example, these connections extend for up
to 4 mm from the injection sitea distance that corresponds to
~20° of visual spacewhereas the classically defined receptive
field at this eccentricity extends for less than 5°. The results of
the present study suggest that horizontal connections could be the
source of a particular class of receptive field surround effects that
exhibit axial specificity, exerting a greater influence in regions of
visual space that lie along the axis of the neuron's preferred
orientation (i.e., end-zones) than along the orthogonal axis
(side-zones). Effects of this type have been described in both cat and
monkey striate cortex and in several cases the effects are primarily
facilitatory (Nelson and Frost, 1985; Fiorani et al., 1992; Kapadia,
1995). Some neurons in macaque visual cortex, for example, show an
enhanced response to placement of an additional stimulus outside the
receptive field (Kapadia et al., 1995); this enhancement occurs only
when the additional element is at the preferred orientation and
collinear with the stimulus placed in the receptive field. Neurons in
layer 2/3 of tree shrew striate cortex also exhibit long range axially specific facilitatory effects. For example, many layer 2/3 neurons in
the tree shrew exhibit length summation, showing an increase in
response with increasing stimulus length for stimuli as long as 40°.
In addition, stimulation of the end-zones alone, without stimulation of
the classical receptive field, is sufficient to drive some layer 2/3
neurons, whereas stimulation of the side-zones is ineffective (Bosking
and Fitzpatrick, 1995).
Long-range collinear facilitatory effects could serve as one of
the important mechanisms that underlies the perception of continuity in
visual patterns. Indeed, the perception of continuity appears to depend
critically on the very features that characterize long-range horizontal
connections. For example, the ability of human observers to detect
contours composed of small oriented line segments from among an array
of distracter elements is dependent upon both the orientation and
position of the elements (Field et al., 1993). Observers are much
better at detecting a contour composed of multiple segments when the
segments are aligned with the path of the contour than when they are
aligned orthogonal to the path. Similarly, detection of an oriented
line segment or a grating is enhanced by flanking the stimulus with
other collinear stimuli (Polat and Sagi, 1993; Kapadia et al.,
1995).
Thus, the modular and axial specificity of horizontal connections
seems well suited for supporting the perception of contours, especially
under noisy or degraded stimulus conditions.
FOOTNOTES
Received Aug. 5, 1996; revised Dec. 9, 1996; accepted Dec. 12, 1996.
This work was supported by National Eye Institute Grant EY06821. We
thank Martha Foster for expert assistance with histology and plotting
of bouton data, Mike Weliky for assistance with software, and Len
White, Michele Pucak, and Justin Crowley for comments on this
manuscript.
Correspondence should be addressed to William H. Bosking, Box 3209, Department of Neurobiology, Duke University Medical Center, Durham, NC
27710.
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