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Volume 16, Number 20,
Issue of October 15, 1996
pp. 6443-6453
Copyright ©1996 Society for Neuroscience
Development of Orientation Preference Maps in Ferret Primary
Visual Cortex
Barbara Chapman1,
Michael P. Stryker2, and
Tobias Bonhoeffer1
1 Max Planck Institute for Psychiatry, 82152 Munich-Martinsried, Germany, and 2 W. M. Keck Center for
Integrative Neuroscience, Department of Physiology, University of
California, San Francisco, California 94143-0444
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
FOOTNOTES
REFERENCES
ABSTRACT
The development of orientation preference maps was studied in
ferret primary visual cortex using chronic optical imaging of intrinsic
signals. The emergence and maturation of the maps were examined over
time in single animals. The earliest age at which cortical domains
selectively responsive to particular stimulus orientations were
observed varied considerably between individuals, from postnatal day 31 to 36. In all cases, the earliest maps seen were low-contrast, with
regions of orientation-specific activity that were difficult to
distinguish from noise. These early maps matured over a period of
several days into the high-contrast, patchy maps typical of adult
animals. The structure of the orientation maps was remarkably constant
over time. The indistinct features in the earliest maps were always
patches of the same sizes and shapes and at the same locations as in
the maps obtained in subsequent recording sessions. Details of the more
mature maps, including the relative intensities of individual
iso-orientation domains, were also constant from one recording session
to another over periods of several weeks. The patterning of
iso-orientation domains in ferret primary visual cortex thus is
established early in development and remains stable over time,
unaffected by either normal visual experience or the anatomical
rearrangements of geniculocortical afferents into eye-specific
domains.
Key words:
orientation map;
development;
ferret;
optical
imaging;
visual system;
cortex;
activity dependence
INTRODUCTION
Neurons are arranged with precise organization in
the primary visual cortex of adult mammals. Radial columns of cortical
cells have similar response properties, and receptive field properties,
such as orientation preference, are mapped rather smoothly across the
cortical surface (Hubel and Wiesel, 1962 ). Despite a long history of
experiments addressing the emergence of these ``cortical maps,'' it
is still not clear how this organization develops and what role visual
experience plays in this process.
The tangential organization of orientation preference in primary visual
cortex was first studied using extracellular electrophysiology (Hubel
and Wiesel, 1962 ); later maps across cortex of the response to a single
stimulus orientation were obtained using 2-deoxyglucose (2-DG)
metabolic labeling techniques (Hubel et al., 1977 ; Albus, 1979 ;
Schoppmann and Stryker, 1981 ; Singer, 1981 ; Thompson et al., 1983 ;
Löwel et al., 1987 ). More recently, the details of cortical
orientation maps have been studied using the technique of optical
imaging (Blasdel and Salama, 1986 ; Grinvald et al., 1986 ; Ts'o et al.,
1990 ; Bonhoeffer and Grinvald, 1991 ; Weliky et al., 1995 ), which
provides a number of advantages over more conventional methods. Optical
imaging of intrinsic signals allows responses to visual stimuli to be
observed across a wide area of cortex simultaneously and also provides
map information at a much higher spatial resolution than is possible
using electrophysiological recording (Swindale et al., 1987 ). In
addition, optical imaging allows the cortical responses to many
different stimuli to be studied in the same area of cortex in the same
experiment, which is not possible using metabolic labeling techniques
such as 2-DG or cytochrome oxidase labeling.
Relatively little is known about the development of orientation
preference maps in primary visual cortex. The development of
orientation tuning at the single-cell level has been widely studied
(monkey: Wiesel and Hubel, 1974 ; cat: Hubel and Wiesel, 1963 ; Barlow
and Pettigrew, 1971 ; Blakemore and Van Sluyters, 1975 ; Buisseret and
Imbert, 1976 ; Frégnac and Imbert, 1978 ; Albus and Wolf, 1984 ),
but the single-unit electrophysiological results do not reveal anything
about either the timing of map development or the tangential
organization of early orientation maps. Metabolic labeling techniques
such as 2-DG or cytochrome oxidase can provide some information about
the early organization of the developing maps (LeVay et al., 1978 ; Des
Rosier et al., 1978 ; LeVay et al., 1980 ; Thompson et al., 1983 ), but
individual differences between animals in the onset of orientation
development and in the patterning of the maps make these results
difficult to interpret. Both electrophysiological recording experiments
and 2-DG labeling studies can provide information only at a single time
point in a given animal; therefore, these methods cannot be used to
determine whether orientation maps are stable during development or
whether the maps are continually rearranging. Obtaining an answer to
this question is of considerable importance because it has profound
implications for models of the development of response properties in
visual cortex.
To examine the emergence, organization, and stability of orientation
preference maps during development, we have developed a chronic method
of optical imaging of intrinsic signals in very young animals. This
technique allows orientation maps to be studied over long periods of
time in individual animals. At the single-cell level, orientation
tuning properties of cells in primary visual cortex previously have
been found to mature very early in development. In the monkey,
orientation tuning is adult-like at or soon after birth (Wiesel and
Hubel, 1974 ); in the cat, maturation of orientation tuning occurs in
the first few weeks of life (for review, see Blakemore and Van
Sluyters, 1975 ; Freeman and Ohzawa, 1992 ). Optical imaging experiments
in young monkeys so far have been limited to acute experiments and have
confirmed that orientation maps are essentially adult-like at the
earliest ages examined (Blasdel et al., 1995 ). Such acute experiments
can, of course, not address the questions of map emergence or
stability. Chronic optical imaging studies have been performed in
kittens, but they have proved very difficult because of the fragility
of the young animals (Kim and Bonhoeffer, 1993 ). To be able to perform
chronic experiments during the time period of orientation map emergence
and maturation, we have chosen the ferret as the experimental animal.
Ferrets have a visual system that is quite similar to that of the cat
(Law et al., 1988 ) and that develops at a similar rate from conception
(Linden et al., 1981 ). However, the gestation period in the ferret is
42 d compared with 65 d in the cat, so that at a stage of
visual system development equivalent to day of birth in the cat, the
ferret is already 3 weeks old. Ferrets thus provide a physiologically
robust preparation during the time period when orientation tuning at
the single-cell level is maturing (Chapman and Stryker, 1993 ). Using
chronic optical imaging of intrinsic signals in the ferret, we have
been able to study the development in individual animals of the maps of
orientation preference in primary visual cortex from before the first
emergence of iso-orientation domains through the time at which
orientation maps are fully mature.
MATERIALS AND METHODS
Optical imaging of intrinsic signals was used to examine the
normal development of orientation maps over time in single animals. A
total of 13 ferret pups (Marshall Farms, New Rose, NY) was used in
these experiments. Imaging was performed through the intact dura to
maintain an optimal physiological state over the course of multiple
imaging sessions lasting several weeks. Maps of the distribution of
cortical activity at each age were generated in response to moving
square-wave gratings at each of four orientations: horizontal,
vertical, and the two obliques.
Optical imaging. Each optical imaging recording session was
performed under aseptic conditions. Anesthesia was induced using a
mixture of xylazine (2-4 mg/kg) and ketamine (20-40 mg/kg) injected
intramuscularly. Atropine (0.1 mg/kg) was injected subcutaneously.
Animals were intubated, and anesthesia was maintained using halothane
delivered in a 3:1 mixture of nitrous oxide:oxygen. Ventilation was
adjusted to a rate and volume providing peak inspiratory pressure at
1.5 kPa and end-tidal carbon dioxide at 3.8-4.2%. Animals were placed
on a heating pad to sustain a core temperature of 38°.
Electroencephalogram, electrocardiogram, end-tidal carbon dioxide,
arterial oxygen saturation (SpO2), and rectal temperature
were monitored throughout the experiment. Subcutaneous injections of
~1 ml of 5% dextrose Ringer's/hour were administered to prevent
dehydration.
The animals were placed in a modified kitten stereotaxic apparatus. In
the initial recording session for each animal, the scalp was incised
and retracted. A craniotomy was performed over the caudal pole of the
left hemisphere. The dura remained intact. In subsequent recording
sessions, the incision was reopened, the agar plug (see below) was
removed from the craniotomy, and the dura was carefully cleaned using
sterile cotton swabs.
Before imaging, 2% agar and a glass coverslip were applied over the
craniotomy. Atropine and neosynephrine eye drops were used to dilate
the pupil and paralyze accommodation, and to retract the nictitating
membrane. Animals were fitted with contact lenses to focus the eyes on
the monitor placed 33 cm in front of the animal. Visual stimuli were
produced using custom-made software (STIM, Kaare Christian, Rockefeller
University) and presented on the monitor. These stimuli consisted of
drifting, square-wave gratings (drift velocity 10-15°/sec) at a
spatial frequency chosen empirically to optimize the activity signal
(This spatial frequency varies with age probably because of changing
optics in the ferrets' maturing eyes.) and were presented at four
different orientations: horizontal, vertical, and the two obliques.
Visual stimuli were presented binocularly during the recording sessions
in five of eight animals; in the other three animals, motor-controlled
shutter eye occluders were used to produce monocular stimuli.
The brain was illuminated through the dura using bandpass-filtered
light at 605 ± 10 nm (Grinvald et al., 1986 ; Frostig et al.,
1990 ). Images of the intrinsic signals produced by neuronal activity in
response to the different visual stimuli were captured using a cooled
charge-coupled device camera (Princeton Instruments) focused ~500
µm below the cortical surface. Five frames of 600 msec duration were
collected during each 3 sec stimulus presentation, followed by a 7 sec
interstimulus interval. For analysis, the first frame was discarded. In
most experiments, each stimulus was presented 128 times, with different
stimuli randomly interleaved.
After each recording session, the agar and coverslip were removed and
the craniotomy was flushed with sterile saline and covered over with a
3% agar plug containing broad-spectrum antibiotics. The fascia and
scalp were sutured closed, and the scalp wound was infused with
lidocaine and covered with topical iodine. The animal was then allowed
to recover from anesthesia before being returned to its mother and
littermates. After the final recording session, the animals were
euthanized with an overdose of barbiturate.
Orientation maps. Single-condition activity maps: Signal
averaging was used to reduce noise in the acquired images. To extract
from the images only the small changes attributable to the visual
stimulation and to remove nonstimulus-specific signals such as uneven
illumination or blood-vessel artifacts, each orientation activity map
was divided by a ``cocktail blank'' consisting of the sum of the
images produced in response to all orientations (for details, see
Bonhoeffer and Grinvald, 1993 ). Activity maps were calculated for
responses to drifting square-wave gratings presented at horizontal,
vertical, and the two obliques.
Angle and polar maps: To obtain a more comprehensive picture of the
mapping of orientation preference across the cortical surface, the
information from the single-condition activity maps for all four
orientations of stimuli was combined into single, color-coded
orientation preference maps using vectorial addition on a
pixel-by-pixel basis. In ``angle maps,'' the vector angle is
displayed as the hue of each pixel, indicating only the preferred
orientation. In ``polar maps,'' the vector angle is again displayed
as the hue of each pixel (indicating the preferred orientation), and
the vector length is additionally encoded as the brightness of the
color (indicating the strength of orientation tuning) (for details, see
Bonhoeffer and Grinvald,
1993 ).
Fig. 1.
Development of orientation maps revealed by
chronic optical imaging. Single-condition orientation maps, angle maps,
and polar maps recorded at six different ages in one animal. Each row
of the figure shows orientation maps recorded in the left primary
visual cortex of one ferret at the age indicated at the
left of the row. Each column of single-condition maps
shows orientation maps recorded in response to a particular orientation
of a moving square-wave grating (0° = horizontal). For each map,
caudal is up and medial is to the left. The curve
in the upper left corner of each map indicates the
location of the caudal pole of the cortex behind which the skull
remained intact over the cerebellum. The approximate location of the
area 17/18 border can be seen in each image as a line
rostral to which no orientation activity is seen. In this example, the
first clear orientation maps can be seen at P33. Early maps are
stronger for horizontal and vertical orientations than for the two
obliques. Individual iso-orientation domains remain stable over time
and do not change their position, shape, or size. The four red
arrows shown in each horizontal single-condition map highlight
this stability by pointing to particular features in the map. The
information from activity maps in response to all four orientations of
stimuli are combined into a single color-coded angle and polar map
using vectorial addition on a pixel-by-pixel basis. In angle maps, the
hue of each pixel indicates the preferred orientation of cells at that
location in cortex. The hue coding scheme is shown to the
right of the figure. In polar maps, the hue again
indicates the preferred orientation, whereas now the brightness of the
color also indicates the strength of orientation tuning. At early ages,
the polar maps are almost completely dark, indicating that there were
no regions of the cortex that showed tightly tuned orientation-specific
responses. As the maps mature, iso-orientation domains become visible
as colored regions in the map. These domains become more strongly
responsive over time, and more domains appear as the maps mature. Scale
bar, 2 mm.
[View Larger Version of this Image (106K GIF file)]
Fig. 2.
Concurrent development of all orientation maps.
Single-condition orientation activity maps from a second ferret. In
this animal, activity maps for all orientations developed at the same
rate. Note that in this ferret the first orientation maps are visible
at a substantially later time (P36) than in the example shown in Figure
1. All conventions as in Figure 1.
[View Larger Version of this Image (124K GIF file)]
Fig. 3.
Orientation similarity plots. Orientation
similarity plots for two animals. For both animals, plots comparing
early maps with the most mature maps are shown. For ferret 1-6-3630, control data comparing early maps with the mature map from a different
animal are shown. Ferret 1-3-3630 is the animal illustrated in Figure
1. Scale bar, 1 mm.
[View Larger Version of this Image (53K GIF file)]
Fig. 4.
Stability of orientation maps. The maximum
similarity index calculated from the orientation similarity plots (see
Fig. 3) for all animals at all ages is shown. Filled
squares show within-animal comparisons and open
squares show between-animal (control)
comparisons. The height of the histogram bars indicates the mean of the
maximum orientation similarity indices for each animal at all ages.
Gray squares indicate data from immature maps recorded
before P35. Additional control data showing the comparison of mature
maps in each animal with a map consisting of randomized pixels is shown
at the far right.
[View Larger Version of this Image (17K GIF file)]
Fig. 5.
``Disorganized'' activity maps seen in one
animal. Single-condition activity maps from one animal in which
orientation activity maps did not have the usual spotty or stripy
appearance seen in the other ferrets in this study. Instead, maps
appeared ``disorganized.'' This structure of the map was real, as it
was reproducible between experiments performed at different ages of the
animal. It was not attributable to blood vessel artifacts, as shown by
the photographs of the cortical surface showing blood vessel patterns
illustrated in the right-most column. There are some
blood vessel artifacts in these maps (one example is indicated by the
arrowheads in the maps recorded at P39), but they are
easily discernible and they do not account for the observed activity
pattern. Scale bar, 2 mm.
[View Larger Version of this Image (125K GIF file)]
Fig. 6.
Spatial structure of orientation preference maps.
A, Two-dimensional spatial auto-correlograms are shown
for mature single-condition orientation maps in each animal. Scale bar,
1 mm. B, Histogram of the angle between the angle of the
best-fitting sine-wave grating and the area 17/18 border for all
animals.
[View Larger Version of this Image (45K GIF file)]
Fig. 7.
Comparison of the development of orientation
tuning assessed by optical imaging and electrophysiology.
A, Orientation tuning derived from polar maps for each
animal at each age studied. Solid curves show the
best-fit cumulative Gaussian sigmoid curve for individual animals. The
dashed line indicates the best-fit curve for data from
all eight animals. The time of eye opening for each animal is also
indicated. Although orientation maps did begin to appear about the time
of eye opening, note that early eye opening was not always correlated
with early development of maps. B, Orientation tuning
assessed electrophysiologically from single-unit recordings compared
with optical imaging of the development of orientation tuning.
Single-unit data from Chapman and Stryker (1993) . Mean orientation
tuning indices derived from orientation tuning histograms collected
from single-unit recordings are shown for 16 animals of different ages.
Note that values of this orientation tuning index greater than 25-30
correspond to a significantly biased response in
favor (Figure legend continues)
of one orientation. Values of this index measured on neurons
in the lateral geniculate nucleus of the ferret were <25; the median
value for neurons in primary visual cortex of the cat was 55-60
(Chapman and Stryker, 1993 ). The solid curve indicates
the best sigmoid-fit curve through these data. The best-fit curve for
the optical imaging data (dashed line) is replotted from
Figure 7A for comparison. The mean of the best-fit
sigmoid for the electrophysiological data is 4 d earlier (P33.4)
than the mean for the optical imaging data (P37.4).
[View Larger Version of this Image (21K GIF file)]
Cross-correlation analysis. Single-condition orientation
maps from young animals were compared with mature single-condition maps
by computing the cross-correlation between the maps. As a first step in
this analysis, a region of interest (ROI) was determined for each
animal to isolate only the area of the maps where orientation-specific
activity was seen in the mature map. Information from the portion of
the images outside the ROIs (including the image of the skull posterior
to the caudal pole and the area of cortex anterior to the 17/18 border)
was not considered in the analysis. The cross-correlograms were
produced by calculating the correlation coefficient between two maps of
similar orientation preference at x- and
y-offsets of 30 to 30 pixels (each pixel corresponds to 36 µm across the cortical surface). This two-dimensional array of
correlation coefficients then allowed us to get a meaningful measure of
the degree of correlation between two maps even if they were not
perfectly aligned.
Two-dimensional mean orientation similarity analysis. To
assess map stability, early angle maps were compared with mature maps
in each animal. As a control, maps obtained in each animal were also
compared with mature maps from different animals.
This analysis consists of a comparison between two maps. As a first
step in this analysis, ROIs for each map were determined as described
above. Next, at each pixel within the intersection of ROIs, the
difference between the preferred orientations in the two angle maps was
calculated, to range between 0 (no difference in the orientation
preference at that point) and 90 (the maximum possible difference
between orientation preferences). The mean angle difference over all of
the pixels within the intersection of ROIs was then calculated. To
produce the two-dimensional plots, the two maps being compared were
shifted across each other horizontally and vertically in one-pixel
steps, and the mean orientation difference was calculated for each
relative position of the two maps. Each pixel in these two-dimensional
plots shows the mean orientation difference for a particular relative
position of the two maps being compared.
The maximum mean orientation difference present in these plots
was used to quantify the similarity between maps. These values were
divided by 90 and subtracted from one to produce an index of similarity
of two orientation maps, which varies between 0 and 1. If two identical
maps are compared by this method, the orientation similarity index is
one. If two maps are completely anticorrelated, with exactly orthogonal
orientation preference at each point, the similarity index is zero.
Comparison of two maps with no correlation in angle preference yields a
similarity index of 0.5.
Auto-correlation analysis. Two-dimensional auto-correlations
were performed on mature single-condition maps to determine the spatial
structure of the maps and to assess the degree to which the maps were
banded (stripy) as well as the angle of iso-orientation bands with
respect to the area 17/18 border.
The auto-correlograms were produced exactly as described above for the
cross-correlograms, only the maps were correlated with themselves.
Two-dimensional auto-correlations were also performed on
single-condition maps from earlier recording sessions to determine the
periodicity of iso-orientation domains. After producing
auto-correlograms for each condition at each age, periodicity was
assessed by determining the sine wave grating that showed the best fit
to the auto-correlation of the map. The spatial period of this sine
wave grating was then taken as a good estimate of the mean periodicity
of the map.
Orientation tuning analysis. Analysis of the development of
orientation tuning was done by using the median length of the vectors
in the polar maps as a measure for orientation tuning. This calculation
was again only performed within the ROI.
RESULTS
Chronic optical imaging experiments were performed in 13 juvenile
ferrets. In three animals, multiple optical imaging recordings
completed very early in development, between postnatal day (P) 26 and
29, showed no evidence for orientation-specific activity in the primary
visual cortex at these ages. In eight animals, it was possible to
perform four or more optical imaging sessions between P31 and P55; data
from these animals are reported in this paper. Shorter data series that
confirmed the conclusions drawn from these eight animals were obtained
in two additional ferrets between P32 and P40.
A complete set of orientation maps from one developing animal, ferret
1-3-3630, is shown in Figure 1. The left side of this figure shows the
activity maps obtained in this animal in response to four orientations
of drifting square-wave gratings, and the right side of the figure
shows angle and polar maps. Each row in the figure illustrates the maps
obtained at a given age during development. In this and all subsequent
figures, each map is presented with caudal up, medial to the left. The
area of the images exhibiting orientation-specific activity corresponds
to the exposed region of area 17. Blank areas where no activity maps
can be seen result from the skull, which remained intact behind the
caudal pole of cortex in the upper left corner of each image, or from
cortical areas rostral to the approximate location of the 17/18 border,
which did not respond to the visual stimuli used in this study. In the
single-condition maps, areas of cortex that respond to a given stimulus
appear dark, whereas nonresponsive areas are light. In the angle and
polar maps, information from the four single-condition maps is combined
to show how orientation preference is arranged across the cortex, with
each hue representing a different preferred orientation; in polar maps,
information about the strength of orientation tuning is additionally
encoded as color brightness.
In ferret 1-3-3630, illustrated in Figure 1, little or no
orientation-specific activity is seen in the single-condition maps at
the earliest age of imaging, P31. By P33, iso-orientation domains are
clearly visible, at least in response to vertical and horizontal
stimuli. Orientation activity maps continue to become stronger over
time, reaching adult-like clarity by P42, the final recording session
in this animal. This progression of development is also shown in the
polar maps for this animal, where the increasing brightness of the
color of the maps with age indicates an increase in the strength of
orientation tuning as the animal matures.
Single-condition orientation maps for a second animal, ferret 1-5-413, are shown in Figure 2. The same general pattern of development was seen
in this animal, with early faint activity maps at P36 developing into
mature maps by P41. The timing of development in ferret 1-5-413 was
quite different, however, with little or no orientation-specific
activity seen at P34, when relatively good maps were already present in
ferret 1-3-3630.
The first age at which iso-orientation domains were visible in ferret
primary visual cortex varied considerably among animals, from P31 to
P36. In all animals, however, the earliest observed maps were
low-contrast, with orientation domains difficult to distinguish from
noise. The maps then matured over several days' time into the
high-contrast, patchy orientation maps seen in adult animals. The
initial emergence of orientation maps occurred about the time of
natural eye opening, which varies considerably between individuals in
the ferret. However, there was no clear correlation between the age of
first visual experience and the timing of map emergence. In some
animals, the eyes were surgically opened at the time of the initial
optical imaging session and very faint maps were already seen, whereas
in other animals no activity maps were seen for several days after the
eyes had opened naturally.
In addition to the inter-animal variability in the timing of map
development, early development of iso-orientation domains responding to
horizontal and vertical stimuli was seen in some, but not all, animals.
An example of this early development of horizontal and vertical
responses occurred in the animal illustrated in Figure 1, in which
horizontal and vertical maps could be seen at P33, whereas oblique maps
did not appear until P35. In contrast, in the animal illustrated in
Figure 2, responses to all orientations of stimuli were first seen at
P36 and appeared to mature at the same rate. The tendency for
horizontal and vertical maps to develop early is fully discussed
elsewhere (Chapman and Bonhoeffer, 1994 ).
Perhaps the most striking property of the developing orientation maps
in ferret primary visual cortex is their constancy over time. Features
of orientation domains that can barely be distinguished in the earliest
maps are always present as patches of the same size, shape, and
location in later recording sessions from the same animal. Fine
features of the more mature maps, including the relative intensities of
individual patches of iso-orientation activity, are also stable over a
period of several weeks, the longest time investigated in our study.
This stability of the maps over time can be seen in all of the maps
presented in this paper, and it was also evident in all of the other
ferrets studied. This stability is evident in Figure 1, and it is
highlighted by the use of arrows pointing to particular map features
that can be clearly seen at all ages of development. For example, the
top right arrow points to an elongated region of cortex that responded
strongly to horizontal stimuli. This region is constant in location and
shape in the five maps obtained between P33 and P42 and may even have
been present at P31, where little orientation-specific activity was
seen.
As a first, obvious step in quantifying the stability of the
orientation preference maps obtained from developing ferret visual
cortex, a cross-correlation analysis was used to compare early
single-condition maps in each animal with the most mature maps obtained
for that animal (data not shown). The two-dimensional cross-correlation
analysis did reveal both the stability of the maps over time and the
increasing strength of orientation tuning in the cortex during
development, which is seen qualitatively in the single-condition maps.
Map stability was evident in the similar spatial structure of the
correlation plots obtained at each age, and maturation of tuning was
seen as an increase in the maximum correlation of the maps with
age.
However, cross-correlation of the single-condition maps with mature
maps was not an ideal method for measuring either map stability or
tuning maturation. Because the strength of tuning in the maps heavily
influenced the correlation coefficient, the analysis could not be used
to produce a stability metric. Because horizontal and vertical
orientation preferences develop earlier than oblique preferences in
some animals (Chapman and Bonhoeffer, 1994 ), the cross-correlation
analysis also could not produce a single measure to assess the strength
of orientation tuning at a given age, because cross-correlations were
higher for horizontal and vertical single-condition maps in those
animals. Therefore, new analyses were devised to measure these
developmental features. The orientation similarity index used to
measure map stability is described below and illustrated in Figures 3
and 4; the measurement of orientation tuning is described in the
Discussion and illustrated in Figure 7.
To develop a quantitative measure of stability, early angle maps in
each animal were compared with the mature angle map in the same animal.
This comparison, unlike the single-condition map cross-correlation
analysis, is independent of map strength because angle maps only show
preferred orientation without containing any information about tuning
strength. To perform the angle map comparison, orientation similarities
between the early and the mature map were determined at each point. The
mean orientation similarity was then calculated across the map. Because
the two maps may not have been in perfect spatial alignment with each
other, the mean orientation similarity between the maps was calculated
at relative offsets of the two maps, ranging from 30 to 30 pixels in
the x and y directions (each pixel corresponds to
36 µm across the cortical surface). Two-dimensional plots of mean
orientation similarities were thus produced for each map comparison. As
a control, the developing maps in each animal were compared with the
mature map from another animal. Examples of such orientation similarity
plots are shown for two animals in Figure 3. For ferret 1-6-3630, both
the analysis and the control plots are shown; for 1-3-3630, only the
analysis is shown because the controls for all animals were very
similar. The locations of the ``hot spots'' near the centers of
orientation similarity plots show the relative position at which the
two angle maps were best aligned. The high values of orientation
similarity at these hot spots indicate the high degree of similarity in
the maps being compared. For both animals, at early ages when little or
no orientation-specific activity was seen, the plots lack convincing
hot spots, showing the anticipated low similarity of essentially blank
maps with the mature maps. For ferret 1-6-3630, developing maps after
P33 were very similar to the mature maps, indicating a very high degree
of stability. Although the magnitude of the similarity was smaller for
the earlier maps, the spatial structure of the plot was the same even
at P35, when the orientation map first emerged, indicating that the
earliest map already had similar organization to the mature map. The
control plots shown for this animal reveal that, as expected, maps from
one animal were not very similar to the mature map seen in a different
animal. For ferret 1-3-3630, the magnitude of the similarity shown at
P33 was low, but already above control, indicating that in this animal
as well, maps were stable throughout development. The spatial structure
of the early plots for this ferret, however, was quite different from
that seen for more mature maps. This is because, as shown in Figure 1,
horizontal and vertical maps in this animal developed earlier than
oblique maps, so that the spatial components of the plot that reflect
the oblique maps were missing at early ages.
The maximum value of the two-dimensional mean orientation similarity
plots was used as a measure of map stability, as illustrated in Figure
4. In this figure, the orientation similarity index for each age is
shown for each animal as a filled square, with the height of the
histogram bar indicating the mean. Gray squares show similarity indices
calculated for maps obtained at early ages (before P35). Open squares
show control orientation similarity indices calculated by comparing
maps obtained at each age with the mature map from a different animal;
the height of the bar again indicates the mean. For all animals
studied, the degree of similarity between early and mature maps was
high at all ages except in some cases at the earliest time points where
little or no orientation-specific activity was seen. There is only one
case in which there is any overlap between the real orientation
similarities for maps obtained after P35 and the control orientation
similarities; this exception is seen for ferret 1-1-4479, which was not
respirated at the earliest time points, resulting in poor activity
maps. In contrast, little similarity was seen between maps in one
animal and maps in another animal, shown by the control bars in the
histogram. This small degree of similarity, however, was larger than
the similarity seen between real angle maps and random pixel maps,
which is shown in the right-most bar of the histogram. The slight
similarity seen between maps from different animals presumably is a
reflection of the similar width of orientation ``stripes'' between
animals and the tendency of these stripes to run perpendicular to the
17/18 border in all animals (see below).
The developing orientation maps seen in different animals varied
considerably in their spatial structure. In some animals, including
that illustrated in Figure 1, the maps appeared somewhat spotted,
whereas in other animals, including that illustrated in Figure 2,
single-condition maps were more stripy in appearance. In one of the
eight animals studied, ferret 1-3-413, the orientation maps looked
quite disorganized. Single-condition maps for this animal are shown in
Figure 5. Images of the blood vessel pattern on the surface of the
brain photographed at each age are shown on the right side of the
figure. These images allow blood vessel artifacts (an example of which
is indicated by the arrows in the P39 maps) to be
identified. Despite the odd appearance of the maps, these maps were
clearly real representations of orientation preference and not
artifactual, because individual features of the maps are present at all
ages studied. Therefore, the orderly appearance of maps published
elsewhere (Blasdel and Salama, 1986 ; Grinvald et al., 1986 ; Ts'o et
al., 1990 ; Bonhoeffer and Grinvald, 1991 ; Weliky et al., 1995 ) is not
seen in all instances, at least in the ferret. Even so, this ferret did
exhibit the same stability of map features during development as was
found in all of the animals in this study (see Fig. 4). In addition,
examination of the angle maps obtained in this ferret and all of the
animals studied (see examples in Fig. 1) reveals that orientation
preference maps in ferret primary visual cortex are similar to those
seen in other species, with relatively smooth mapping of orientation
across the cortex punctuated by ``pinwheels.''
One feature observed in the animals that had the more stripy patterns
of orientation maps was a tendency of the stripes to run perpendicular
to the area 17/18 border. To quantify this effect, all four mature
single-condition maps from all eight animals were examined. Spatial
auto-correlograms were performed on each map to reveal any
anisotropies. These auto-correlograms are shown in Figure
6A. Long, straight bands of anticorrelation
(blue-black) were present in the auto-correlograms made from
maps that were stripy, whereas a more circular or cross-shaped pattern
is seen in other maps. To determine the relationship between the
iso-orientation stripes and the 17/18 border, the best-fitting sine
wave grating to each correlogram was determined, and the angle of this
sign wave with respect to the 17/18 border was measured. Results of
this analysis are shown in Figure 6B. The histogram
indicates that in the majority of maps, iso-orientation stripes tend to
run perpendicular to the areal border, and in no maps do the stripes
run parallel or near-parallel to the border.
Auto-correlograms were also produced for all of the earlier maps
obtained in each animal to determine the spacing of orientation stripes
during development. The average periodicity seen in the grouped data
from all animals at all ages studied was 872 ± 65 µm. Analysis
confirmed that the spacing seen in orientation maps was very constant
during development, as was expected from observation of the maps and
from the high degree of stability shown by the orientation similarity
index. The changes seen in periodicity within individual animals varied
from 3 to 12%; in no animal was there any tendency for periodicity to
increase with age over the period examined. The constant spacing seen
over time, together with the constant appearance of blood-vessel
pictures (e.g., in Fig. 5), suggests that there is little growth in the
size of the brain during the period between P31 and P55, at least in
the cortical areas investigated in this study.
DISCUSSION
Using the technique of chronic optical imaging of intrinsic
signals, we have examined the development of orientation preference
maps in ferret primary visual cortex. We have found that orientation
activity maps are initially low-contrast and that they mature over
several days into high-contrast, adult-like maps. During this period of
maturation, the features of the developing maps are very stable.
Despite differences among animals in the timing of map emergence and
the individual spatial layout of the maps, the overall course of
development was similar in all eight ferrets studied.
The time course of the map maturation found in this study closely
parallels, but appears to lag slightly behind, the time course of
orientation tuning maturation previously seen at the single-cell level
in electrophysiological recordings from young ferret visual cortex
(Chapman and Stryker, 1993 ). The development of orientation tuning
determined from optical imaging experiments is illustrated in Figure
7A. This figure shows the orientation tuning calculated from
the polar maps obtained in all of the animals in this study at all ages
examined. The solid sigmoid curves show the best-fit normal
distribution for these data in each individual animal, and the dashed
line indicates the best fit for data from all animals. The time of eye
opening is also shown for each animal. For comparison, this summary
distribution of developing tuning seen in optical imaging experiments
is replotted in Figure 7B (dashed curve) along
with the development of tuning seen in electrophysiological recording
data [solid curve shows best-fit sigmoid; data replotted
from Chapman and Stryker (1993) , their Figs. 3, 4]. A time difference
of several days is seen between the development of orientation at the
single-cell level and that seen in the activity maps. This cannot be
explained by differences in the rate of maturation of orientation
tuning in different cortical layers; the supragranular layers that are
responsible for most of the signal obtained in optical imaging
(Bonhoeffer and Grinvald, 1996 ) are the layers where orientation first
matures at the single-cell level (Chapman and Stryker, 1993 ). The
difference in the timing of the development of orientation tuning
assessed by the two different techniques has several possible
explanations. First, the difference may be attributable to a difference
in the sensitivity of the two techniques. Because optical imaging
cannot measure tuning of individual cells, it may not be able to assess
the earliest development of orientation tuning when only a few
individual cells in the cortex first become well-tuned for orientation.
In addition, optical imaging may be less sensitive to early orientation
tuning because cortical cells at the earliest ages that orientation is
seen electrophysiologically are less responsive than more mature cells
(Chapman and Stryker, 1993 ). Second, it is possible that the difference
in time course might not be caused by the different sensitivities of
the two techniques, but rather might indicate that at early ages cells
tuned for different orientations might be intermingled and might sort
out into iso-orientation domains during development. The marked
stability seen in the orientation tuning maps as soon as they appear,
however, makes this explanation of the timing difference less than
likely.
The observed stability of orientation maps in supragranular cortical
layers is a surprising result given the massive rearrangements of the
connections to the cortical cells that are known to occur during the
developmental time period covered by our experiments. Not only do
eye-specific afferents segregate into ocular dominance columns in layer
IV during this period, greatly altering the geniculate inputs to a
given orientation column (LeVay et al., 1978 ; Des Rosier et al., 1978 ;
LeVay et al., 1980 ; Thompson et al., 1983 ; Ruthazer et al., 1995 ), but
intracortical patchy connections within cortical layers II/III undergo
substantial refinement during this period of development (Callaway and
Katz, 1990 ; Ruthazer and Stryker, 1994 ). The constancy of the
orientation preference maps in the face of such extensive changes in
the connectivity of cortical cells suggests the primacy of orientation
preference as an organizing feature in visual cortex. This conclusion
is also supported by experiments double-labeling the patchy
intracortical connections at two time points in individual animals.
These experiments suggest that the general pattern of orientation
columns is present early and changes little if at all during
development (Callaway and Katz, 1990 ).
The stability of orientation maps during normal development observed in
this study is, in fact, very much in line with results from several
other experiments. We have found not only that orientation tuning is
present in primary visual cortex much earlier than other cortical
features such as ocular dominance columns, but also that as soon as
orientation-specific activity is seen with optical imaging and very
shortly after it is evident in the responses of more than a few single
units, orientation preference is already mapped across cortex with the
same map features found in mature animals. Other studies have shown
that orientation maps are continuous across areal borders in normal
animals (Bonhoeffer et al., 1995 ) and across ocular dominance columns
in strabismic animals (Löwel et al., 1994 ). In addition, the
features of orientation maps are unaffected by monocular deprivation
and reverse occlusion (Kim and Bonhoeffer, 1994 ) despite the dramatic
anatomical rearrangements of geniculocortical axons produced by brief
periods of monocular deprivation (Antonini and Stryker, 1993 ), and
matching orientation maps develop for the two eyes even in animals
raised under a reverse-suture paradigm from the time of natural eye
opening, such that the two eyes never have common visual experience
(Gödecke and Bonhoeffer, 1996 ). These reports, along with the
present results, suggest that the smooth mapping of orientation
preference across cortex constitutes a remarkably stable framework for
the development of other features of cortical organization.
Although this study was not designed to assess the role of visual
experience, its results indicate that visual experience plays little or
no role in determining the layout of orientation maps. Faint
orientation activity maps having the same features as the mature maps
were seen in the initial imaging session in at least one animal before
the time of natural eye opening, and early eye opening did not
correlate with early development of orientation maps (see Fig.
7A). In addition, the stability of the maps during
development shows that the map structure was not altered by the
animals' normal visual experience. These results are consistent with
the fact that orientation tuning at the single-cell level has been
found to be present at birth in the monkey (Wiesel and Hubel, 1974 ) and
about the time of natural eye opening in the cat (for review, see
Blakemore and Van Sluyters, 1975 ). The stability of orientation maps
during early development reinforces the interpretation (Stryker et al.,
1978 ) that the plasticity of orientation preference that seems to occur
after restricted early visual experience with oriented contours
(Blakemore and Cooper, 1970 ) is in fact attributable to selective
orientation-dependent losses in responsiveness of single cells rather
than genuine changes in orientation preference of the cells. Future
experiments will be required to test this interpretation directly, but
the use of optical imaging for such purposes is fraught with the peril
of potential artifact. Imaging relies on aggregate responses of
populations and thus has more difficulty than single-unit recording in
distinguishing a selective loss of responsiveness in some cortical
columns from a reorganization of the columns.
The tendency of iso-orientation stripes to run perpendicular to the
area 17/18 border, which was noted in the orientation maps obtained in
this study, is surprising given previous reports that in the adult
ferret, ocular dominance columns also tend to run perpendicular to the
areal border (Law et al., 1988 ). The precise relationship between
orientation maps and ocular dominance maps in individual animals
remains to be determined.
Our studies of the emergence and maturation of cortical orientation
maps suggest that orientation selectivity may be the primary organizing
feature of the developing visual cortex. Smooth mapping of orientation
preference emerges very early in cortical development, and once
established, the maps remain stable despite the anatomical
rearrangements of connections to the cortical cells. In addition,
details of the organization of the maps are not affected by normal
visual experience. This primacy of orientation has profound
implications for how we think about the development of the visual
cortex. These results raise questions about what could be the substrate
for map stability given the massive alterations in geniculocortical and
intracortical connections that fail to affect the maps. In addition,
these results provide groundwork for future theoretical and
experimental studies of how the organization of orientation may guide
the development of the organization of other cortical cell receptive
field properties such as ocular dominance.
FOOTNOTES
Received May 28, 1996; revised July 24, 1996; accepted July 24, 1996.
This work was supported by the Max Planck Gesellschaft, Human Frontier
Science Program Grant RG 69/93 to T.B. and M.P.S., and National
Institutes of Health Grant EY09760 to M.P.S. We thank Frank Brinkmann
for expert technical assistance.
Correspondence should be addressed to Tobias Bonhoeffer, Max Planck
Institute for Psychiatry, Am Klopferspitz 18A, 82152 Munich-Martinsried, Germany.
Barbara Chapman's present address: Center for Neuroscience, 1544 Newton Court, University of California, Davis, CA
95616.
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