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INTRODUCTION |
The visual pathways of mammals are organized
into several parallel, largely independent neuronal streams from retina
through the lateral geniculate nucleus (LGN) to visual cortex
(Rodieck and Brening 1983
; Sherman 1985
;
Stone 1983
; Stone et al. 1979
). These pathways differ in
terms of their projection patterns, their neuronal morphology, and
their cellular response properties. Presumably, each of these pathways
is organized to perform somewhat different visual processing tasks for
the animal (Lennie 1980
; Shapley and Perry
1986
; Sherman 1985
; Stone 1983
; Stone et
al. 1979
).
What remains uncertain is precisely how many of these separate
pathways pass through the macaque's lateral geniculate nucleus and
what relation these pathways have to the cat's W, X, and Y pathways.
Initial analysis suggested that one pathway similar to the cat's X
pathway passes through the parvocellular laminae and another similar to
the cat's Y pathway passes through the magnocellular laminae
(Dreher et al. 1976
; Sherman et al.
1976
). A putative third pathway, passing through the
interlaminar zones of the primate LGN and encroaching somewhat into the
parvo- and magnocellular laminae, remains incompletely characterized
(Casagrande 1994
; Fitzpatrick et al.
1983
; Hendry and Yoshioka 1994
). Kaplan and Shapley (1982)
observed that the monkey's parvocellular
laminae contain essentially only X cells of rather low visual
sensitivity and that the magnocellular laminae contain a mixture of
both X and Y cells of relatively high sensitivity. These authors
concluded that the pathways passing through the monkey's magnocellular
laminae are homologous to the X and Y pathways passing through the
cat's A laminae. Shapley and Perry (1986)
extended this
trans-species comparison to suggest that the pathway
involving the monkey's parvocellular geniculate laminae corresponds to
the W pathway in the cat.
The resolution of this question would be facilitated by a more thorough
classification of the neuron types found in these laminae. There is
general agreement that cells in the parvocellular laminae are of a
different class from those in the magnocellular laminae
(Derrington and Lennie 1984
; Dreher et al.
1976
; Kaplan and Shapley 1982
; Sherman et
al. 1976
; Spear et al. 1994
). Kaplan and
Shapley (1982)
claim that the magnocellular laminae contain two
cell classes, X and Y, which can be distinguished by several correlated
parameters: the Y cells, which display nonlinear summation, have poorer
spatial resolution and are innervated by faster conducting retinal
axons than the X cells, which display linear summation. Derrington and Lennie (1984)
found no evidence for two
cell types among the neurons in their sample from the monkey's
magnocellular laminae; a quantitative measure of the extent of
nonlinear summation, the "nonlinearity index" of Hochstein
and Shapley (1976)
, was unimodally distributed among these
neurons, and no correlation was seen between the extent of nonlinear
summation and spatial resolution. However, Derrington and Lennie
(1984)
emphasize that the sample size in both their study and
that of Kaplan and Shapley (1982)
precludes an
unambiguous resolution of this matter of classification. More recently,
Spear et al. (1994)
described the response properties of
a much larger sample of neurons in both the magno- and parvocellular laminae of macaque LGN. All response measures appeared continuously distributed; however, they did not determine the extent of nonlinear summation, which might have revealed subpopulations.
To address these issues, we used achromatic stimuli to measure a range
of response properties from neurons in the parvo- and magnocellular
laminae of the LGN of nine macaque monkeys: four raised normally and
five monocularly deprived of vision by lid suture for at least five
years starting near the time of birth. In cats, monocular deprivation
produces a selective loss of Y cells and a reduction in spatial
resolution among X cells in LGN laminae driven by the deprived eye
(Lehmkuhle et al. 1980
; Sherman and Spear
1982
; Sherman et al. 1972
). Studying the
monocularly deprived monkey LGN might similarly indicate whether a
particular cell type within the magno- or parvocellular laminae was
affected or lost. A previous study (Blakemore and Vital-Durand
1986b
) reported little difference between cells in layers
driven by the two eyes in monocularly deprived old-world monkeys.
However, they studied only one animal deprived for more than 70 days
and made too few quantitative measurements on each cell to establish
effects of deprivation specific to particular physiologically defined
cell types. Our results show that parvo- and magnocellular neurons form
two distinct and separate functional cell classes; we find no evidence
using achromatic stimuli that these classes can usefully be subdivided.
Monocular deprivation had only very subtle effects on the visual
response properties of geniculate neurons and did not seem to have
specific effects on any particular cell group.
We have briefly described some of these results in abstract form
(Levitt et al. 1989
; Sherman et al.
1984
).
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METHODS |
Surgical preparation and maintenance
We performed these experiments on four normal young adult
cynomolgus monkeys (Macaca fascicularis) and on five rhesus
monkeys (M. mulatta) reared from birth to the age of 5-6 yr
with the right eyelid sutured shut. All experimental procedures
conformed to National Institutes of Health guidelines. Animals were
initially premedicated with atropine (0.25 mg), and acepromazine
maleate (0.05 mg/kg), or valium (Diazepam: 0.5 mg/kg). After
induction of anesthesia with intramuscular injections of ketamine
(Vetalar: 10-30 mg/kg), cannulae were inserted in the saphenous veins
and surgery was continued under intravenous barbiturate anesthesia (sodium thiopental, Pentothal: 1-2 mg/kg boluses as needed). After cannulation of the trachea, the animal's head was fixed in a
stereotaxic frame. A small craniotomy was made, and after making a
small slit in the dura, a tungsten-in-glass microelectrode
(Merrill and Ainsworth 1972
) was positioned at
stereotaxic coordinates A7 L11; the hole was then covered with warm
agar. Bipolar stimulating electrodes (Rhodes Medical) were also
implanted into the optic chiasm; the appropriate position was
determined by recording evoked visual activity through the electrodes.
Once correctly positioned, they were fixed to the skull with dental
cement. On completion of surgery, animals were paralyzed to minimize
eye movements. Paralysis was maintained with an infusion of pancuronium
bromide (Pavulon: 0.1 mg · kg
1 · h
1) or vecuronium bromide (Norcuron: 0.1 mg · kg
1 · h
1) in lactated Ringer solution with dextrose
(5.4 ml/h). Animals were artificially ventilated with room air or a
49:49:2 mixture of
N2O:O2:CO2.
Peak expired CO2 was maintained at 4.0% by
adjusting the respirator stroke volume or the CO2
content in the gas mixture. Rectal temperature was kept near 37°C
with a thermostatically controlled heating pad. Anesthesia was
maintained by continuous infusion of sodium pentobarbital (Nembutal:
1-2 mg · kg
1 · h
1). The electrocardiograph (EKG),
electroencephalograph (EEG), and rectal temperature were monitored
continuously to ensure the adequacy of anesthesia and the soundness of
the animal's physiological condition. Animals also received daily
injections of a broad-spectrum antibiotic (Bicillin: 300,000 U).
The pupils were dilated and accommodation paralyzed with topical
atropine, and the corneas were protected with zero power contact
lenses; supplementary lenses were chosen that permitted the best
spatial resolution of recorded units. We opened the eyelids of the
monocularly deprived animals on the day of the experiment and noted
that while the deprived eye tended to be rather myopic relative to the
nondeprived eye [in agreement with Wiesel and Raviola
(1977)
, interocular differences ranging from 5 to 11.5 diopters], the quality of the deprived eye's optics was in every case
excellent. Contact lenses were removed periodically for cleaning, and
the eyes were rinsed with saline. The lenses were also removed for
several hours each day, the eyes given a few drops of ophthalmic antibiotic solution (Gentamicin), and the lids closed. At the beginning
of the experiment, and before beginning each day's recording, the
foveas were located and plotted using a reversible ophthalmoscope.
Characterization of receptive fields
Receptive fields were initially mapped by hand on a tangent
screen using black-and-white or colored geometric targets. When a
single neuron's activity was isolated, we established the eye through
which it was driven and occluded the other for quantitative experiments. We classified each cell by the criteria of Wiesel and Hubel (1966)
according to its receptive field organization and sensitivity to color, using four broadband gelatin (Wratten) filters (red, green, blue, and yellow). We also measured the cell's response latency to electrical stimulation of the optic chiasm, receptive field eccentricity, and whether it was on- or off-center. Following this initial characterization, we positioned the receptive field on the face of a display CRT, and quantitative experiments using
sinusoidal grating stimuli proceeded under computer control. Achromatic
stimuli (vertically oriented sinusoidal gratings) were presented within
a circular region on the face of a Hewlett-Packard 1332A display
oscilloscope with a P31 phosphor and a mean luminance of 40 cd/m2; display contrast was linearly related to
input voltage up to the maximum contrasts used. At the viewing distance
of 57 cm, the screen subtended 9.5° at the monkey's eye. Stimulus
presentation was controlled by a PDP11 computer, which also
accumulated, stored, and analyzed neuronal response data. Action
potentials were conventionally amplified and displayed; standard pulses
triggered by each impulse were stored by the computer and were also fed
to an audiomonitor. A standard experimental procedure was followed for
all cells encountered. Each experiment consisted of several (generally
4-10) blocks of trials. Within each block, all stimuli were presented
for the same amount of time (generally 5-10 s); grating stimuli were
either drifted or counterphase flickered with a sinusoidal time course. In each experiment, we measured responses by averaging several repeats
of a randomly interleaved set of stimuli, and we always included a
uniform field stimulus of the same duration and mean luminance as our
grating stimuli to obtain an estimate of spontaneous activity. We
Fourier-analyzed responses to determine the mean (F0), first harmonic
(F1), and second harmonic (F2) components of the response as well as
the temporal phase of each response component; except as specifically
noted in the following text, we always measured response with the F1
component, that is, the amplitude of the response component that
modulated in synchrony with the temporal modulation of the stimulus.
Neuroanatomical methods
During recording, small electrolytic lesions were produced at
locations of interest along the electrode track by passing DC current
through the electrode tip (1-2 µA for 2-5 s, tip negative). At the
end of the experiment, the animals were killed with an overdose of
Nembutal and perfused transcardially with buffered formalin or 4%
paraformaldehyde. Blocks containing the region of interest were sunk in
the cold in a postfix solution containing 30% sucrose, after which
50-µm-thick coronal sections were cut on a freezing microtome.
Sections were stained for Nissl substance with cresyl violet. Cells'
laminar locations were determined by the stereotypical shift in eye
preference as the electrode passed through each of the LGN laminae;
recording sites were subsequently verified histologically. Selected
tissue sections of interest were reacted to reveal Cat-301
immunoreactivity (Hendry et al. 1984
, 1988
;
Hockfield et al. 1983
). Briefly, tissue sections were incubated overnight in monoclonal antibody Cat-301 (full-strength supernatant) and then for 2-4 h in an appropriate dilution (1:50 or
1:100) of secondary antibody [affinity-purified rabbit anti-mouse conjugated with horseradish perioxide (HRP): Cappell]. HRP label was
visualized with diaminobenzidine as the chromogen, then tissue sections
were mounted on gelatin-coated slides, defatted, cleared, and coverslipped.
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RESULTS |
Our sample consists of 468 geniculate neurons: 214 studied in the
four normal animals and 254 neurons from the five monocularly deprived
animals. We studied certain response parameters of these cells
qualitatively, and we describe these before considering the more
quantitative receptive field data. We will describe the results from
normal and deprived animals together to demonstrate more clearly any
possible subpopulations within the magnocellular or parvocellular
laminae and to address the effects of deprivation. While we may have
encountered a few koniocellular neurons, it is unlikely we recorded
from many since they are so small and are restricted to the
interlaminar zones. Values reported for each parameter are means ± SD, and we used Mann-Whitney U tests for all statistical
comparisons between groups.
Neuroanatomical observations
Figure 1 shows photomicrographs of
coronal sections through the right hemisphere (ipsilateral to the
sutured eye) of one of the deprived animals. Figure 1A is a
Nissl-stained section. Cells in laminae innervated by the deprived eye
(2, 3, and 5) were clearly pale and shrunken when compared with cells
in nondeprived laminae as previously noted by many others (e.g.,
Headon and Powell 1973
; Sherman and Spear
1982
; Tigges et al. 1984
; Vital-Durand et
al. 1978
; von Noorden and Crawford 1978
). We
also examined the pattern of Cat-301 immunoreactivity in the deprived
animals' LGN since it preferentially labels magnocellular laminae in
the monkey and Y cells in the cat LGN (Hendry et al. 1984
,
1988
; Hockfield and Sur 1990
; Hockfield
et al. 1983
), and expression of this antigen in the cat is
dependent on visual experience (Guimaraes et al. 1990
;
Sur et al. 1988
). We therefore thought examining
reactivity patterns in the deprived monkey LGN would confirm the
efficacy of our deprivation regimen and suggest parallels with the
functional organization of the cat LGN. Figure 1B shows
Cat-301 immunoreactivity in a nearby section. Immunoreactivity is most
intense in lamina 1, the nondeprived magnocellular lamina, though
fainter reactivity can also be observed in the nondeprived
parvocellular laminae 4 and 6 as well. Immunoreactivity is essentially
eliminated in the deprived magnocellular lamina 2 as well as in the
deprived parvocellular laminae 3 and 5.

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Fig. 1.
Photomicrographs of Nissl (A)- and nearby Cat-301
(B)-stained sections from the right hemisphere of a
monocularly deprived animal's LGN. In both panels, the
top of the figure is dorsal, and the
right side is medial. Scale bars = 1 mm.
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Qualitative physiological observations
We determined the laminar location of each neuron, usually from
the stereotypic shift in ocular dominance of the receptive fields as
our electrode traversed vertically through each of the six geniculate
laminae. We confirmed our assessments of laminar location
histologically (see METHODS). Our normal sample includes 94 neurons in magnocellular laminae 1 and 2, plus 120 in parvocellular laminae 3-6; our sample from the monocularly deprived animals consists
of 62 deprived parvocellular neurons, 75 nondeprived parvocellular
neurons (including 4 binocular cells between parvocellular laminae), 56 deprived magnocellular neurons, and 61 nondeprived magnocellular neurons.
Table 1 shows our sample of recorded
units from the monocularly deprived animals. In testing cells in
laminae connected to the deprived and nondeprived eyes, we were careful
to sample equally from the LGNs both contra- and ipsilateral
to the deprived eye. We recorded in the same range of eccentricities as
in the normal animals; as in the normals, we also took pains to obtain
our magno- and parvocellular samples at similar retinal eccentricities
(see following text). Although we sampled the LGN ipsilateral to the deprived eye (i.e., the right hemisphere) at slightly more peripheral eccentricities, we found no consistent differences in response properties between the hemispheres in the deprived animals (see Table
4) and have therefore pooled data across hemispheres.
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Table 1.
Distribution of units recorded in the LGN of animals deprived of vision
in the right eye from birth to the age of 5-6 yr
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CELL TYPES.
Our distribution of geniculate neurons sensitive to chromatic (types I,
II, and IV) and luminance (type III) contrast agrees well with that
originally described by Wiesel and Hubel (1966)
. In the
normal animals, we found that only one magnocellular neuron (1%) was
chromatically opponent and that a substantial minority of 44 parvocellular neurons (40%) were type III. However, as
Derrington et al. (1984)
noted, it seems likely that
nearly every parvocellular neuron exhibits some degree of chromatic
opponency, a phenomenon that our techniques were probably too crude to
demonstrate. The proportions of the various cell types encountered in
the deprived animals did not seem to differ either from the normal
animals or between deprived and nondeprived laminae. In deprived
magnocellular laminae, 1 cell in 57 (1.8%) was chromatically opponent
versus 3% (3/61) of the nondeprived magnocellular neurons. In deprived parvocellular laminae, 14.5% (9/62) of the sample was type III, while
20% (15/74) of the nondeprived sample was.
ECCENTRICITY.
The receptive field eccentricities of our normal parvocellular sample
ranged from 0 to 9°, while those of our normal magnocellular sample
ranged from 0 to 14°. A substantial proportion of both magno- and
parvocellular samples was within the central 5°; however, while
essentially the entire parvocellular sample (94%) was within the
central 5°, only about half of the magnocellular sample was. We
therefore also list in Table 3 summary statistics of our magno- and
parvocellular samples restricted to the central 5°. More
detailed descriptions of eccentricity values of our neuronal sample are given in the following text in relationship to other variables. Where response characteristics vary with eccentricity we make comparisons between magno- and parvocellular samples restricted to this
matched range of eccentricities. In the monocularly deprived animals,
all LGN divisions (deprived and nondeprived magno- and parvocellular)
were sampled at similar eccentricities (i.e., from 0 to 8°, mean
eccentricity of roughly 4°).
DISTRIBUTION OF ON- AND OFF-CENTER CELLS.
Table 2 shows the distribution of on- and
off-center cells across the laminae for our normal and deprived animal
samples. In the normal animals, we observed an obvious center/surround organization in 207 (96.7%) of the receptive fields. There were clear
interlaminar differences among these in the balance of on- and
off-center cells. Although we found an approximate balance for the
entire normal sample (106 on center vs. 101 off center), the
parvocellular sample contained mostly on-center cells (70 on center vs.
46 off center), while the magnocellular sample was dominated by
off-center cells (36 on center vs. 55 off center), and the anisometry
of distribution is statistically significant (P < 0.01 on a
2 test). We did not observe the dramatic
segregation of on- and off-center cells for the parvocellular laminae
as described by Schiller and Malpeli (1978)
, who
concluded that laminae 5 and 6 were nearly exclusively on center and
laminae 3 and 4 off center (see also Derrington and Lennie
1984
). As shown in Table 2, however, we did observe a
preponderance of on-center cells in both laminae 5 and 6 (and this held
in each of the monkeys); curiously, in each monkey we also encountered
more off-center cells in lamina 1.
We observed a broadly similar pattern in both deprived and nondeprived
laminae of the monocularly deprived animals, although there were
certain differences. In contrast to the approximate balance between on-
and off-center cells seen in the normal animals' LGN, there were
clearly more on- than off-center cells in total in the deprived
animals' LGN, and the parvocellular laminae were again dominated by
on-center cells. The overall anisometry of distribution of on- and
off-center cells was significant as in the normal animals
(P < 0.005 in deprived-eye laminae, P < 0.01 in nondeprived-eye laminae). However, the preponderance of
on-center cells in laminae 5 and 6 was more pronounced and the
preponderance of off-center cells in laminae 1 and 2 was less
pronounced than in the normal animals. While such differences could
conceivably result from sampling biases, they might also reflect subtle
species differences between the normal animals (M. fascicularis) and the deprived animals (M. mulatta). In
any case, deprivation had no obvious effect on the relative proportions
or distribution across laminae of on- and off-center cells.
Quantitative physiological observations
LATENCY TO OPTIC CHIASM STIMULATION.
Figure 2 shows that for the 203 normal
LGN neurons from which we obtained a measure of the response latency to
activation of the optic chiasm (OX), cells in the magnocellular laminae
exhibited significantly shorter latencies than did parvocellular cells, and this difference was seen for each of the four monkeys
(parvocellular: 3.14 ± 0.54 ms, magnocellular: 1.76 ± 0.33 ms; P < 0.001 on a Mann-Whitney U test for
each monkey). This confirms earlier observations (Dreher et al.
1976
; Kaplan and Shapley 1982
; Marrocco
et al. 1982
). We found no difference in this parameter between
parvocellular neurons identified as types I, II, or IV and those
identified as type III, which indicates that this aspect of receptive
field organization is not correlated with the conduction velocity of the retinogeniculate input. Finally, we found no relationship between
OX latency and receptive field eccentricity for either magno- or
parvocellular neurons. OX latencies in the monocularly deprived animals
differed between magno- and parvocellular groups as in the normals and
did not differ significantly between the deprived and nondeprived
parvocellular samples (deprived: 3.20 ± 0.51 ms, nondeprived:
3.19 ± 0.46 ms). There was a small but statistically reliable
difference between deprived and nondeprived magnocellular neurons
(deprived: 1.72 ± 0.32 ms, nondeprived: 1.86 ± 0.26 ms,
P < 0.018); the significance of this observation is
unclear.

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Fig. 2.
Distributions of lateral geniculate nucleus (LGN) response latencies
(in ms) following electrical stimulation of the optic chiasm. Shown
separately (and in succeeding figures) are normal (Normal M), deprived
(Dep M), and nondeprived (Nondep M) magnocellular neurons, and normal
(Normal P), deprived (Dep P), and nondeprived (Nondep P) parvocellular
neurons.
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Save for the differences in laminar distributions of on- and off-center
receptive fields noted in the preceding text, the magno- and
parvocellular populations each appeared to be fairly homogeneous and
quite distinct from one another. Thus in the quantitative analyses in
the following text, data from these various cell types will generally
be pooled across the magno- or parvocellular laminae. We used a
consistent protocol to study the responses of each neuron, yielding the
set of measurements shown in Fig. 3 for a
single magnocellular neuron.

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Fig. 3.
Response measures derived from a single representative magnocellular
LGN cell. In all panels, F1 response (see METHODS) is used
unless otherwise noted. A: spatial frequency response
function: , drifting gratings; , uniform field
flicker. , the best-fitting difference-of-Gaussians function; ,
center characteristic spatial frequency
(fc). B:
amplitude of F1 ( ) and mean F2 responses ( ),
and their ratio (C) as a function of spatial frequency.
in C indicates an undefined ratio as F1
response was indistinguishable from baseline at this spatial frequency.
D: temporal frequency response function. , the
best-fitting difference-of-exponentials function. , optimal temporal
frequency and temporal resolution. E: response temporal
phase as a function of stimulus temporal frequency. F
and G: response amplitude and response temporal phase,
respectively, as a function of stimulus contrast. in
F is best-fitting saturating function.
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First, we determined spatial properties of neurons with drifting and
counterphase flickered gratings. These gratings had a contrast of 0.5 and a temporal frequency of 4 Hz. For the drifting gratings (Fig.
3A), six spatial frequencies from 0.38 to 12 c/° in octave
steps were chosen; zero spatial frequency (or DC) was approximated by
sinusoidally flickering a blank screen at 4 Hz and at a depth of
modulation equivalent to the luminance difference between the brightest
and darkest points along the gratings. The counterphase flickered
gratings had the same range of spatial frequencies; for each frequency,
we presented these at six equally spaced absolute spatial phases.
We found no substantive or consistent differences between the tuning
functions taken from drifting gratings and those derived from
counterphased flickering gratings. We therefore took most spatial
properties of these neurons from the modulated responses to drifting
gratings. We used the difference of Gaussians receptive field model to
derive a number of spatial properties from the tuning curve
(Derrington and Lennie 1984
; Enroth-Cugell and
Robson 1966
; Rodieck 1965
). To each spatial
frequency response, we fit a function (Fig. 3A,
) of the
form
where R is response, k is an overall scaling
factor, ks is the relative strength of
the surround, and fc and
fs are the characteristic spatial
frequencies of the center and surround mechanisms. From these
characteristic frequencies, we calculated the characteristic radii of
the center and surround mechanisms (Enroth-Cugell and Robson
1966
).
The counterphase flickered gratings were used to test the linearity of
each cell's spatial summation by examining the fundamental (F1) and
second harmonic (F2) response components. The F1 response varies
sinusoidally with the spatial phase of the grating, whereas the F2
response is for the most part independent of spatial phase. At each
spatial frequency where there was a reliable evoked response, we
calculated the ratio of the mean of the F2 responses to the amplitude
of the F1 responses (Fig. 3, B and C). The
maximum value of this ratio across spatial frequency we define as the
"nonlinearity index," closely following Shapley and
Hochstein (1975)
and Hochstein and Shapley
(1976)
.
Second, we determined the temporal properties of each cell by measuring
responses to gratings of 0.5 contrast and optimal spatial frequency,
drifted at 7-13 different temporal frequencies (Fig. 3D).
These were varied in octave or half-octave steps from 0.5 to 48 Hz. To
the temporal frequency response data, we fitted a function representing
cascaded low-pass exponential and high-pass RC filters (Fig.
3D,
) and from the fit determined each cell's optimal
temporal frequency (peak response), temporal resolution (high temporal
frequency at half-maximum response), and response transience (the slope
of the low frequency limb of the function, see following text). Since
the temporal phase of each neuron's response to different temporal
frequencies was proportional to temporal frequency, the slope of the
resulting line is the "steady-state visual latency," which
provides a measure of each neuron's temporal integration behavior
(Fig. 3E).
Third, we studied response as a function of stimulus contrast, using
gratings of optimal spatial frequency. We chose a temporal frequency at
or slightly below the optimum to take account of contrast gain control
effects (Shapley and Victor 1978
). The contrast of these
gratings usually ranged from 0.015 to 0.7 in steps of 0.15 log units
(Fig. 3F). To these data, we fit the function suggested by
Robson (1975)
where R is response, k is a scaling factor,
C is contrast, and C0 is a
saturation constant. Over the range of contrasts we used, parvocellular
responses were nearly linear, but magnocellular responses often showed
a nonlinear saturation at higher contrasts. At low contrasts, however,
all cells gave responses proportional to contrast; the slope of the
contrast response function at 0 contrast,
k/C0, is our measure of
responsivity. We also determined the degree to which the temporal phase
of responses depended on stimulus contrast [indicative of the contrast
gain control described by Shapley and Victor (1978)
]
(Fig. 3G). We fitted a function simultaneously to both the
amplitude and phase of contrast response data (Carandini et al.
1997
), and from this complex function we extracted a function
relating temporal response phase to stimulus contrast. From this phase
versus contrast function, we determined the difference in response
phase between the 50% contrast condition and the blank condition (0%
contrast); we took this "phase advance," expressed in milliseconds,
to measure contrast gain control.
Tables 3 and
4 summarize a
number of the parameters that we determined quantitatively for neurons
in the normal and monocularly deprived animals. These are shown
separately for magno- and parvocellular neurons. The parameters shown,
defined in the preceding text and considered in more detail in the
following text (see also DISCUSSION), include receptive
field eccentricity in deg, response latency to optic chiasm stimulation
in seconds (OX latency), radius in degrees
(rc), and characteristic frequency in
c/degree (fc) of the center
mechanism, surround sensitivity (ks),
nonlinearity, optimal and cutoff temporal frequencies in Hz, response
latency to visual stimuli in milliseconds (visual latency), response
transience, responsivity, and phase advance in milliseconds.
SPATIAL PROPERTIES.
Figure 4 illustrates the distributions of
the characteristic frequencies
(fc) of our magno- and
parvocellular samples (derived from spatial tuning functions as
described in the preceding text), and Fig.
5 shows the variations of
fc and
rc (center radius) with eccentricity.
Note that, with increasing eccentricity,
rc increases and
fc decreases, although this trend was
somewhat less obvious in the monocularly deprived animals (due to the
presence in these animals of units with lower spatial resolutions close
to the fovea and with higher spatial resolutions at intermediate
eccentricities). This again might reflect subtle species differences.
However, Derrington and Lennie (1984)
and Spear
et al. (1994)
observed a similar weak dependence on
eccentricity of these parameters within the central 10° in both
M. mulatta and M. fascicularis monkeys. Note also
that with our methodology, we found little difference between magno-
and parvocellular neurons, in both normal and deprived animals, with
respect to these variables. This belies the expectation that
magnocellular neurons should have markedly larger
rc values and poorer resolution than
parvocellular neurons at matched eccentricities (Derrington and
Lennie 1984
; Kaplan and Shapley 1982
;
Merigan et al. 1991
) but is in accord with the findings
of Spear et al. (1994)
. Our normal sample with receptive fields within 1° of the fovea is predominantly parvocellular, and
beyond 8° it is exclusively magnocellular. Although parvocellular neurons on average had somewhat larger
fc and smaller
rc values (fc: parvocellular, 4.57 ± 2.73 c/° and magnocellular, 2.82 ± 1.68 c/°;
rc: parvocellular, 0.069 ± 0.076° and magnocellular, 0.112 ± 0.080°), this partially
reflects the eccentricity differences in our normal samples. In our
samples within both the 1-2.5° and 3-7.5° sectors of reasonably
matched eccentricity, we found no significant differences between
parvo- and magnocellular neurons for mean or variance of
rc and
fc values. In our sample restricted to
the central 5°, we did still find a small (though significant) difference between parvo- and magnocellular neurons
(fc: parvocellular, 4.57 ± 2.75 c/°; magnocellular, 3.55 ± 1.94 c/°;
P < 0.02). This is consistent with the results of
Spear et al. (1994)
and of Blakemore and
Vital-Durand (1986a)
, who found that the majority of parvo- and
magnocellular neurons at a given eccentricity (the X-like ones) had
similar spatial resolution. However, we have noted, as have
Derrington and Lennie (1984)
and Spear et al.
(1994)
, that the smallest rc
(and highest fc and spatial resolution
values) at each eccentricity tend to belong to the parvocellular cells. The values of fc and
rc in the deprived animals did not
differ significantly from those values in the normal animals, nor did we find any effect of deprivation.

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Fig. 4.
Distributions of center mechanism characteristic frequencies
(fc) plotted separately (as in Fig.
2) for normal, deprived, and nondeprived magno- and parvocellular
neurons.
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Fig. 5.
Scatterplot of the relationship between center characteristic frequency
fc (or receptive field center radius
rc) and receptive field eccentricity for
normal LGN cells (top), deprived and nondeprived
magnocellular cells (middle), and deprived and
nondeprived parvocellular cells (bottom).
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We found no significant differences between the parvo- and
magnocellular populations in the mean strength of receptive field surrounds (ks: parvocellular,
0.54 ± 0.35; magnocellular, 0.60 ± 0.33), nor did this
parameter vary significantly with eccentricity. Deprivation had no
effect on ks for parvocellular
neurons, but the relative strength of the surround mechanism was
stronger in magnocellular neurons in deprived-eye laminae than in
nondeprived laminae (deprived, 0.60 ± 0.18; nondeprived,
0.41 ± 0.24; P < 0.0035).
Figure 6 summarizes the distribution of
nonlinearity index values. Larger values indicate greater
frequency-doubled responses relative to the F1 component, indicative of
nonlinearities in spatial summation, i.e., "Y-like" behavior. We
found no change in this index with eccentricity for either the magno-
or parvocellular populations. On average, magnocellular neurons display
greater nonlinearity indices than do parvocellular neurons, consistent with previous reports that the nonlinear (Y-like) cells are found as a
subgroup only within the magnocellular laminae (parvocellular, 0.42 ± 0.19; magnocellular, 0.65 ± 0.55); this difference
was significant in both the overall sample and the sample restricted to
the central 5° (P < 0.001). However, there is
considerable overlap between populations, and both the parvo- and
magnocellular distributions are essentially unimodal, an observation in
agreement with that of Derrington and Lennie (1984)
.

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Fig. 6.
Distributions of nonlinearity indices for normal, deprived, and
nondeprived magno- and parvocellular neurons.
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Comparison between deprived and nondeprived laminae suggests that there
was a small but significant decrease in the average nonlinearity
indices of our monocularly deprived sample in both magno- and
parvocellular laminae (parvocellular nondeprived, 0.47 ± 0.20;
parvocellular deprived, 0.38 ± 0.16, P < 0.0085;
magnocellular nondeprived, 0.56 ± 0.28; magnocelluar deprived,
0.42 ± 0.31, P < 0.0006). Although this is
reminiscent of the Y-cell loss noted in cats following monocular
deprivation (Sherman et al. 1972
; but see So and
Shapley 1980
), the effect is not the same. Here, we see a
decrease in nonlinearity indices in both magno- and
parvocellular laminae, while only the magnocellular laminae contain the
nonlinear (Y-like) cells, i.e., those with indices greater than 1 (Blakemore and Vital-Durand 1986a
; Kaplan and
Shapley 1982
). Furthermore we found no evidence for the loss of
any one subpopulation; nonlinear cells were still found in deprived
laminae. Rather, we observed a simple shift in the overall population
distributions that was approximately 0.5 of a standard deviation in
both magno- and parvocellular layers.
The unimodal distributions of nonlinearity index shown in Fig. 6 do not
by themselves rule out the suggestion of Kaplan and Shapley
(1982)
that magnocellular neurons can be classified into distinct linear (X) and nonlinear (Y) types, since these types might
differ both in their linearity and in such other characteristics as
their spatial resolution or the conduction velocity of their retinal
afferents. Figure 7A shows
scatter plots, separately for magno- and parvocellular neurons, of
characteristic frequency (fc,
equivalently center radius rc,
right-hand ordinate) versus nonlinearity index for our normal sample
(Fig. 7A, left) and for our deprived sample
(right), which again shows that both these parameters were
continuously distributed with no clear segregation into subpopulations.
Inspection of the data from deprived animals reveals no evidence of a
loss of a particular cell group; data from deprived laminae are simply
shifted toward lower values of the nonlinearity index (cf. Fig. 6).
Figure 7B shows similar plots of OX response latency versus
nonlinearity index. There is again no evidence for a distinctive group
of nonlinear neurons in either population, nor do similar displays (not
shown) of nonlinearity index against other properties such as spatial
or temporal resolution reveal subgroups. These results therefore do not
support earlier suggestions that there are separate X and Y cells in
the magnocellular layers; rather, the magno- and parvocellular layers
each seem to contain a single class of neuron with some diversity of
properties within the class.

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Fig. 7.
A: scatterplots of the relationship between center
characteristic frequency fc (or equivalently
center radius rc, right-hand ordinates) and
nonlinearity index for LGN cells from normal animals
(left) and from deprived animals (right).
B: scatterplots of the relationship between latency to
optic chiasm stimulation and nonlinearity index for LGN cells from
normal animals (left) and from deprived animals
(right). The datum from 1 parvocellular neuron from a
normal animal with an optic chiasm latency of 6.4 ms has been
omitted.
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TEMPORAL PROPERTIES.
Figure 8 illustrates the distributions of
our observed temporal resolution values. As noted in the preceding
text, the optimum spatial frequency and spatial resolution were also
determined for these neurons, but we found no correlation between these
spatial and temporal variables. There was no measurable influence of
eccentricity on optimal temporal frequency, and we found no significant
differences in temporal frequency optima between magno- and
parvocellular neurons; nor did we find any significant effects of
deprivation (parvocellular normal, 6.76 ± 3.24 Hz; parvocellular
nondeprived, 7.59 ± 4.20 Hz; parvocellular deprived, 7.41 ± 5.01 Hz; magnocellular normal, 7.94 ± 4.80 Hz; magnocellular
nondeprived, 8.51 ± 5.48 Hz; magnocellular deprived, 10.4 ± 4.4 Hz). In our normal sample, however, magnocellular neurons did on
average have significantly better temporal resolution than did
parvocellular neurons (parvocellular, 21.9 ± 12.3 Hz;
magnocellular, 31.6 ± 15.9 Hz; P < 0.001). This difference might in part reflect the slight increase in temporal resolution with eccentricity (r = 0.36, P < 0.01 for magnocellular neurons; r = 0.29, P < 0.05 for parvocellular neurons) coupled with the bias in our normal magnocellular sample to more eccentric receptive field locations relative to the parvocellular sample. However, we did also observe a small significant magno-parvocellular difference in temporal resolution values in our normal sample restricted to the central 5° (parvocellular, 21.4 ± 11.7 Hz;
magnocellular, 27.5 ± 13.7 Hz; P < 0.02).

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Fig. 8.
Distributions of temporal resolution values (high temporal frequency at
half-maximum response) for normal, deprived, and nondeprived magno- and
parvocellular neurons.
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Macaque LGN neurons have also been classified according to their
capacity to maintain discharge during stimulus presentation; Dreher et al. (1976)
and Schiller and Malpeli
(1978)
reported that responses in the parvocellular laminae are
more sustained than those in the magnocellular laminae. We defined a
transience index from each cell's temporal frequency
response function by measuring the slope in log-log coordinates of the
low-frequency (high-pass) limb of the function, below the optimal
temporal frequency. Cells with larger transience indices had greater
attenuation of responses to low temporal frequencies; this is
equivalent to saying that their responses were less sustained (more
transient) during stimulus presentation
assuming that neurons'
temporal summation behavior is linear, which seems essentially true
(Lee et al. 1994
). Thus transience indices near 0 indicate perfectly low-pass temporal frequency response behavior
("sustained" responses), while larger transience indices indicate
band-pass temporal frequency responses with attenuated response at low
temporal frequencies ("transient" behavior). Figure
9 illustrates the distributions of
transience indices of our magno- and parvocellular samples.
Unexpectedly, normal magnocellular neurons on average had slightly
smaller transience indices than normal parvocellular neurons
(magnocellular, 0.54 ± 0.29; parvocellular, 0.70 ± 0.41);
these distributions overlapped to a great extent and were significantly
different from one another (P < 0.0081). The
difference was not significant, however, in the samples restricted to
the central 5°. This index is distributed unimodally through both
magno- and parvocellular laminae with no evidence for any special
subpopulations. Our finding that the distributions overlap agrees with
Blakemore and Vital-Durand's (1986a)
conclusion that
response transience was not strongly correlated with other receptive
field classification criteria in macaque LGN. Our finding that
parvocellular neurons were, on average, slightly more
transient than magnocellular neurons is nonetheless unexpected.

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Fig. 9.
Distributions of response transience indices for normal, deprived, and
nondeprived magno- and parvocellular neurons. Transience is defined as
the slope in log-log coordinates of the portion of the temporal
frequency response function in the decade below the peak temporal
frequency.
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In the monocularly deprived animals, transience indices in both parvo-
and magnocellular laminae showed no significant effect of deprivation
(parvocellular nondeprived, 0.62 ± 0.41; parvocellular deprived,
0.60 ± 0.48; magnocellular nondeprived, 0.47 ± 0.29; magnocellular deprived, 0.47 ± 0.28). These mean transience
indices are somewhat lower than those in the normals. The differences between normal cells and either deprived or nondeprived cells were,
however, significant only for the comparison of normal and deprived
parvocellular neurons (P < 0.017). While this
difference might indicate a subtle effect of deprivation on the
transience of parvocellular LGN cells, the absence of a reliable
difference between deprived and nondeprived cells suggests that this
merely reflects minor differences between the different macaque species.
We also determined the steady-state visual response latencies for our
sample. As illustrated by Fig. 10,
despite substantial overlap in the distributions, magnocellular
neurons' visual latencies were on average significantly shorter than
those of parvocellular neurons in both normal and deprived animals, and
deprivation had no significant effect on latencies (parvocellular
normal, 44.8 ± 8.3 ms; magnocellular normal, 37.9 ± 4.5 ms;
P < 0.0001; parvocellular nondeprived, 47.0 ± 21.5 ms; parvocellular deprived, 54.6 ± 49.4 ms; magnocellular
nondeprived, 40.9 ± 7.5 ms; magnocellular deprived, 41.1 ± 11.7 ms). These values are significantly smaller than the mean value of
approximately 77 ms reported by Spear et al. (1994)
. As
response latency is known to vary with stimulus contrast
(Sestokas and Lehmkuhle 1986
; Shapley and Victor
1978
), these latency differences might simply reflect
differences between their experimental conditions and our own, but we
are puzzled by the discrepancy. Finally, for both the magno- and
parvocellular populations, we found no correlation between visual
latency and receptive field eccentricity, optimum temporal frequency,
or temporal resolution.

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Fig. 10.
Distributions of steady-state visual response latencies for normal,
deprived, and nondeprived magno- and parvocellular neurons. Latency is
defined as the slope of the line relating response temporal phase to
stimulus temporal frequency.
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CONTRAST-RESPONSE PROPERTIES.
Figure 11 shows the distributions of
responsivity values in our sample and shows that for the normal magno-
and parvocellular neurons we tested, magnocellular neurons were
significantly more responsive than were parvocellular neurons
(parvocellular, 23.4 ± 24.2; magnocellular, 87.1 ± 80.1;
P < 0.0001). This confirms earlier observations that
magnocellular neurons display greater sensitivity to luminance contrast
than do parvocellular neurons (Derrington and Lennie
1984
; Hicks et al. 1983
; Kaplan and
Shapley 1982
; Schiller and Colby 1983
;
Spear et al. 1994
). Both distributions are unimodal with
no indication of distinct subpopulations in either LGN division having
high or low responsivities. Nor did we find any relationship between
responsivity and either receptive field eccentricity or center radius
(rc). In monocularly deprived animals,
cells in deprived laminae had lower responsivity than those in
nondeprived laminae, although this difference was significant only in
the magnocellular laminae (parvocellular nondeprived, 33.1 ± 114.6; parvocellular deprived, 26.3 ± 105.2; P > 0.05; magnocellular nondeprived, 251.2 ± 341.5; magnocellular
deprived, 177.8 ± 285.5; P < 0.033). We note
here another likely species difference between the normals (M. fascicularis) and the monocularly deprived animals (M. mulatta); nondeprived cells in the deprived animals were more
responsive than those in the normals (parvocellular normal vs.
nondeprived: P < 0.0183; magnocellular normal vs.
nondeprived: P < 0.0001).

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Fig. 11.
Distributions of responsivity values for normal, deprived, and
nondeprived magno- and parvocellular neurons. Responsivity is defined
as the slope of the best-fitting contrast response function at 0 contrast.
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Figure 12 shows the distributions
of phase advance values in our magno- and parvocellular samples. It is
clear that most parvocellular neurons had phase advances of less than
10 ms, whereas most magnocellular neurons had phase advance values
between 10 and 40 ms, and there was no significant dependence of this
parameter on eccentricity. The difference between these distributions
was highly significant (parvocellular, 6.7 ± 8.0 ms;
magnocellular, 17.7 ± 10.4 ms; P < 0.0001). This
difference shows that the magnocellular laminae are distinguished not
only by the presence of cells with high luminance contrast sensitivity
and nonlinear spatial summation but also by cells with marked contrast
gain control effects. This is again reminiscent of cat Y cells, as they
are the cells exhibiting such nonlinearities of spatial summation and
phase advances indicative of contrast gain control (Kaplan and
Shapley 1982
; Shapley and Victor 1978
). However,
none of these attributes revealed distinct subpopulations within the
macaque magnocellular laminae, as all of these parameters were
unimodally distributed in our magnocellular sample, and cells showing
contrast gain effects were also found (though more rarely) in the
parvocellular laminae. Phase advance values differed between magno- and
parvocellular laminae in the deprived animals as in the normals, and
deprivation had no significant effect on the amplitude of the phase
shift (parvocellular nondeprived, 10.2 ± 14.9 ms; parvocellular
deprived, 8.3 ± 12.9 ms; magnocellular nondeprived, 20.7 ± 12.2 ms; magnocellular deprived, 17.4 ± 10.9 ms).

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Fig. 12.
Distributions of phase advance values for normal, deprived, and
nondeprived magno- and parvocellular neurons. Phase advance (indicative
of contrast gain control), derived from the complex function fitted to
contrast response data, is the difference in response temporal phase
(in ms) between the 50% contrast and blank stimulus conditions.
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In summary, the only significant effects of monocular deprivation that
we found by comparison of deprived and nondeprived laminae were the OX
latency (magnocellular: deprived < nondeprived, P < 0.018), surround strength (ks)
(magnocellular: deprived > nondeprived, P < 0.0035), nonlinearity index (parvocellular: deprived < nondeprived, P < 0.0085; magnocellular: deprived < nondeprived, P < 0.0006), and responsivity
(magnocellular: deprived < nondeprived, P < 0.033).
DEPRIVATION EFFECTS AND STATISTICAL ANALYSES.
We performed one other statistical analysis to uncover possible effects
of deprivation, a logistic regression. Rather than simply using a
series of two-way comparisons, this analysis allows one to take an
entire set of measurements and shows how much predictive power each additional parameter confers when one tries to make a binary
classification on the data (i.e., deprived vs. nondeprived). The set of
measurements used were OX latency, center frequency (fc), surround strength
(ks), nonlinearity, temporal frequency optimum and resolution, response latency and transience, and
responsivity. This analysis, though robust, does require a full set of
measurements from each cell, so any cells missing any of the set of
independent measures is simply not used. One might therefore believe
that the cells stable enough to obtain all measurements might represent a biased subset of our sample. We collected the full set of
measurements on 60 parvo- and 79 magnocellular cells. For the
magnocellular cells, a set of four measurements permitted one to
predict whether a cell was deprived or nondeprived
OX latency,
nonlinearity, ks, and responsivity
(which are the same measures shown to be affected by deprivation by
simple pairwise comparisons). The coefficients and standard errors for
each parameter in the final fit were OX =
2.7 ± 0.98, ks = 2.7 ± 1.32, responsivity =
0.002 ± 0.0009, nonlinearity =
2.9 ± 1.22. Addition of each successive measure led to a
statistically significant improvement in the
2
test of the regression fit (using a maximum likelihood test), and
addition of no other parameter improved the fit. The final model's log
likelihood was
42.3,
2 = 84.6, df = 74, P = 0.187 (i.e., the fit is not rejected and the model
using 4 parameters does fit the data). For the parvocellular cells, no set of measurements could be used to predict the
deprived/nondeprived classification, and no measure improved the
2. Final log likelihood was
41.4,
2 = 82.9, df = 59, P = 0.022 (i.e., the fit is rejected). Thus although pairwise comparisons
for each parameter showed a few (subtle) differences between deprived
and nondeprived groups, this analysis using all of the available
information shows that there were no reliable effects of deprivation in
the parvocellular laminae and only a few small ones in the
magnocellular laminae. Our inability to uncover any major effects of
monocular deprivation on the LGN can therefore not be attributed
to the particular battery of statistical tests used.
 |
DISCUSSION |
Our results confirm that parvo- and magnocellular neurons form two
distinct and separate functional cell classes; we find no evidence
using achromatic stimuli that these classes can usefully be subdivided.
However, we also note (in agreement with Spear et al.
1994
) that there is extensive overlap between magno- and parvocellular populations in most properties studied. Monocular deprivation had only very subtle effects on the visual response properties of geniculate neurons and did not seem to have specific effects on any particular cell group that we could identify.
Magno-parvocellular differences and evidence for subpopulations
Our results are consistent with previous studies of the LGN
showing that neurons in the magnocellular division of the LGN may be
distinguished from those in the parvocellular laminae by their faster
afferent conduction velocities, greater luminance contrast
sensitivities, and greater contrast gain control (Blakemore and
Vital-Durand 1986a
; Derrington and Lennie 1984
;
Dreher et al. 1976
; Hicks et al. 1983
;
Kaplan and Shapley 1982
; Marrocco et al.
1982
; Schiller and Malpeli 1978
; Shapley
et al. 1981
; Spear et al. 1994
). We observed a
tendency for neurons with the best spatial resolution to be
parvocellular and the best temporal resolution to be magnocellular.
However, we found extensive overlap in spatial and temporal properties
of LGN neurons, in agreement with Spear et al. (1994)
;
this overlap can also be seen in the data of Derrington and
Lennie (1984)
. Furthermore, the distributions of all parameters studied were unimodal and distributed continuously through the population with no clear segregation into subpopulations. Our data
therefore provide no compelling evidence for distinct subgroups within
the parvo- and magnocellular divisions of the monkey LGN. In
particular, we find no evidence to support earlier suggestions that
magnocellular neurons can be classified into distinct linear (X) and
nonlinear (Y) types with high and low spatial resolutions (Blakemore and Vital-Durand 1986a
; Kaplan and
Shapley 1982
). We emphasize again that all of these conclusions
were reached using achromatic stimuli; chromatic opponency
is one of the prime distinguishing features between the magno- and
parvocellular laminae (Derrington et al. 1984
;
Schiller and Colby 1983
; Wiesel and Hubel
1966
), and we did not study the chromatic properties of these
cells in any detail.
Much emphasis has been placed on the functional differences between the
pathways through the parvo- and magnocellular divisions of the LGN and
the different visual abilities they might mediate (Livingstone
and Hubel 1988
; Merigan and Maunsell 1990
;
Merigan et al. 1991
; Schiller et al.
1990
). We have shown that in many respects magno- and
parvocellular functional properties overlap with subtle quantitative
differences being the rule. It may therefore be problematic to assign
responsibility for different visual functions to different divisions of
the LGN (Livingstone and Hubel 1988
; Schiller et
al. 1990
). Our results are therefore more consistent with
Merigan's (1991)
conclusion that apart from the
obvious exception of color vision, which is mediated by parvocellular
neurons, the parvo- and magnocellular LGN pathways both participate in
most visual functions, and differ mainly in the particular range of spatiotemporal frequencies that they provide to visual cortex. Our
magno- and parvocellular samples almost certainly included some
koniocellular neurons, but we can rule out the possibility that
differences among our magno- or parvocellular samples were masked by
intrusion of koniocellular data. We compared receptive field properties
of neurons located within either 50 or 100 µm of a laminar boundary
to those of cells located further from the boundary; cells receiving
koniocellular inputs should sit closer to laminar borders. We found
no properties to differ as a function of distance from the
laminar border.
So what is the answer to the question we raised in the introduction,
"How many distinct parallel pathways involve the parvo- and
magnocellular laminae of the lateral geniculate nucleus?" The short
answer is two. Based on an examination of the spatiochromatic opponent
organization of LGN receptive fields, Wiesel and Hubel (1966)
identified three classes in the parvocellular and two in the magnocellular laminae. We have shown that full examination of these
neurons' conduction velocities and spatial, temporal, and contrast
processing properties using achromatic stimuli reveals each of the
magno- and parvocellular divisions to be composed of one population
with no compelling grounds for identifying any distinctive class. We
therefore share the conclusion of Derrington and Lennie
(1984)
that magno- and parvocellular neurons can be divided
only by chromatic properties (i.e., spatial opponency and cone inputs).
Anatomical effects of monocular deprivation
As noted by many previous studies (e.g., Headon and Powell
1973
; Sherman and Spear 1982
; Tigges et
al. 1984
; Vital-Durand et al. 1978
; von
Noorden and Crawford 1978
), cells in laminae driven by the
deprived eye were pale and shrunken compared with the nondeprived-eye
laminae. We also observed a decrease in immunoreactivity for the
Cat-301 antigen. This decrease was most prominent in the magnocellular
laminae, which seemed uniformly less reactive; we saw no sign that any
subset of Cat-301-positive cells remained unaffected. This is unlike
the cat, in which Cat-301 seems to specifically label Y cells, which
are lost after deprivation (Guimaraes et al. 1990
;
Hockfield and Sur 1990
; Sur et al. 198