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The Journal of Neuroscience, April 1, 2002, 22(7):2737-2747
Functional Asymmetries in ON and OFF Ganglion Cells of
Primate Retina
E. J.
Chichilnisky and
Rachel S.
Kalmar
Systems Neurobiology, The Salk Institute, La Jolla, California
92037, and University of California, San Diego, La Jolla, California
92037
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ABSTRACT |
Functional asymmetries in the ON and OFF pathways of the primate
visual system were examined using simultaneous multi-electrode recordings from dozens of retinal ganglion cells (RGCs) in
vitro. Light responses of RGCs were characterized using white
noise stimulation. Two distinct functional types of cells frequently
encountered, one ON and one OFF, had non-opponent spectral sensitivity,
relatively high response gain, transient light responses, and large
receptive fields (RFs) that tiled the region of retina recorded,
suggesting that they belonged to the same morphological cell class,
most likely parasol. Three principal functional asymmetries were
observed. (1) Receptive fields of ON cells were 20% larger in diameter
than those of OFF cells, resulting in higher full-field sensitivity. (2) ON cells had faster response kinetics than OFF cells, with a
10-20% shorter time to peak, trough and zero crossing in the biphasic
temporal impulse response. (3) ON cells had more nearly linear light
responses and were capable of signaling decrements, whereas OFF cells
had more strongly rectifying responses that provided little information
about increments. These findings suggest specific mechanistic
asymmetries in retinal ON and OFF circuits and differences in visual
performance on the basis of the activity of ON and OFF parasol cells.
Key words:
retinal ganglion cell; receptive field; monkey; retina; kinetics; dynamics; sensitivity; white noise; nonlinear
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INTRODUCTION |
The ON and OFF pathways of the
visual system (Hartline, 1938 ; Kuffler, 1953 ) are prototypical examples
of parallel processing in neural circuits. ON-OFF segregation begins
with the divergence of photoreceptor signals to sign-conserving and
sign-inverting second order (bipolar) retinal neurons (Werblin and
Dowling, 1969 ) and is preserved in the brain. These pathways have
generally been treated as symmetric systems with equal and opposite
light responses that primarily transmit information about increments
and decrements of light, respectively (for review, see Schiller, 1992 ).
For example, the parasol retinal ganglion cells in primates that
project to the magnocellular layers of the lateral geniculate nucleus
are composed of morphologically and physiologically similar ON and OFF
types, with opposite sign light responses and dendritic fields (DFs)
that tile the retina (Polyak, 1941 ; Watanabe and Rodieck, 1989 ;
Silveira and Perry, 1991 ; Dacey and Brace, 1992 ). However, some studies
have suggested that the ON and OFF pathways are not fully symmetric.
Psychophysical evidence has indicated asymmetries in perception and
detection of incremental and decremental stimuli (Bowen et al.,
1989 ; Wehrhahn and Rapf, 1992 ; Kremers et al., 1993 ), although it is
unclear whether psychophysical methods can truly isolate the ON and OFF
pathways or at what point in the visual system the observed asymmetries
arise. Anatomical evidence indicates that the dendritic fields of
parasol (human) and (rat, dog) ON retinal ganglion cells are larger
than their OFF counterparts (Peichl et al., 1987 ; Peichl, 1989 ; Dacey
and Petersen, 1992 ; Tauchi et al., 1992 ), suggesting asymmetries in
receptive field (RF) size. However, electrophysiological studies have
revealed little evidence of functional asymmetries in the ON and OFF
pathways (Linsenmeier et al., 1982 ; Kremers et al., 1993 ; Benardete and Kaplan, 1997 , 1999 ; Lankheet et al., 1998 ).
Using multi-electrode recordings, we demonstrate significant
asymmetries in spatial summation, kinetics, nonlinearity, and sensitivity in light responses of simultaneously recorded ON and OFF
ganglion cells of the macaque monkey retina. The ensembles of ON and
OFF cells recorded tiled the same retinal area and apparently represented the same morphological class, most likely parasol. ON-OFF
asymmetries were consistent within and across experimental preparations. Receptive field size asymmetries were consistent with
known asymmetries in dendritic fields. Kinetic asymmetries could
reflect distinct mechanisms governing the undershoot of biphasic light
responses. Nonlinearity asymmetries suggest differences in spike
threshold or basal transmitter release in ON and OFF retinal neurons.
Thus the ON and OFF pathways display significant functional asymmetries
that originate in the retinal circuitry and may influence visual
sensitivity and perception.
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MATERIALS AND METHODS |
Preparation. Eyes were obtained from terminally
anesthetized macaque monkeys (Macaca fascicularis, M. mulatta, M. radiata) used by other experimenters, in
accordance with institutional guidelines for the care and use of
animals. Immediately after enucleation, the anterior portion of the eye
and vitreous were removed in room light, and the eye cup was placed in
bicarbonate-buffered Ames' solution (Sigma, St. Louis, MO) and stored
in darkness for at least 20 min before dissection. Under infrared
illumination, pieces of retina 2-4 mm in diameter were cut from
regions 10-40° from the fovea and placed flat against a planar array
of 61 extracellular microelectrodes that were used to record action
potentials from retinal ganglion cells (Meister et al., 1994 ;
Chichilnisky and Baylor, 1999a ). The preparation was superfused
with Ames' solution bubbled with 95% O2 and 5%
CO2 and maintained at 35-36°C, pH 7.4. In most
experiments the piece of retina was separated from the retinal pigment
epithelium (RPE) before recording. In 5 of 13 preparations the RPE was
left attached. Results from RPE-attached preparations were similar to
results from isolated retina preparations.
Retinal eccentricity of some preparations was measured with a precision
of 1-2 mm. Eccentricities are expressed below as temporal equivalent,
because the contours of constant RGC density (and thus presumably
dendritic and receptive field size) in the macaque monkey retina are
approximately semicircular in the temporal half of the retina, but
elliptical with an aspect ratio of 0.61 in the nasal half (Perry and
Cowey, 1985 ; Watanabe and Rodieck, 1989 ). Thus a location X
mm nasal and Y mm superior (or inferior) to the fovea was
assigned an equivalent eccentricity of
. A location
X mm temporal and Y mm superior (or inferior) to the fovea was assigned an equivalent eccentricity of
. Visual angle
(A) in degrees from previous studies (Croner and
Kaplan, 1995 ) was converted to retinal eccentricity in millimeters
(E) by inverting the relation A = 0.1 + 4.21E + 0.038E2 (Drasdo and
Fowler, 1974 ; Dacey and Petersen, 1992 ).
Stimuli. The preparation was stimulated with the optically
reduced (1.0-1.3 mm diameter) image of a cathode ray tube computer display refreshing at 66.67 or 120 Hz, focused on the photoreceptor layer by a microscope objective, and centered on the 480-µm-diameter electrode array. Stimuli were attenuated to low photopic light levels
using neutral density filters. In isolated retina experiments the
stimulus was delivered from the photoreceptor side. In experiments in
which the RPE was attached, the preparation was stimulated from the
retinal ganglion cell side through the mostly transparent electrode
array. In the latter case the shadows cast by the platinized (black)
electrode tips, 5 µm in diameter and spaced 60 µm apart, had a
minimal influence on the intensity and spatial pattern of the stimulus,
because they occupied roughly 1% of the total area of the array and
were optically diffused by virtue of lying in a different focal plane
than the photoreceptors.
The stimulus consisted of a square lattice of randomly flickering
pixels that was presented for 15-45 min. Random flicker was created by
selecting the intensities of the red, green, and blue display phosphors
at each pixel location independently from a Gaussian or binary
(two-valued) distribution every 15 msec (66.67 Hz display) or 8.33 msec
(120 Hz display). This stimulus modulated photon absorptions
asynchronously in all three cone types. Pixel size varied between 24 and 72 µm at the retina in different experiments. The rms
contrast of the three phosphors on the display varied between 0.32 and
0.96; in each experiment the rms contrast of all three phosphors was equal.
The typical mean photon absorption rate for the long, middle, and short
wavelength sensitive cones was approximately equal to the absorption
that would have been caused by spatially uniform monochromatic lights
of wavelength 561, 530, and 430 nm and intensity 9200, 9200, and 5100 photons per
µm 2/sec 1,
respectively, incident on the photoreceptors. For RPE-attached preparations, this intensity includes a factor of 2 for the
light-funneling effect of the inner segments (Packer et al., 1996 ). In
some preparations the intensity was roughly double or half the above.
Recordings. Spikes were digitized at 20 kHz (Meister et al.,
1994 ; Litke, 1999 ) and stored for off-line analysis. Spikes from 15-85
cells were segregated by identifying distinct clusters of spike height
and width recorded on each electrode and verifying the presence of a
refractory period. For quantitative analysis of light responses, spike
counts from each cell were computed in time bins of 15 msec (66.67 Hz
display) or 8.33 msec (120 Hz display).
Model of light responses. Analysis of visual signaling
required a quantitative model of RGC light response that, unlike
classical models, accounts for significant nonlinearities demonstrated
below. Light responses were characterized using a linear-nonlinear
(LN) cascade model for firing rate as a function of the stimulus [for a description of the model and analysis, see Korenberg and Hunter (1986) , Chichilnisky (2001) ; for a test of the validity of the model in
the present experimental conditions, see Chichilnisky (2001) , Kim and
Rieke, (2001) ]. Briefly, it is assumed that (1) contrast modulations
over space and time are pooled linearly to create a generator
signal, and (2) spike rate at each point in time is determined
by a (generally nonlinear) function of the generator signal at the same
point in time. The parameters of this model are as follows:
w, the linear weighting of the stimulus over space and
recent time that creates the generator signal, and N, the
function that transforms the generator signal to spike rate. Thus, if
s is a vector the entries of which represent the contrast of
each phosphor at each spatial location over recent time, the
instantaneous firing rate is given by:
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(1)
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where · is the inner product of vectors. Under the assumptions
of the LN model, it can be shown that w is equal to the
spike-triggered average (STA) stimulus, that is, the average stimulus
over a period of time preceding a spike (Chichilnisky, 2001 ). This
period was chosen empirically to exceed the duration of the impulse
response of the cell. To complete the model for light response required only obtaining an estimate for N. The generator signal at
each time during stimulation was estimated by summing the elements of
the recent stimulus multiplied by a parametric fit to the STA (to
reduce estimation bias; see below). The spike rate associated with each
distinct value of the generator signal was obtained by averaging spike
counts over many time points in which nearly the same value of
the generator signal was observed. This procedure, repeated over the
range of observed values of the generator signal, yielded the
relationship between generator signal and average spike rate, that is,
the function N. This completes the model for light response.
Examples of the STA and nonlinearity for one cell are shown in Figure
1A.
Fitting and parameter estimation. Together, the weighting of
stimuli over space and time (w, equal to the STA) and the
response nonlinearity (N) provide a description of
the average response to any stimulus. Spatial, kinetic, and sensitivity
measures were obtained from smooth functional approximations to
w and N. The former was accurately described as
the product of a spatial sensitivity function, a temporal sensitivity
function, and a chromatic sensitivity function. The spatial sensitivity
function was defined as a difference of two-dimensional Gaussian
profiles (Rodieck, 1965 ) with common elliptical isosensitivity
contours, representing the center and surround of the RF:
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(2)
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Here v is two-dimensional vector that specifies a
spatial location, s(v) indicates the sensitivity at that
spatial location, u is a two-dimensional vector that
specifies the midpoint of the RF, Q is a 2 × 2 symmetric positive semi-definite matrix that specifies the elliptical
Gaussian shape of the RF center, k is a scalar that
specifies the relative strength of the surround, and
1/r is a scalar that specifies the relative size of
the surround.
The temporal sensitivity function specifies how strongly the stimulus
contrast at a time t before the present influences firing rate. This was given by the difference of two cascades of low-pass filters:
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(3)
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Here, t specifies time before the present,
f(t) is the sensitivity at that time, and n,
p1,
p2,
1, and
2 are free parameters.
Finally, chromatic sensitivity was captured by two additional scalars
representing the relative sensitivity to modulation of the three
phosphors (the time courses of the three phosphors in the STA were
always very nearly in a scalar relationship, consistent with dominant L
and M cone input; see Figs. 2, 8). The product of the spatial,
temporal, and chromatic sensitivities defined above determined the fit
to the STA (i.e., w).
The response nonlinearity N was well approximated using the
lower portion of a sigmoidal function:
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(4)
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where x is the generator signal, n(x) is
the firing rate, G(x) is the cumulative normal (indefinite
integral of standard normal distribution), and a,
b, and c are free parameters.
Together, these fits to w and N provide a full
parametric model of light response (see Eq. 1). In a typical
measurement such as that in Figure 1A, the STA was
obtained over a 30 × 30 spatial grid with three colors and 30 time bins (250 msec) per location, for a total of 81,000 values. The
model fit, shown in Figure 1B, described this STA
with 14 parameters. The nonlinearity was described by three parameters.
Parameters were selected to minimize mean squared error using Powell's
method (Press et al., 1988 ). Estimates of peak, trough, and zero
crossing of the STA time course, RF location, and value and slope of
nonlinearity were taken from these fits. RF diameter was defined as the
diameter of a circle with the same area as the 1 SD (elliptical)
boundary of the Gaussian center profile. RF integration area was
defined as 2 times the square of the diameter, that is, the volume
under the Gaussian center profile. Usually, spatially antagonistic
surrounds were weak relative to centers (Fig.
1); results obtained with single Gaussian
spatial profiles (k = 0) yielded the same conclusions in all analyses presented below.

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Figure 1.
Characterization of light response and parametric
fits. A, Left panel, The average stimulus
observed 33 msec (4 frames, near time-to-peak) before a spike in one
RGC. The dark central region reveals the receptive field
of the cell. Middle panel, Average time course of
contrast of the red, green, and
blue display phosphors in the 250 msec preceding a
spike, summed over 36 pixels in the center of the receptive field. The
dominant negative lobe indicates that this is an OFF cell. Right
panel, Average firing rate as a function of the generator
signal (stimulus weighted by STA) observed during white noise
stimulation. B, Parametric fits, as described in
Materials and Methods, to the corresponding panels in
A.
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Statistical comparison of each light response parameter (e.g., RF
diameter) for ON and OFF cells was performed by computing the mean
value of the parameter for ON and OFF cells in each preparation, µon and
µoff, dividing each mean by the pooled sample SD to obtain a normalized value, and then performing a
two-tailed nonparametric Wilcoxon order test (Rice, 1988 ) on pairs of
the form (µon/ ,
µoff/ ) accumulated from multiple
preparations. Whenever possible, parameters obtained directly from raw
data were examined to check that fits did not introduce systematic
errors. In all cases, raw data and fits yielded the same pattern of results.
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RESULTS |
Characterization of light response
Retinal ganglion cells were characterized and classified on the
basis of their responses to white noise stimulation (Sakai et al.,
1988 ; Chichilnisky, 2001 ). The stimulus was a square lattice of
randomly flickering pixels with no spatial, temporal, or chromatic structure. The light response properties of each cell were summarized by the spike-triggered average stimulus (STA). The STA is a
measure of how effectively stimuli at different locations and with
different colors are integrated by the cell over time to control firing (see Materials and Methods).
STAs from six simultaneously recorded cells are shown in Figure
2. For each cell, the average stimulus 33 msec before a spike is displayed as an image. The spatial RF of each
cell is indicated by the region of the image that deviates from the
gray background. The cells on the left (right) of Figure 2 were
predominantly excited by increases (decreases) in the intensity of the
three phosphors and were therefore classified as ON (OFF) cells.
Antagonistic RF surrounds are present in these images, although they
are weaker than the centers. The second panel for each cell shows the
time course of red, green, and blue phosphor intensities preceding a
spike, summed over the pixels in the RF center. These biphasic time
courses indicate how the cell integrated visual inputs of different
colors over recent time.

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Figure 2.
Characterization of light response for three ON
and three OFF macaque RGCs, recorded simultaneously. Three panels for
each cell show, from left to right, the
average stimulus observed 33 msec (4 frames, near time-to-peak) before
a spike, the time course of contrast of the red,
green, and blue display phosphors in the
200 msec preceding a spike, and the average firing rate as a function
of the generator signal (stimulus weighted by STA) observed during
white noise stimulation, in the same format as Figure
1A.
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The STA alone would provide a full description of RGC light responses
if responses were linear. Because they generally were not, a simple
nonlinear model was used to obtain a more accurate, quantitative
characterization (see Materials and Methods for details). In the model
it is assumed that (1) contrast modulations over space and time are
pooled linearly to create a generator signal, and (2) spike rate at
each point in time is given by a (generally nonlinear) function of the
generator signal at the same point in time. Under these conditions it
can be shown that the STA reveals the linear weighting (Chichilnisky,
2001 ). The relation between generator signal and firing rate can be
determined by comparing the STA-weighted stimulus to observed spike
counts. Examples are shown in the third panel for each cell in
Figure 2. If responses were linear, these data would fall on straight
lines; the departure from this prediction highlights the importance of
using a nonlinear model to characterize light response. The above model
can be used to predict the response to any stimulus, and empirical
tests indicate that it describes light responses fairly accurately in
the present conditions (Chichilnisky, 2001 ; Kim and Rieke, 2001 ).
Importantly, because this model allows for response nonlinearities such
as rectification and saturation, it makes weaker assumptions about light responses than commonly used strictly linear models.
Cell classification
Because distinct morphological cell classes have different light
responses, an analysis of ON-OFF asymmetries is only meaningful for
opposite sign cells of the same morphological class, e.g., parasol. A
category of cells was identified on the basis of RF size, response
kinetics, response gain, and tiling that apparently represents a single
morphological class, most likely parasol. The ON and OFF cells in
Figure 2 are examples.
Cell classification was performed as follows. Blue-on/yellow-off cells
in each preparation were easily identified on their color-opponent STA
time courses (Chichilnisky and Baylor, 1999a ). Cells with
opposite color opponency (blue-off/yellow-on) were not observed, so
these cells were excluded from further analysis. Among the remaining
cells, four distinct functional groups were routinely identified by
their stereotyped light response properties. Figure
3 shows such a classification in two
preparations. Scatter plots show the RF diameter and the peak amplitude
of the STA for each cell: ON cells fall on the right (positive STA
peak) and OFF cells on the left (negative STA peak). Within the ON and
OFF groups, clusters of cells with large and small RF sizes are
evident; large RF clusters are identified in the figure. Because the
anatomical identities of these cell groups are uncertain, they will be
referred to as the large (L)-ON, small (S)-ON, L-OFF, and S-OFF cells. The RFs of the L-ON and L-OFF groups often partially tiled the area of
retina recorded. In Figure 3, outlines of the RFs of all L-OFF and L-ON
cells from each preparation are shown above the scatter plots,
superimposed on the hexagonal boundary of the electrode array. These
RFs closely abutted with little overlap; neighboring RFs were separated
by 1-1.5 RF diameters. This tiling did not simply reflect the regular
spacing of electrodes because tiling with neighbor distances of
100-300 µm was observed in different preparations, whereas
inter-electrode spacing was always 60 µm.

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Figure 3.
Cell classification for two preparations
(A, B). A, Scatter plot
shows the RF diameter and peak STA contrast for each of 62 cells
recorded simultaneously. Clusters defining L-ON cells
(right) and L-OFF cells (left) are
indicated by ovals. Top panel shows
outlines of RFs (1 SD boundary of Gaussian fit; see Materials and
Methods) for all L-OFF cells and L-ON cells in this preparation.
B, Data from 85 cells recorded in a second preparation,
in the same format as A.
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Taken together, the clustering and tiling of L-ON and L-OFF RFs suggest
that each of these cell groups corresponded to a single morphological
cell type, similar to the tiling reported in rabbit retina (Devries and
Baylor, 1997 ), which probably reflected complete non-overlapping
coverage of the retina by the dendritic fields of cells of each type
(Wassle et al., 1981 ). Two observations further suggest that the L-ON
and L-OFF groups are of the same morphological class, e.g., parasol.
First, the L-ON and L-OFF cells were more similar to one another in RF
size, kinetics, response gain (Fig. 4),
and chromatic sensitivity than to simultaneously recorded S-ON, S-OFF,
and blue-on/yellow-off cells. Second, consistent clustering of cell
groups in different preparations (Fig. 3) suggests that the L-ON and
L-OFF groups represent each cell type commonly observed, probably
because their morphological and electrotonic properties led to
favorable sampling by the multi-electrode arrays used. Presumably,
their opposite-sign morphologically similar counterparts would also be
sampled frequently, particularly in the peripheral retina where
ganglion cell bodies form a monolayer and cell-type specific somatic
lamination (Perry and Silveira, 1988 ) cannot introduce additional
sampling biases. Thus it is likely that L-ON and L-OFF cells are of the
same class. Two observations further suggest that the L-ON and L-OFF
cells are parasol cells (Polyak, 1941 ).

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Figure 4.
Kinetics and response gain for cells with
large and small RFs, for two preparations (A,
B). A, Left, Response gain
(derivative of spike rate with respect to contrast of an achromatic 15 msec full-field flash, deduced from white noise measurements) and index
of biphasicity (absolute value of ratio of trough to peak of STA time
course) for all L-ON and all S-ON cells in the preparation of Figure
3A. L-ON cells are shown by filled
symbols; S-ON cells are shown by open symbols.
Right, Same measurements for all L-OFF and S-OFF cells
in the same preparation. L-OFF cells are shown by filled
symbols; S-OFF cells are shown by open symbols.
B, Same as A, for the data set from
Figure 3B.
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First, L-ON and L-OFF cells had higher response gain and more biphasic,
or transient, light responses than their S-ON and S-OFF counterparts.
The left panel of Figure 4A
shows response gain as a function of an index of the biphasicity of the
STA for the L-ON and S-ON cells shown in Figure 3A. The
right panel shows the same plot for L-OFF and S-OFF cells
from the same preparation. L-ON and L-OFF cells generally had higher
response gain and more biphasic light responses than simultaneously
recorded S-ON and S-OFF cells, respectively. Figure
4B shows the same trend for the cells of Figure
3B. Similar results were observed for L-ON and S-ON cells in
seven of eight other preparations; few S-OFF cells were observed in
other preparations.
Second, L-ON and L-OFF cells had RF diameters that would be expected
for parasol cells at the same retinal eccentricity. Because no survey
exists of parasol cell RF diameters as a function of eccentricity, this
was determined as follows. The small squares in Figure
5 show dendritic field diameters
of parasol cells as a function of retinal eccentricity (Watanabe and
Rodieck, 1989 ). The open circles show RF diameters (twice
the SD of Gaussian fits) of magnocellular-projecting RGCs recorded
in vivo (Croner and Kaplan, 1995 ) that are presumably mostly
parasol cells (Lee, 1996 ). Because it is unclear how RF diameters
measured this way should compare with DF diameters, the latter have
been scaled to bring the RF diameters into registry with DF diameters.
Finally, filled circles indicate the mean L-ON and L-OFF RF
diameters from nine preparations in which eccentricity information was
available, scaled by the same factor. These values fall within the
distribution of parasol DFs.

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Figure 5.
Comparison of L-ON and L-OFF cells to
parasol cells. Small squares show DF field
diameters of individual parasol cells as a function of retinal
eccentricity, replotted from Watanabe and Rodieck (1989) . Open
circles show RF diameters of individual
magnocellular-projecting RGCs, replotted from Croner and Kaplan (1995) ,
multiplied by 1.57, a value chosen by linear regression to bring RF
diameters into registry with DF diameters. Filled
circles show mean RF diameters of all L-ON and L-OFF cells from
each of nine preparations, also multiplied by 1.57.
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The differences in response gain and kinetics in Figure 4 would be
expected (Lee, 1996 ) if L-ON and L-OFF cells corresponded to parasol
cells and S-ON and S-OFF cells corresponded to midget cells [note that
midget cells in the peripheral retina do not display color opponency
(Dacey, 2000 )]. The receptive field diameters in Figure 5 would be
expected if L-ON and L-OFF cells were parasol cells. Furthermore,
simultaneously recorded blue-on/yellow-off cells had RF diameters
comparable to those of L-ON and L-OFF cells (Chichilnisky and Baylor,
1999a ), and S-ON and S-OFF cell RFs were roughly half as large
(Fig. 3). These proportions roughly match the relative DF diameters of
the midget, parasol, and small bistratified cells that together
constitute a majority of RGCs (Perry et al., 1984 ; Watanabe and
Rodieck, 1989 ) and are frequently encountered with extracellular
electrodes (Lee, 1996 ). In the peripheral primate retina, roughly 45%
of all RGCs are midgets, 20% are parasols, and 10% are small
bistratified (Dacey, 1994 ). Thus for the L-ON and L-OFF cells to be
other than parasols would require the presence of another morphological
class of RGC with RF size and density similar to parasols, constituting
a majority of the remaining 25% of RGCs in the peripheral retina. A
cell class of this density has not been reported.
It is assumed in what follows that the L-ON and L-OFF cells defined
above are of the same morphological class, most likely parasol. The
visual signaling properties of L-ON and L-OFF cells differed in three
principal respects: RF size, kinetics, and linearity.
Larger receptive fields in ON cells
L-ON cells had consistently larger RFs than L-OFF cells. This can
be seen in Figure 3, where for each preparation the distribution of
L-ON cell RF sizes is slightly higher than that of L-OFF cell RF sizes.
The asymmetry in RF size can be seen directly in Figure 6, which shows the RFs of nine L-ON and
nine L-OFF cells recorded simultaneously in one preparation. All L-OFF
cells recorded are shown, and the nine L-ON cells shown uniformly span
the range from largest to smallest L-ON RF size recorded. Both groups
of cells are sorted by RF size. Clearly, as would be predicted from the
plots in Figure 3, the distribution of RF sizes of L-ON cells and L-OFF
cells overlaps significantly. However, when the largest (top
row), intermediate (middle row), and smallest
(bottom row) RFs in Figure 6 are compared, it is clear that
L-ON cells had, on average, slightly larger RFs than L-OFF cells. In
this preparation, the mean (±SEM) RF diameter for L-ON cells was 100 (± 3.2) µm and for L-OFF cells was 87 (± 4.5) µm. Figure 2 shows
another example of RF size asymmetry. This trend was consistent across preparations. Each point in Figure
7A shows the mean and SEM of L-ON and L-OFF RF sizes in one preparation; 17 preparations are represented. The points fall below the identity diagonal, indicating larger L-ON cell RFs. A linear regression to these data indicates that
L-ON cells had, on average, 21% larger RF diameters than L-OFF cells
(p < 0.001; see Materials and Methods).

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Figure 6.
Receptive field size asymmetry. For nine L-ON
(left) and nine L-OFF (right) cells
recorded simultaneously, the average stimulus on the display 45 msec (3 frames, near time-to-peak) before a spike is shown in the same format
as Figure 1. Cells of each group are sorted by RF size, from largest
(top left) to smallest (bottom right).
The RF location of each cell is different; these images have been
cropped to the region immediately surrounding the RF.
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Figure 7.
Receptive field size asymmetry summary.
A, Each point shows the mean receptive
field diameter of all L-ON cells and all L-OFF cells recorded in one
preparation. Error bars, sometimes smaller than points, indicate 1 SEM.
The diagonal line indicates equality for L-ON and L-OFF
cells. Data from 169 L-ON and 162 L-OFF cells from 17 preparations are
represented. B, Each point shows the
square root of the mean number of pixels for L-ON and L-OFF cells for
which the rms energy in the STA exceeded 25% of the rms energy of the
strongest pixel.
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Because RF size was estimated from Gaussian fits, deviations of actual
RF profiles from an idealized Gaussian shape could bias RF size
estimates and artifactually indicate asymmetries. Two considerations
argue against this. First, spatially antagonistic surrounds, generally
weak in the present data (e.g., see Figs. 2, 6), were unlikely to
complicate RF size estimates. The RF diameters shown in Figure
7A were estimated from fits that included a surround the
size and relative strength of which were free parameters; the size of
the center is shown. Fits obtained without allowing for surrounds
yielded similar results. Second, RF sizes measured without parametric
models show the same asymmetry. For each cell, the number of pixels
(spatial locations) at which the rms contrast in the STA exceeded 25%
of the rms contrast of the strongest pixel was determined. The square
root of this number (roughly proportional to diameter) is shown in
Figure 7B for L-ON and L-OFF cells from the same
preparations as Figure 7A. In all preparations, L-ON cell
RFs on average contained a larger number of such pixels than L-OFF cell
RFs (p < 0.001).
Faster response kinetics in ON cells
L-ON cells displayed consistently faster light responses than
L-OFF cells. Figure 8 shows the STA time
course (which can be interpreted as the time-reversed impulse response)
of six L-ON and six L-OFF cells in one preparation. The primary lobe of
the STA time course for the L-ON cells was visibly narrower than that of the L-OFF cells. This was quantified by examining the time of zero
crossing, relative to the time of the spike, obtained from smooth
parametric fits to time courses (see Materials and Methods). The mean
time to zero crossing for 13 L-ON cells recorded in this preparation
was shorter (62 ± 1 msec) than for 10 L-OFF cells (71 ± 1 msec). A second example is shown in Figure 2. This kinetic asymmetry
was consistent across preparations. Each point in Figure
9B shows the mean and SEM of
L-ON and L-OFF time to zero crossing in one preparation; data from 17 preparations are shown. In 16 of 17 preparations the points fall above
the identity diagonal, indicating faster L-ON cell kinetics
(p < 0.001). A linear regression indicates that
L-OFF cells had, on average, 23% longer time to zero crossing than
L-ON cells.

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Figure 8.
Kinetic asymmetry. STA time courses are shown for
six L-ON (left) and six L-OFF (right)
cells recorded simultaneously. Each panel shows the
average time course of red, green, and
blue display phosophor contrast in the 250 msec
preceding a spike, summed over the center of the RF, as in Figure
1.
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Figure 9.
Kinetic asymmetry summary. A, Each
point shows the mean time-to-peak of the STA time course
for all L-ON cells and all L-OFF cells recorded in one preparation.
Error bars indicate 1 SEM. Data from 169 L-ON and 162 L-OFF cells from
17 preparations are represented. B, Mean time to zero
crossing for L-ON and L-OFF cells. C, Mean time to
trough for L-ON and L-OFF cells.
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The time-to-peak of the STA was also usually shorter for L-ON cells.
This was more difficult to observe in individual plots such as those in
Figure 8, because of the coarse (15 or 8.33 msec) refresh interval of
the stimulus display and consequent temporal sampling of the STA.
However, averaged data from many cells and preparations reveal the
trend clearly. Each point in Figure 9A shows the mean and
SEM of L-ON and L-OFF time-to-peak in one preparation. The points fall
mostly above the identity diagonal, indicating faster L-ON cell
kinetics (p = 0.006). A linear regression
indicates that L-OFF cells had, on average, 13% longer time to peak.
Finally, the time to trough (extreme point of undershoot in STA time
course) was on average 26% longer for L-OFF cells
(p < 0.001), as can be seen in Figure
9C. Essentially identical results were obtained by measuring
time-to-peak, zero crossing, and trough from the raw STA rather
than parametric fits.
More linear light responses in ON cells
Although both L-ON and L-OFF cells displayed light response
nonlinearity, the nonlinearity in L-OFF cells was more extreme. This is
shown in the plots of Figure 10. Each
panel shows spike rate as a function of the generator signal (stimulus
weighted by STA, i.e., effective contrast) for one cell. For ON cells, incremental pulses of light correspond to positive generator signal, whereas decrements correspond to negative generator signal; for OFF
cells the reverse holds. If light responses in RGCs were linear, these
data would fall on straight lines. Both L-ON and L-OFF cells clearly
displayed significant nonlinearities. However, over the stimulus range
examined, L-OFF cells showed stronger rectification. This is evidenced
by the sharp bend near zero for L-OFF cells compared with the more
gentle curvature for L-ON cells. In fact, the L-OFF cell nonlinearity
was nearly flat for negative generator values, whereas for L-ON cells
it was not. This implies that L-ON cells provided graded responses to
decrements of light, whereas L-OFF cells provided a limited
representation of increments. A second example is shown in Figure
2.

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Figure 10.
Nonlinearity asymmetry. Each panel
shows firing rate as a function of generator signal (stimulus weighted
by STA) for one cell obtained during white noise stimulation, as in
Figure 1. Data are shown for six L-ON cells (left) and
six L-OFF cells (right) recorded simultaneously.
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This asymmetry was summarized by computing an index of nonlinearity,
the logarithm of the ratio of the slope of the nonlinearity at maximum
to the slope at zero. The mean nonlinearity index for 11 L-ON cells was
0.1 ± 0.02 and for 8 L-OFF cells was 1.1 ± 0.05 in the
preparation of Figure 10. This asymmetry was consistent across
preparations. Each point in Figure
11A shows the mean
and SEM of the index of nonlinearity for all L-ON and L-OFF cells in
each preparation. In 16 of 17 preparations, L-ON cells showed more
linear light responses than L-OFF cells (p < 0.001).

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Figure 11.
Nonlinearity, gain, and SNR asymmetry
summary. A, Each point shows the mean
nonlinearity index for all L-ON cells and all L-OFF cells recorded in
one preparation. Error bars indicate 1 SEM. Nonlinearity index is the
logarithm of the ratio of the slope of the nonlinearity at the maximum
generator signal value observed to the slope at zero generator signal.
Data from 169 L-ON and 162 L-OFF cells from 17 preparations are
represented. B, Mean logarithm of response gain for L-ON
cells and L-OFF cells. Response gain is the derivative of firing rate
(spikes per second) with respect to the contrast of a brief (15 or 8.33 msec) achromatic full-field flash deduced from white noise
measurements. C, Mean logarithm of signal-to-noise ratio
(SNR) for L-ON and L-OFF cells. SNR is defined as the
response gain divided by the SD of spike counts observed at zero
generator signal.
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Other properties
The mean firing rate of L-ON and L-OFF cells during white noise
stimulation varied between 5 and 30 Hz across preparations, but the
firing rate of L-ON cells tended to exceed that of L-OFF cells (13 of
17 preparations; p = 0.005). The firing rate asymmetry was also present at times when the white noise provided no net stimulation, i.e., when the generator signal was zero, equivalent to a
steady uniform background (14 of 17 preparations; p = 0.002), and thus was consistent with previous findings (Troy and
Robson, 1992 ; Kremers et al., 1993 ) [but see Troy and Lee (1994) ,
Benardete and Kaplan (1997 , 1999 )]. Color properties of L-ON and L-OFF
cells were probed by comparing the mean ratio of the red to the green, or red to blue, phosphor contribution to the STA. No color asymmetry was observed (p = 0.13 and p = 0.79, respectively), consistent with nonselective inputs from a random
cone mosaic to both cell types.
Consequences for visual sensitivity
Asymmetries in RF size, kinetics, response nonlinearity, and
firing rate could have significant consequences for the strength and
fidelity of visual signals. Response gain (the derivative of spike rate
with respect to the contrast of a full-field flash) was determined by
multiplying the peak of the STA by the integration area of the RF and
the slope of the nonlinearity at zero generator signal. Results are
shown in Figure 11B. In most cases, L-ON cells displayed higher gain than L-OFF cells (14 of 17 preparations; p = 0.003). Asymmetry in response gain at the peak of
the RF (gain divided by RF integration area) was less systematic (12 of
17 preparations; p = 0.013).
L-ON cells also provided a higher fidelity neural representation of
weak full-field flashes. The signal-to-noise ratio (SNR) was estimated
by dividing the response gain by the SD of spike counts observed at
zero generator signal. The results in Figure 11C show that
L-ON cells usually had higher SNR than L-OFF cells (13 of 17 preparations; p = 0.006), indicating a higher fidelity encoding of full-field stimuli. However, the peak SNR was not significantly greater for L-ON cells (8 of 17 preparations;
p = 0.79), indicating that the higher fidelity was
attributable to larger RF size.
 |
DISCUSSION |
Morphological types of cells recorded
The significance of the ON-OFF asymmetries described here relies
on the L-ON and L-OFF cells recorded in each preparation being of the
same morphological class, e.g., parasol, because cells with different
morphologies generally have different response properties. The L-ON and
L-OFF cell groups had distinctive and similar response properties,
tiled the retina, and were both well sampled by a common set of
electrodes, suggesting that they are of the same morphological class.
The RF size, response kinetics and gain, density, and sampling
frequency of L-ON and L-OFF cells all suggest that they are parasol cells.
Two alternative possibilities could explain the consistent asymmetries
observed here. (1) The recordings were heavily biased toward a single
type of ON cell and a morphologically different type of OFF cell that
have similar spatial and kinetic properties, whereas the opposite-sign
cells of each type do not exist or were systematically excluded. (2)
Different types of ON and OFF cells were sampled in different
recordings, yet the RFs of the ON cell types recorded were
systematically larger, the kinetics faster, and the nonlinearities
milder than those of the OFF cell types recorded. These possibilities
seem remote.
Mechanisms of asymmetry
The RF size asymmetry could be created by larger DFs in L-ON cells
collecting inputs via bipolar cells from a larger region of the
photoreceptor mosaic. Indeed, ON parasol and midget cells in human
retina have DFs about 30 and 50% larger than OFF parasol and midget
cells, respectively (Dacey and Petersen, 1992 ). Also, ON cells in
rat (Peichl, 1989 ; Tauchi et al., 1992 ) and dog (Peichl et al., 1987 )
have larger DFs than OFF cells. An alternative explanation might be
that L-ON cells have stronger reciprocal excitatory connections that
effectively mix the RFs of neighboring cells, as was reported for brisk
transient cells in rabbit retina (DeVries, 1999 ). Such reciprocal
excitation was not evident in the present recordings, and synchronized
firing in neighboring cells (Chichilnisky and Baylor, 1999b ),
defined as the number of spikes synchronized within ±5 msec divided by
the number expected by chance, was not systematically stronger in L-ON
cells than L-OFF cells (8 of 17 preparations; p = 0.94).
One potential source of kinetic asymmetry is the metabotropic glutamate
receptor in ON-bipolars that inverts the sign of the light response
from that in photoreceptors using a second-messenger cascade (Nawy and
Jahr, 1990 ). The extra biochemical steps involved in creating the
ON-bipolar response, compared with the directly gated ionic currents
underlying the OFF-bipolar response, might be expected to result in
slower transfer of visual signals. Indeed, response latency, estimated
as the time to 5% of the peak of the STA, was on average 10% (1-2
msec) shorter for L-OFF cells than for L-ON cells (13 of 17 preparations; p = 0.024). This asymmetry must be
treated as tentative because it is small compared with the temporal
discretization of the stimulus. Surprisingly, for the more
reliably measured features of the light response time to peak, zero
crossing, and trough L-ON cells displayed faster kinetics than L-OFF
cells. This suggests that kinetic asymmetries in mechanisms responsible
for later phases of the light response oppose and overwhelm those
introduced at the photoreceptor synapse.
Larger ON RFs could shorten the time-to-peak if input from more
photoreceptors caused a stronger light response that was followed by
saturation. This would not explain the shorter time to zero crossing.
Larger RFs could cause stronger adaptation to contrast (Shapley and
Victor, 1981 ) or mean light level (Enroth-Cugell and Shapley, 1973 ),
resulting in faster light responses [but see Cleland and Freeman
(1988) ]. This seems unlikely because in each preparation kinetics were
highly stereotyped within L-ON and L-OFF populations (Fig. 8), although
L-ON and L-OFF RF sizes typically varied by more than the mean
difference between them (Figs. 3, 6). Alternatively, the mechanisms of
adaptation in ON and OFF circuits may differ (Chander and Chichilnisky,
2001 ; Kim and Rieke, 2001 ). Another possibility is that the mechanisms
that create the undershoot of the biphasic light response, perhaps in
the inner retina, could counteract the primary lobe of the response sooner or more strongly in L-ON cells. Indeed, the mechanisms of
inhibition differ for ON and OFF cells in guinea pig (Demb et al.,
2001 ).
There are at least two possible sources of asymmetries in nonlinearity.
First, L-OFF cells could have a higher spike threshold relative to
resting potential, raising the net stimulation required to enter a
linear range of light response. Second, basal transmitter release rates
could be lower in the bipolars that provide input to L-OFF cells,
rectifying the response near zero contrast (Demb et al., 2001 ).
Consistent with both possibilities, L-OFF cells usually displayed lower
firing rates.
The higher fidelity (SNR) of L-ON responses was apparently caused by
the integrated inputs from more photoreceptors and bipolars overwhelming sources of noise, because the SNR at the peak of the RF
was not asymmetric. Surprisingly, the peak response gain in L-ON cells
was at least as high as that in L-OFF cells. This is the reverse of the
dependence of peak gain on receptive field size (eccentricity) reported
in cat RGCs (Linsenmeier et al., 1982 ) that is attributable to denser
dendritic branching in cells with smaller DFs (Kier et al., 1995 ). One
possibility is that smaller L-OFF cell dendritic fields do not have
correspondingly denser branching than nearby L-ON cells, but this
interpretation is complicated by the significant effect of response
nonlinearity on gain that was not accounted for in previous studies.
Note that, as in previous studies, the present conclusions regarding
gain and SNR depend strongly on the model for light response.
Previous physiological findings
One previous study described slower kinetics in OFF than ON
color-opponent parvocellular-projecting RGCs (Lankheet et al., 1998 ),
but others reported no obvious asymmetries between ON and OFF cells of
the same functional class, including magnocellular-projecting (probably
parasol) and parvocellular-projecting cells (Kremers et al., 1993 ;
Benardete and Kaplan, 1997 , 1999 ) and cat X and Y cells [but see
Hammond (1974) and Linsenmeier et al. (1982) ]. Several methodological
differences could explain the lack of strong evidence for asymmetries
in previous studies.
First, previous studies relied on sequential characterization of single
cells. Variation in response properties over time or across animals
could obscure ON-OFF asymmetries. Previous studies also examined cells
over a range of eccentricities, rather than a collection of cells in a
small area. Variability in RF size and response kinetics with
eccentricity could obscure ON-OFF asymmetries; in the present
data, this variation was often larger than the mean asymmetry observed
within a preparation (Figs. 7, 9).
Second, previous studies used sinusoidally modulated grating stimuli
and harmonic analysis to characterize spatial and temporal sensitivity
assuming that RGC light responses are strictly linear, an approximation
that may contribute to measurement error. The white noise method used
here allows for instantaneous response nonlinearities such as spike
generation or saturation, providing a more realistic description and
empirically revealing significant nonlinearities (Fig. 2). Also,
harmonic stimuli were not as completely interleaved as white noise,
making the analysis less robust to adaptation and nonstationarities in
recording, and circular symmetry of RFs was assumed in previous work;
Figure 3 indicates that RFs often deviate from this assumption. These
differences in analysis techniques might have introduced error in
previous experiments that obscured ON-OFF asymmetries.
Finally, it is possible that differences between the in
vitro preparation used here and the in vivo
anesthetized preparations used in previous studies contributed to the
discrepancy. Note that asymmetries were observed both in isolated
retina and in RPE-attached preparations.
Asymmetries in central visual pathways
Numerous psychophysical experiments have suggested asymmetries in
visual sensitivity and perception that might reflect asymmetries in the
ON and OFF pathways. For example, decrements are more easily detected
than increments (Bowen et al., 1989 ; Kremers et al., 1993 ), and
direction discrimination is more strongly dependent on spatial
displacement for decrements than increments (Wehrhahn and Rapf, 1992 ).
However, several factors complicate the interpretation of
psychophysical findings in terms of ON and OFF neurons.
First, it is not clear how well ON and OFF cells can be selectively
recruited by choice of visual stimuli. Typically, transient increments
and decrements have been used to isolate the ON and OFF pathways,
supported by evidence from pharmacological blockade of the ON
pathway (Schiller et al., 1986 ), but L-ON cells clearly provide graded
responses to decrements. Second, comparison of psychophysical and
neurophysiological measurements requires quantitative detail. Although
lower psychophysical detection thresholds for decrements could suggest
higher sensitivity in OFF cells, the gain and SNR are higher for L-ON
cells. The psychophysical asymmetry could instead result from
decrements being encoded by both ON and OFF cells and increments being
encoded primarily by ON cells. Also, if cells with smaller RFs are more
closely spaced (Peichl, 1989 ), a larger number of OFF cells than ON
cells may encode a given stimulus, offsetting higher SNR in individual
ON cells. A third issue is that because many cell types at many stages
of the visual pathways participate in the response to a stimulus, it is
difficult to infer where psychophysical asymmetries arise. These
asymmetries could reflect the existence of cell types for which no
corresponding opposite-sign cells exist, rather than asymmetries
between ON and OFF cells of the same morphological class.
These issues highlight the difficulty in interpreting attempts to
compare the ON and OFF pathways in psychophysical experiments, but
ultimately the significance of ON-OFF asymmetry depends on its
consequences for visual behavior. The present results suggest that
visual tasks which rely primarily on ON and OFF parasol cells should
exhibit differences in spatial resolution, temporal resolution, and
response as a function of contrast.
 |
FOOTNOTES |
Received July 16, 2001; revised Jan. 7, 2002; accepted Jan. 8, 2002.
This work was supported by National Institutes of Health Grant
EY-13150, a Sloan Research Fellowship, a McKnight Scholar's Award
(E.J.C.), and a University of California, San Diego
Undergraduate Research Scholarship (R.S.K.). We thank E. Callaway, S. Zola, and T. Albright for providing access to tissue, D. Baylor, E. Callaway, J. Demb, S. du Lac, and F. Rieke for useful discussions, A. Litke and colleagues for technology development, D. Chander for
assistance during experiments, and S. Barry and R. Roder for technical assistance.
Correspondence should be addressed to E. J. Chichilnisky, Systems
Neurobiology, The Salk Institute, 10010 North Torrey Pines Road, La
Jolla, CA 92037-1099. E-mail: ej{at}salk.edu.
 |
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Organization of the retina of the mudpuppy, Necturus maculosus. II. Intracellular recording.
J Neurophysiol
32:339-355[Free Full Text].
Copyright © 2002 Society for Neuroscience 0270-6474/02/2272737-11$05.00/0
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