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The Journal of Neuroscience, July 15, 1999, 19(14):6145-6156
Neural Correlates of Perceived Brightness in the Retina, Lateral
Geniculate Nucleus, and Striate Cortex
Andrew F.
Rossi and
Michael A.
Paradiso
Department of Neuroscience, Brown University, Providence, Rhode
Island 02912
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ABSTRACT |
Brightness changes can be induced in a static gray field by
modulating the luminance of surrounding areas. We used this induction phenomenon to investigate the neural representation of perceived brightness. Extracellular recordings were made in striate cortex, the
lateral geniculate nucleus (LGN), and the optic tract of anesthetized cats using stimuli that produced brightness induction. While a cell's
receptive field (RF) was covered by uniform gray illumination, the
luminance of rectangular flanking regions was modulated sinusoidally in
time, inducing brightness changes in the RF. We looked for a
correspondence between the modulation of a cell's response and stimulus conditions that did or did not produce perceptual changes in
brightness. We found that the responses of retinal ganglion cell axons
in the optic tract were never correlated with brightness. On the other
hand, many neurons in striate cortex and a small fraction in the LGN
responded in a phase-locked manner at the temporal frequency of the
flank modulation, even though the flanks were 3-7° beyond the edges
of the RF. Only in striate cortex were cells found that had responses
correlated with brightness under all stimulus conditions. These
findings suggest that brightness information is explicitly represented
in the responses of neurons in striate cortex as part of a neural
representation of object surfaces.
Key words:
brightness; striate cortex; LGN; optic tract; surface
perception; vision
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INTRODUCTION |
Physiological studies of the visual
system have demonstrated that beyond the initial photoreceptor level of
the retina, neurons are primarily responsive to luminance contrast
within their receptive fields (Kuffler, 1953 ; Hubel and Wiesel, 1962).
This apparent bias toward contrast makes it unclear how the visual
system determines the perceptual properties we attribute to areas
bounded by contours, such as brightness and color.
Psychophysical studies have demonstrated that the perceived brightness
and color of an area can be greatly influenced by the properties of
neighboring and more distant regions. For example, in brightness
induction, a gray patch on a bright background appears darker than the
same gray patch on a dark background. If the background luminance is
sinusoidally modulated in time, the brightness of the constant gray
patch appears to change in antiphase to the background even though the
patch is physically constant. This dynamic version of brightness
induction is visible only at surprisingly low temporal frequencies of
the background luminance modulation (below ~2.5 Hz), above which the
central gray patch appears constant in brightness (DeValois et al.,
1986; Rossi and Paradiso, 1996). The low temporal cutoff of dynamic
induction is consistent with other studies (Paradiso and Nakayama,
1991; Paradiso and Hahn, 1996), suggesting that a relatively slow
mechanism integrates information over large areas of the visual field
to assign the brightness we perceive at a given location.
Brightness induction can be produced in test patches that are much
larger than receptive fields (RFs) in the retina, lateral geniculate
nucleus (LGN), and striate cortex. If cells in these areas play a role
in the perceptual effect, the underlying neural interactions presumably
come from outside the small receptive fields. Numerous studies have
shown that across visual areas the response of a neuron to contours
within the RF can be significantly affected by stimuli presented
outside the RF (Maffei and Fiorentini, 1976; Allman et al., 1985;
Gilbert and Wiesel, 1990; DeAngelis et al., 1992; Sillito et al., 1995;
Toth et al., 1996; Levitt and Lund, 1997). These surround effects
suggest that individual neurons are capable of integrating information
over large areas of the visual field in the determination of a response
that is context dependent.
Virtually all of the previous studies examining surround interactions
in striate cortex used gratings or bars of light as stimuli. This is
consistent with the hypothesized role of V1 in form vision. However,
recent work from our laboratory suggests that a significant percentage
of neurons in striate cortex also integrate surface information over a
spatial scale comparable to perceptual interactions (MacEvoy et al.,
1998) and convey information about brightness (Rossi et al., 1996).
Recent reports from other laboratories also support the hypothesis that
surface information is represented in the responses of V1 neurons
(Lamme, 1995; Komatsu et al., 1996; Lee et al., 1998). In the present
study, we set out to further characterize brightness-associated
responses in striate cortex and to assess whether such responses
originate in the retina, LGN, or striate cortex.
A portion of the results from the cortical recordings has been
published previously (Rossi et al., 1996).
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MATERIALS AND METHODS |
Animal preparation. Twenty-two adult cats, ranging in
weight from 2.5 to 5.5 kg, were used for this study. All procedures were conducted in accordance with National Institutes of Health guidelines and were approved by Brown University's Institutional Animal Care and Use Committee. Animals were initially sedated with an
injection of acepromazine (0.11 mg/kg, i.m.) accompanied by atropine
sulfate (0.05 mg/kg, i.m.), and a surgical level of anesthesia was
achieved with sodium thiopental (initial dose 20 mg/kg, i.v.,
supplemented as needed). A tracheotomy was performed, and the animal
intubated. The animal was then paralyzed with an intravenous infusion
of atracurium besylate (initial dose 5 mg, 0.6-1.2
mg · kg 1 · hr1) and
artificially respired. The stroke rate and volume of the respirator
were adjusted to maintain an end-tidal CO2 between 3.5 and
4.0%. Rectal temperature was maintained near 38°C with a heating
pad. Initially, sodium thiopental was infused continuously at the rate
of 2 mg · kg1 · hr1.
During the experiment, EKG and EEG (via epidural wires) were monitored, and adjustments in the rate of infusion were made to maintain the proper level of anesthesia. Pupils were dilated with 1%
atropine sulfate, and the nictitating membranes were retracted with
10% phenylephrine. The accommodative power of the eyes was adjusted so
that the eyes were focused on a tangent screen 57 cm away. This was
accomplished by choosing the correct power contact lens that produced a
sharp image of the retinal vasculature, which was back-projected on the
tangent screen (tapetal reflection method). The positions of retinal
landmarks were mapped on the tangent screen to estimate the
eccentricity of receptive fields.
Recordings were made in three different components of the visual
system: striate cortex, LGN, and optic tract. For the cortical recordings, a 2 × 2 mm craniotomy was made above the central
visual field representation of striate cortex, and a small portion of the dura was resected. A glass-insulated tungsten electrode was then
lowered to the cortical surface, and the craniotomy was filled with
agar to minimize motion of the brain. For the LGN and optic tract
recordings, a craniotomy was made around A9L6. Recordings of geniculate
neurons were made in the A and A1 laminae. Recordings from axons of
retinal ganglion cells were made by positioning the electrode in the
optic tract ventral to the LGN.
Stimuli and procedure. A window discriminator was used to
isolate the response of a single neuron based on the amplitude and slope of the action potential waveform. When the response of a neuron
was isolated in striate cortex, LGN, or optic tract, the receptive
field was mapped on the tangent screen using a hand-held stimulator.
Boundaries of the receptive field were determined using moving and
flashed bars and spots of light. In striate cortex, properties
including orientation selectivity, ocular dominance, end-stopping, and
direction selectivity were noted. In the LGN and optic tract, linearity
was tested with counterphased sinewave luminance gratings. All further
visual testing was conducted with the automated presentation of
computer-generated stimuli. Stimuli were generated by a Number Nine
Graphics Board installed in a PC clone and displayed on a 27 inch
monitor (NEC 4PG) with 640 × 480 pixel resolution and a refresh
rate of 60 Hz. Stimuli were presented monocularly to the eye that
responded best in previous testing. The key experimental stimulus
configuration is shown in Figure
1A,B. A static gray
central region was flanked on either side by regions where the
luminance was modulated sinusoidally in time by lookup table animation.
This produced brightness changes in the static center region, roughly
in antiphase to the luminance modulation of the flanks (Fig.
1C). The luminance of the static, central portion of the
stimulus was 30 cd/m2. The luminance of the flanks
was modulated about a mean of 30 cd/m2 such that the
stimulus had a 95% Michelson contrast
[(Lmax  Lmin/Lmax + Lmin)] when the luminance was maximal
and minimal. For all stimuli, the starting phase of the luminance
modulation was a luminance increment from the mean value (i.e., sine
phase). Photodiodes were used to confirm that the luminance of the
static central portion of the stimulus remained constant while the
luminance of flanking regions was modulated. After the receptive field
of a cell was determined, the size of the stimulus was manipulated so
that the central region was large enough to exceed the receptive field
borders by at least 3° on each side. In preliminary experiments, we
found that there was no significant effect of stimulus size on the
response, so long as the flanking regions of the stimulus remained well
outside the receptive field. Therefore, the largest stimulus size
(center region of stimulus = 14 × 14°) was often used to
assure that the luminance-modulated flanks were far outside the RF.
Stimulus size was not scaled to reflect RF sizes in the optic tract,
LGN, and V1, because we reasoned that any neural response associated
with perceived brightness must occur in stimulus conditions known to
yield perceptual brightness induction.
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Figure 1.
A, Luminance profile of the
induction stimulus. The stimulus was composed of three rectangular
regions of equal size. The luminance of the areas flanking the central
gray area was modulated (arrows) sinusoidally in time
(B), creating the perception that the brightness
of the static central area varied in antiphase to the flanks
(C). The static center region of the stimulus had
a luminance equal to the time-average luminance of the modulated
flanks.
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Within an experimental run, we presented several variations of the
basic induction stimulus (Fig. 2) to
assess the effects of the different components of the stimulus in
isolation. In addition, several temporal frequencies of the luminance
modulation were presented for each stimulus condition. The stimuli were
presented in random order, and each condition was repeated 15-30 times
within a given experimental run. The duration of the stimulus
presentation was 4 sec, and the interval between stimulus presentations
was 5 sec.
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Figure 2.
Spatial configurations of the stimuli. Stimuli
were presented so that the central area of the stimulus was centered
over the receptive field (shown as a gray oval). Stimuli consisted of
the following: (1) constant gray center with
luminance-modulated flanks (arrows) that resulted in the
perception of brightness changes in the region corresponding to the
receptive field and (2) black center with
luminance-modulated flanks. There was no perceived brightness
modulation in the central area containing the receptive field in this
condition. (3) Same as (1)
with the addition of drifting white (or black) bars over receptive
field. Brightness induction was perceived in the area surrounding the
bars. (4) Luminance modulation in center with
static gray flanks.
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Data collection and analysis. The activity of a neuron was
recorded as an event record of spike times relative to stimulus onset.
These event records were converted to a time series with a resolution
of 4 msec and displayed as peristimulus time histograms (PSTHs). To
assess the degree of modulation in the PSTH, the neural response was
multiplied by a sliding squarewave weighting function:
where s(t) = number of spikes in
the 4 msec time bin, beginning at (t),
w(t) = weighting function at (t),
and the summation is incremented in steps equal to the time bin width
(4 msec). The weighting function is defined as a function of the
initial squarewave phase  , which varies from 0 to 2 :
where f = squarewave frequency.
This procedure yields a function that represents the summed activity of
the neuron at incremental steps of phase in the luminance modulation of
the stimulus. This function was then smoothed by means of the
Savitzky-Golay filter (Press et al., 1988) with a space constant of 10 data points; each point corresponded to a 4 msec time bin. From the
smoothed function, the amplitude and phase of the cell's response were
determined at the luminance modulation frequency of the stimulus. This
process is illustrated schematically in Figure
3. To determine the statistical
significance of the response modulation, we performed simulations to
estimate the probability that the modulation occurred by chance. A
neuron was considered to have a significantly modulated response if the normalized measure of the response modulation satisfied the
p < 0.05 level of significance. We found that this
procedure gave more reasonable estimates of response modulation at the
driving frequency than a fast Fourier transform, because the responses were usually rectified.
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Figure 3.
Schematic illustration of the procedure used to
quantify the degree of modulation in the response histogram. On the
left of the figure is the response of a neuron to the
induction stimulus at a luminance modulation rate of 1 Hz. To assess
the degree of modulation in the PSTH, the neural response was
multiplied by a sliding squarewave weighting function having a period
equal to the inverse of the modulation rate. The gray
bands superimposed on the PSTH represent the weighting function
in which the activity within the gray zones was summed. A plot of
response modulation was constructed (top right) by
incrementally shifting the weighting function across 360° of initial
phase (left). The amplitude and phase of the response
modulation sinusoid was then used to define the modulation amplitude
and phase.
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Histology. At the end of each electrode penetration,
electrolytic lesions (5-10 µA, 5-10 sec) were made at selected
locations along the electrode track to aid in the identification of
recording sites. At the conclusion of each experiment, animals were
given an overdose of thiopental sodium and perfused through the heart initially with saline and then with a mixture of 10% formaldehyde in
0.1 M phosphate buffer, pH 7.4. The brain was removed and
kept for several days in a fixative solution with 30% sucrose. A
freezing microtome was used to cut the tissue at 50 µm increments in
the coronal plane. Sections were mounted and stained with cresyl
violet. For cortical reconstructions, the laminar position of recording sites along a penetration was determined by criteria based on the
relative size and density of cresyl-stained cell bodies (Garey, 1971).
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RESULTS |
Several configurations of the induction pattern composed the
stimulus set that was used to examine the responses of neurons in
striate cortex, LGN, and optic tract. The different stimulus configurations will be referred to by their numerical designation in
Figure 2. We recorded in the central visual representation of striate
cortex and the LGN, where receptive field size was typically between 1 and 5°. To assure that stimulus flanks were well outside the RF,
cells were not studied if the largest dimension of the receptive field
exceeded 8°. The stimuli were presented so that the flanking regions
were either to the left and right or above and below the RF. Receptive
field boundaries were routinely remapped after the automated
presentation of the stimulus set. All of the neurons described in this
study responded significantly to spots of light or oriented bars
presented within the RF.
Striate cortex
Effects of luminance modulation outside the RF
We reported previously that a significant percentage of neurons in
striate cortex respond to luminance modulation outside the RF (Rossi et
al., 1996). Here we will briefly review the key elements of the
cortical results and provide additional analysis and comparison with
recordings from the LGN and optic tract. Many cortical neurons were
found to respond only in stimulus conditions that produced perceptual
changes in brightness in the area corresponding to the receptive field.
An example of this is shown in Figure 4.
The third row of this figure shows the response of a neuron to the
presentation of a constant gray field flanked on either side by
luminance varying fields of equal size. The receptive field was 4°
wide and was centered on the central gray area that was 14° across.
The response of the neuron was phase-locked to the frequency of the
luminance modulation in the stimulus flanks. There was no such response
when the central portion of the stimulus was black (fourth row). This
is an important distinction because there is perceptual induction of
brightness changes in the stimulus with the gray center (third row) but
not in the stimulus with the black center (fourth row).
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Figure 4.
A neuron in striate cortex that responded to
luminance modulation outside the RF. Stimulus configurations are shown
on the left and the response of the neuron on the
right. The RF was 4° wide × 3.5° high,
and the static gray central portion of the stimulus was 14° wide × 14° high. At 0.5 and 1.0 Hz, the response was modulated in
sync with luminance changes in the flanks, although the flanks were
5° beyond the RF on each side (third row). When the
stimulus center was black, induction was perceptually lost along with
the neuronal response modulation (fourth row). There was
a clear shift in response phase in the induction condition
(third row) compared with the condition with luminance
modulation within the RF (second row).
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In some neurons, the effect of surround modulation could only be
brought out by adding a stimulus with contrast into the RF to raise
baseline activity. The stimulus configuration used to test this (Fig.
2, stimulus 3) was identical to the induction stimulus (Fig. 2,
stimulus 1) with the addition of bar stimuli that were drifted
continuously through the receptive field. The color (black or white),
orientation, speed, and direction of the bar stimuli were selected to
produce the best response when presented within the RF in isolation. To
human observers, the presence of the small drifting bars on the
constant gray center did not appreciably affect the brightness
modulation induced in the gray field surrounding the bars by the flanks
of the stimulus. Figure 5 is an example of a striate neuron in which the effect of stimulation outside the RF
was most apparent when the drifting bars were presented within the RF.
For this neuron, the modest response to the bar stimuli within the RF
(second row) was significantly augmented by the stimulation outside the
RF (fifth row). Moreover, this increase in the response of the neuron
was phase-locked to the rate of luminance modulation outside the RF.
This neuron did not exhibit a modulated response to the induction
stimulus when presented without the drifting bars (third row). In other
words, this cell appeared to convey information about brightness, but
only in concert with information about contrast within the receptive
field.
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Figure 5.
A neuron in striate cortex for which response
modulation was most apparent when the baseline firing rate was elevated
by drifting white bars of light through the RF (bottom
row). Stimulus configurations are shown on the
left with response of the neuron on the
right. The second row shows the response
of the neuron to drifting white bars on a static gray background. In
the bottom three rows, there are three histograms for
each stimulus condition corresponding to flank modulation at 0.5, 1.0, and 2.0 Hz. The bar stimuli were drifted through the receptive field at
6.6°/sec. Receptive field size = 4° wide × 3° high;
stimulus center = 14 × 10°.
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In our sample of striate neurons we did not find a systematic
relationship between classic receptive field properties (orientation selectivity, spatial tuning, simple vs complex) and the magnitude of
the response to the brightness induction stimuli. We also did not find
a significant effect of stimulus orientation (horizontal or vertical
arrangement of flanks). In general, the response to the induction
stimuli was less than the response to an optimal bar stimulus.
The effects of surround modulation were generally of two types: an
overall increase in firing rate and modulation at the driving frequency. Using the procedure outlined in Materials and Methods, we
quantified the degree to which responses showed general excitation or
inhibition and/or modulation at the frequency of the flank modulation.
Because low temporal frequencies (0.5-1.0 Hz) elicited the best
responses on average to the induction stimulus (stimulus 1), we chose
to examine the responses to 1 Hz luminance modulation. First, the total
number of spikes that occurred during the stimulus presentation was
taken as a measure of overall activity. To compare responses in
conditions that do and do not give perceptual induction, we calculated
an activity ratio as follows: activity ratio1,2 = total spikes (stimulus 1)/total spikes (stimulus 2).
Second, the amplitude of the modulation present in the response was
determined at the temporal frequency of the luminance modulation (see
Materials and Methods). The amplitude ratio of the neuron's response
was given by: amplitude ratio1,2 = amplitude (stimulus
1)/amplitude (stimulus 2).
The amplitude and activity ratios obtained for the population of 160 striate neurons is shown in Figure
6A. Although there is
considerable scatter in the population data, there is a tendency for
neurons to show both increased overall activity and increased response
modulation to effective stimuli.
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Figure 6.
Comparison of the activity and amplitude ratios
for the neurons recorded in striate cortex (A),
the LGN (B), and the optic tract
(C). Neurons with ratios >1 in either dimension
indicate a larger response in the induction condition (stimulus 1) than
the center-black condition (stimulus 2). For all neurons shown, the
temporal frequency of the luminance modulation was 1.0 Hz.
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The population was then examined with regard to how specific a
neuron's response was to stimulus conditions that produce brightness induction in human observers (stimuli 1 and 3). Several criteria were
adopted to make this determination. First, only neurons that exhibited
a statistically significant amplitude of response variation (p < 0.05), with luminance modulation outside
the RF, were included (see Materials and Methods). In our sample of 160 striate neurons, 120 (75%) satisfied this criterion. Second,
comparisons of the responses to stimulus 1 (or stimulus 3) and stimulus
2 were made to establish whether the neuron's modulated response to
stimulus 1 or 3 was lost when the central area was black, thus
eliminating the perceptual induction (stimulus 2). The distribution of
the amplitude ratio1(3),2 for 120 striate neurons is shown
in Figure 7A.
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Figure 7.
A, Distribution of the amplitude
ratio1(3),2 for 120 striate neurons. Ratios >1 indicate
that the amplitude of the response modulation was greater for induction
(stimulus 1 or stimulus 3) than for the center-black control (stimulus
2). B, Distribution of the amplitude
ratio1(3),4 for 42 striate neurons in which the amplitude
ratio1(3),2 was >2. Ratios >1 indicate that the amplitude
of the response modulation was greater for induction (stimulus 1 or
stimulus 3) than for luminance modulation within the RF (stimulus 4).
Both amplitude ratios were determined for responses to 1 Hz
stimuli.
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This figure shows that a significant fraction of the population had
ratios >1, indicating that the amplitude of the response modulation to
stimulation outside the RF was greater for those stimuli that produced
brightness induction within the RF. We chose the conservative criterion
that neurons were considered for further analysis only if the
modulation amplitude in response to stimulus 1 or stimulus 3 was more
than twice that of the response to stimulus 2. Forty-nine neurons had
amplitude ratios1(3),2 that met this criterion. The 49 neurons (30% of total population) that satisfied this criterion
appeared to reliably respond in a manner correlated with the perceptual
induction of brightness. Because the response was significantly less in
the center-black condition (stimulus 2), it is unlikely that the
brightness-correlated responses resulted from scattering of light in
the eye (see Discussion). A breakdown of how this subpopulation of
neurons responded to stimuli 1 and 3 is shown in Table
1.
Effects of luminance modulation within the RF
In the majority of the neurons tested, the response to luminance
modulation within the RF was compared with the aforementioned effects
of luminance modulation outside the RF. Surprisingly, it was not
uncommon that striate neurons responded robustly to a uniform field of
varying luminance that overlapped the RF by several degrees (stimulus
4), despite the lack of contours within the RF. For those neurons that
exhibited amplitude ratios1(3),2 >2, we wished to compare
the response to the induction stimulus (stimulus 1 or 3) with that
elicited by direct luminance modulation within the RF (stimulus 4). To
describe this relationship, the amplitude ratio1(3),4 was
calculated: amplitude ratio1(3),4 = amplitude
(stimulus 1 or stimulus 3)/amplitude (stimulus 4).
Figure 7B shows the distribution of the amplitude
ratio1(3),4 for 42 striate neurons that met the criterion
for amplitude ratio1(3),2 and were also fully studied with
luminance modulation within the RF. It can be seen that the majority of
these neurons had amplitude ratios >1, indicating that the degree of
modulation in response to the 1.0 Hz induction stimulus was often
equivalent to or greater than that produced by luminance modulation
within the RF at the same rate. Neurons that exhibited a significantly modulated response to luminance change within the RF
(ratio1(3),4 > 0.5) and also satisfied the amplitude
ratio1(3),2 criterion are examined in greater detail in the
following sections.
Effects of temporal frequency on response phase
One characteristic of the dynamic induction stimulus we used is
that the induced brightness changes in the center of the stimulus occur
in antiphase to the luminance modulation in the flanks. In many neurons
there is a similar phase difference in the response to the induction
stimulus (stimulus 1 or 3) relative to luminance modulation within the
RF (stimulus 4). Examples of these phase differences can be seen in the
responses of neurons in Figures 4 and 9A. In both these
examples, there was an approximate phase difference of 180° in the
response to the induction stimulus (third row) relative to the response
to direct changes in luminance within the RF (second row). As in the
examples in the previous section, the response to luminance modulation
outside the RF was greatly diminished when the gray center of the
stimulus was removed (fourth row). The magnitude of the observed phase
differences varied among neurons in our sample and is summarized in
Figure 8. It can be seen in this figure
that the greatest number of neurons exhibited either no phase
difference or a phase difference near 180°. Because lower temporal
frequencies (0.5-1.0 Hz) elicited the optimal response on average (see
the following section), we chose to examine the population phase
relationship of neurons at 1.0 Hz.
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Figure 8.
Distribution of phase differences in the response
to induced (stimulus 1) versus direct (stimulus 4) brightness changes
within the RF. The luminance modulation rate was 1.0 Hz.
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It was often the case that the observed phase differences were most
pronounced at low temporal frequencies of the luminance modulation. It
can be seen in Figure 9A that
as the temporal frequency of the luminance modulation was increased
above 1 Hz, there was a noticeable decrease in the phase difference
between the induction and center-modulation responses. This shift in
the phase of the response at higher temporal frequencies was observed
only in neurons that had marked phase differences (>100°) at lower
temporal frequencies.
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Figure 9.
A, Temporal frequency of luminance
modulation affects the response to induction and control stimuli
differently. Responses to luminance modulation rates of 0.5, 1, 2, and
4 Hz are shown. B, The amplitude of response modulation
plotted as a function of temporal frequency for the striate neuron
shown in A. Gray bars represent the
response to the induction stimulus (stimulus 1), and black
bars represent the response to luminance modulation covering
the RF (stimulus 4). The modulation amplitude is expressed as the
percentage of the maximum response elicited by stimulus 4. C, Averaged normalized modulation amplitudes for 24 striate neurons plotted as a function of the rate of luminance
modulation. The modulation amplitude is expressed as the percentage of
the maximum response amplitude elicited by either stimulus for each
neuron. In nearly all neurons, the maximum response was elicited by
stimulus 4. Gray bars represent the response to stimulus
1, and black bars represent the response to stimulus 4. Error bars are equal to 1 SEM.
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Effects of temporal frequency on the response to
luminance modulation
Psychophysical experiments (DeValois et al., 1986; Rossi and
Paradiso, 1996) have shown that brightness induction occurs only when
the luminance of the inducing stimuli is modulated at low rates (<3
Hz). Therefore, for those neurons that responded to both the induction
stimulus and luminance modulation within the RF, we compared the
responses at different rates of luminance modulation. Figure
9A is an example of a neuron that was tested at temporal
frequencies of 0.5, 1.0, 2.0, and 4.0 Hz. It can be seen in this
example that there was a reduction in the modulation amplitude to the
induction stimulus with increases in temporal frequency above 1.0 Hz
(third row). Conversely, this neuron exhibited an increase in response
modulation to luminance changes within the RF as the temporal frequency
was increased (second row). The difference in the modulation amplitude
for this striate neuron is quantified in Figure 9B, where
the amplitude of the response modulation for these two conditions is
plotted as a function of the temporal frequency. Figure 9C
shows the relationship between response amplitude and luminance
modulation rate for the group of neurons that were stimulated at all
four temporal frequencies (n = 24). It can be seen in
this figure that the degree of response modulation is comparable in the
induction and "real" modulation conditions at 0.5 and 1.0 Hz. At
temporal frequencies above 1.0 Hz, there was a steady decline in the
modulation amplitude to luminance changes outside the RF (gray bars),
whereas there was an increase in the modulation amplitude to luminance
changes within the RF (black bars). This difference in the responses at
higher temporal frequencies is striking because it correlates with
perceived variations in brightness. At low temporal frequencies,
brightness changes are perceived with both induced and "real"
modulation, but at higher temporal frequencies, brightness variations
are seen with the "real" modulation but are lost with induction.
Laminar distribution
Histological reconstructions were made of the electrode
penetrations in six of the animals that were studied. Neurons that exhibited responses that were correlated with brightness changes were
located in equal proportions in all laminae of striate cortex. Table
2 shows the laminar distribution of 27 striate neurons that had responses significantly more modulated by the
induction stimulus than the center-black control stimulus (i.e.,
amplitude ratio1,2 > 2).
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Table 2.
Laminar distribution of 27 neurons that had responses
significantly more modulated by the induction stimulus than the
center-black control stimulus
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Lateral geniculate nucleus
In the previous section, we showed the effects of luminance
modulation outside the RF on the response of cortical neurons. We found
neurons in all cortical layers that responded to stimulation outside
the RF in a manner correlated with perceptual changes in brightness. We
wished to determine whether the brightness-correlated responses first
occur in cortex or whether they are present at earlier stages of visual
processing. Following the same procedure that was used in the study of
cortical neurons, we examined the responses of 75 neurons in lamina A
and A1 of the lateral geniculate nucleus.
Effects of luminance modulation outside the RF
The responses of the geniculate neurons that we studied did not
correlate with perceived brightness as well as the responses in striate
cortex. In total, 42 of the 75 (56%) geniculate neurons in our sample
had responses that were significantly modulated (p < 0.05) and phase-locked to the luminance
changes outside the RF. Figure
10A shows a
geniculate neuron with a response that followed the modulation of light
covering the RF (second row). The neuron was also excited by the
induction stimulus with luminance modulation outside the RF (third
row). However, the response to the induction stimulus was not
significantly modulated.
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Figure 10.
Responses of two geniculate neurons with
on-center/off-surround receptive fields. A, A neuron
that exhibited an elevated response in the induction condition, but
little or no response modulation (third row). There was
response modulation to luminance changes within the RF (second
row). This cell's response did not correlate with perceived
brightness. B, A neuron that exhibited a modulated
response in the induction condition (third row) but no
response in the center-black condition (fourth
row). Note that there is a difference in the phase of the
response to luminance modulation within (second row) and
outside (third row) the RF. Although rare in the LGN,
this response pattern was correlated with brightness.
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To establish the degree to which the response of a geniculate neuron
was specific to stimulus conditions that produced brightness induction,
comparisons were made of the response to the induction stimulus
(stimulus 1) and the black-center control (stimulus 2). Ratios of the
overall activity and amplitude of modulation were calculated for each
neuron as described previously for cortical neurons. A comparison of
the amplitude and activity ratios for the population of neurons is
shown in Figure 6B. The distribution of points in
this figure indicates that most neurons had response amplitudes that
were greater for stimulus 2 than for stimulus 1 (i.e., ratio < 1). Although approximately half of the neurons in our sample exhibited
a greater overall response to stimulus 1 (activity
ratio1,2 > 1), the modulation amplitude in response to stimulus 2 was usually greater (amplitude ratio1,2 < 1). This suggests that very few cells were modulated by the
induction stimulus to a degree that exceeded that which might result
from light scattering. Figure 11 shows
the distribution of the amplitude ratio1(3),2 for 42 LGN
neurons compared with the distribution for cortical neurons.
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Figure 11.
Distribution of the amplitude
ratio1(3),2 for neurons recorded in the LGN
(n = 42) compared with striate cortex
(n = 120). Note that the distribution of neurons
for each group is represented as a percentage of the total number of
neurons in that group. Ratios >1 indicate that the amplitude of
response modulation was greater in the induction condition (stimulus 1)
than in the center-black condition (stimulus 2). The amplitude ratios
were determined for responses to 1 Hz stimuli. A larger percentage of
neurons in striate cortex had ratios >1, indicating that cortical
responses were more often correlated with perceived brightness in the
induction condition.
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It can be seen in Figures 6B and 11 that a small
fraction of our geniculate neurons had significantly greater response
modulation to stimulus 1 (or stimulus 3) than to stimulus 2. As with
the similar cortical neurons, the responses appeared to correlate with
perceived brightness. Figure 10B shows an example of
a geniculate neuron with an on-center/off-surround receptive field
configuration that had a phase-locked response to luminance modulation
outside the RF only when the center region of the stimulus was gray.
Like many striate neurons, this LGN neuron showed a phase-locked
response to luminance modulation within the RF (second row). It is
important to note that the light modulation occurred outside the RF,
not in the off-surround. Additionally, the phase of the response to stimulus 1 (third row) was in approximate antiphase to the response to
luminance modulation within the RF. However, this antiphase response
pattern was far less common in the LGN (2 of 75 neurons) than in cortex
(Fig. 8).
Effects of temporal frequency on response amplitude
Approximately 10% of the geniculate neurons were significantly
more modulated in the induction condition than in the center-black control condition. We have shown in Figure 9C that the
amplitude of the striate response to the induction stimulus decreased
as the temporal frequency of the luminance modulation was raised above
1.0 Hz. Figure 12 shows the same
relationship between the response amplitude and the rate of luminance
modulation for seven geniculate neurons stimulated at all four temporal
frequencies. Similar to the response of striate neurons, the modulation
amplitude of geniculate responses to luminance changes within the RF
increased over the range of temporal frequencies tested. However,
unlike our sample of striate neurons, the average modulation amplitude to luminance changes outside the RF did not decrease as the temporal frequency was raised.
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Figure 12.
Average amplitude of response modulation plotted
as a function of temporal frequency for seven LGN neurons. Gray
bars represent the response to the induction stimulus (stimulus
1), and black bars represent the response to luminance
modulation covering the RF (stimulus 4). With both stimuli, the
modulation amplitude tended to increase with temporal frequency,
although not significantly for the induction condition. The modulation
amplitude is expressed as the percentage of the maximum response
amplitude elicited by either stimulus for each neuron. Error bars are
equal to 1 SEM.
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Optic tract
With the same experimental procedure and analysis that were used
in the study of cortical and geniculate neurons, we examined the
responses of 33 retinal ganglion cells recorded in the optic tract.
Similar to the responses of geniculate neurons, some retinal ganglion
cells did respond in a phase-locked manner to luminance modulation
within the RF, but most cells in the optic tract did not show modulated
responses when the light level outside the receptive field was varied.
Figure 13 shows the responses of an X-type ganglion cell to the basic stimulus set. It can be seen in the
third row of this figure that there was a maintained elevation in the
response of the cell to stimulus 1, but the effect of the luminance
change outside the RF is not apparent in the response. The elevated
response might have been caused by the presence of the static gray
center in stimulus 1, because the response was greatly diminished when
the region corresponding to the RF was black (fourth row).
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Figure 13.
Response of an X-type retinal ganglion cell
recorded in the optic tract. In the induction condition (third
row) the cell's response was elevated above the spontaneous
firing rate (first row), but the response was not
modulated. The response was modulated by luminance changes within the
RF (second row).
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The relationship between the overall activity and modulation amplitude
of the response to stimulus 1 and stimulus 2 is shown in Figure
6C. It can be seen in this figure that most of the retinal ganglion cells studied had a greater modulation amplitude in response to stimulus 2, yet exhibited a greater overall response to stimulus 1. It is important to note that none of the 33 cells that were tested
exhibited a significant degree of modulation in their response to
luminance modulation outside the RF based on our minimum criterion (p < 0.05). Therefore, the measure of amplitude
ratio1,2 for this population may not be meaningful because
the degree of modulation observed in the responses of retinal ganglion
cells was quite small.
| |
DISCUSSION |
At present, little is known about the neural representation of
surfaces in general and brightness in particular. We examined neurons
with a dynamic brightness induction stimulus because it allowed us to
dissociate responses correlated with brightness from those correlated
with actual light level. We found that some neurons in the optic tract,
LGN, and striate cortex are affected by light outside the RF, often at
distances up to 5-10°. This is comparable in scale to perceptual
interactions involving brightness induction and constancy in humans
(Land, 1959; Heinemann, 1972). We found significant differences in the
responses of neurons in the three brain areas studied, suggesting that
a brightness representation is developed at later stages of visual
processing from the early contrast-based response.
Correlation of neural activity with perceived brightness
In the stimuli we used, the brightness of the area covering the RF
was changed either by varying its luminance or by inducing a perceptual
change by luminance modulation of the surround. Within the confines of
the parameters we varied, a neural response correlated with brightness
might be expected to have the following properties. (1) When the
luminance of the area covering the RF is varied, the response should
follow; (2) when the area covering the RF is static black, the response
should not change despite modulation of the surround, because there is
no perceptual change in the black area; (3) when the area covering the
RF is static gray and the luminance of the surrounding area is
modulated, the response should follow the induced changes in
brightness; (4) in the center-gray induction condition, the response
should phase shift 180° relative to the control condition in which
the center luminance is varied, because that is what is perceived; and
(5) response modulation in the induction condition should decline as
the temporal frequency of the inducing surround increases above ~2.5
Hz, whereas response modulation to luminance changes in the RF should
not decline. These temporal properties would correlate with the low
cutoff rate for induction (DeValois et al., 1986; Rossi and Paradiso, 1996) relative to the critical flicker fusion rate, which is roughly 10 times higher.
Each of the criteria above is open to question. Which assumptions are
legitimate significantly impacts the assessment of whether activity in
different visual structures is related to brightness. At one extreme is
the retina, in which we found no cells that exhibited properties
(3)-(5). In all cases, it appeared that responses were based on light
level within the receptive field, with the occasional exception of an
overall excitatory effect of surround illumination. Striate cortex is
at the other extreme. Even with the strict criteria that we used (e.g.,
that response modulation to the induction stimulus must have at least
twice the amplitude of the response in the center-black
condition), 16 of our total population of 160 striate neurons were
found that had all of the properties listed above. Although 16 neurons
is not a large population, 10% of all neurons in striate cortex
represents an impressive number of neurons that potentially carry
information correlated with perceived brightness. Fittingly, the LGN
was found to be intermediate in the degree to which the neurons had the
properties above. Although no neurons were found that had all five
properties, a handful did have the first four. It is possible that we
have underestimated the number of neurons involved in representing brightness information, by insisting that a neuron possess all five
properties listed above. For example, if a neuron in striate cortex
showed appropriate response changes with temporal frequency, it might
be involved in a brightness representation even if it did not show a
180° phase shift.
Do cells in the retina, LGN, and striate cortex represent brightness
information in their firing rate? The lack of correlation between
brightness and activity in the optic tract suggests that the answer is
"no" for the retinal output. On the other hand, in striate cortex,
there appears to be a sizeable population of cells that carries
brightness information. Because these cells were selective for multiple
visual attributes, it appears that brightness information is
multiplexed with information about orientation, spatial frequency, and
other stimulus properties. Both simple and complex cells spread across
the cortical lamina were found to have brightness-correlated responses.
There is always the possibility that additional tests might prove that
the cortical responses do not entirely correlate with brightness.
However, the correlations that we did observe showed intriguing
subtleties, particularly the changes in response amplitude with
"real" and induced brightness modulation as temporal frequency was
increased above 1 Hz. As seen perceptually, induced modulation affected
the neural response primarily at low temporal rates, whereas real
luminance modulation evoked phase-locked responses at high rates.
It is more difficult to classify the LGN. Valberg et al. (1985)
observed that steady surround illumination outside the receptive field
can alter the sensitivity of geniculate neurons to receptive field
stimulation in a manner suggestive of simultaneous contrast. DeValois
and Pease (1971) did not observe induction in LGN neurons in the
primate, but they used a static version of induction that might not
have been as powerful a stimulus as ours. The dynamic induction
stimulus that we used elicited responses that partially correlated with
perceived induction in some cells. However, no LGN cells completely fit
the profile of "brightness neurons" by possessing all of the
properties listed above. Therefore, to summarize our findings, striate
cortex is the first component of the visual system that has responses
reliably correlated with brightness. It appears that important
computations take place at this level that make some cells respond in a
manner better correlated with perceived brightness than with actual
light level.
Possible concerns and artifacts
Conceivably, the interactions that we have reported as coming from
beyond the receptive field might be caused by interactions within the
receptive field. There are two ways this might happen. The first is by
underestimating the size of the RF, thus having the surround stimuli
actually within the RF. Although we used the most common technique of
plotting receptive fields, there is no question that small differences
in RF size result from different techniques. Nonetheless, it is quite
unlikely that this was an important factor because the flanking regions
of our stimuli were positioned at least 3° (and up to ~5 or 6°)
beyond the conservatively estimated borders of the receptive fields. A
second way in which RF stimulation might yield the results we obtained
would be by light scattered within the eye. However, a number of
observations suggest that scattered light did not cause the surround
interactions we observed. First, the neuronal response to stimulation
outside the RF was unaffected by the use of artificial pupils.
Restriction of the angle of incident light would result in a reduced
response if stray light from regions of the stimulus outside the RF
illuminated areas of the retina corresponding to the RF. Second,
increasing the ambient room illumination to alter the adaptation state
of the retina did not reduce the effectiveness of the induction
stimuli. Such a reduction would be expected if light scattered into the receptive field produced suprathreshold effects at low ambient illumination. Finally, we examined whether the responses in the center-black and center-gray conditions were consistent with light scatter. The effects of stray light on the response of a cell should be
greater when the center of the stimulus is black than when the center
is gray, because the photoreceptor gain would be higher in the former
case. For this reason, we only considered neurons with greater
responses in the center-gray condition. We took the conservative stance
that a cell showing a greater response in the center-black condition
might carry artifacts resulting from scattered light.
Another concern is that we have compared the physiological data from
cats with psychophysical data from humans. Although there are no
behavioral data showing that cats perceive the brightness effects that
we have described, there is considerable similarity in the visual
systems of cats and humans up to the level of striate cortex (Sherman
and Spear, 1982), and cats have been shown to see brightness effects
associated with the perception of illusory figures (Bravo et al.,
1988).
Contextual responses and surface perception
Several lines of evidence suggest that a general representation of
surfaces first occurs in striate cortex and that this involves interactions from beyond the small receptive fields. Brightness appears
to be first explicitly represented in striate cortex (Reid and Shapley,
1989; Rossi et al., 1996), and spatial interactions observed in this
area are consistent with long-range brightness effects (Komatsu et al.,
1996; MacEvoy et al., 1998). Striate cortex also appears to represent
information about texture (Nothdurft and Li, 1985; Knierim and Van
Essen, 1992; Kastner et al., 1997) and figure-ground segregation
(Lamme, 1995; Zipser et al., 1996; Lee et al., 1998). Thus, aside from
color, which appears to be handled more by extrastriate cortex (Zeki,
1980; Schein and Desimone, 1990), responses in striate cortex have been
found that correlate with most attributes of surfaces. In general, it
is not known whether these responses result from interactions within
striate cortex or via feedback, but there is evidence that
figure/ground segregation involves extrastriate feedback to V1 (Hupe et
al., 1998; Lamme et al., 1998). Regardless of the mechanism, the first visual cortical area appears to be involved in far more than the detection of oriented contours, and its output conveys information that, in some ways, correlates with visual perception.
| |
FOOTNOTES |
Received Dec. 28, 1998; revised April 28, 1999; accepted May 3, 1999.
This research was supported by grants from the National Eye Institute
and the Whitehall Foundation. Special thanks to Cindi Rittenhouse for
help with the data acquisition and Smita Nayak and Woojin Kim for their
assistance with the histology.
Correspondence should be addressed to Dr. Michael Paradiso, Department
of Neuroscience, Brown University, P.O. Box 1953, Providence, RI 02912.
Dr. Rossi's present address: Laboratory of Brain and Cognition,
National Institute of Mental Health, National Institutes of Health,
Bethesda, MD 20892.
| |
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Responses of Spectrally Selective Cells in Macaque Area V2 to Wavelengths and Colors
J Neurophysiol,
April 1, 2002;
87(4):
2104 - 2112.
[Abstract]
[Full Text]
[PDF]
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M. Kinoshita and H. Komatsu
Neural Representation of the Luminance and Brightness of a Uniform Surface in the Macaque Primary Visual Cortex
J Neurophysiol,
November 1, 2001;
86(5):
2559 - 2570.
[Abstract]
[Full Text]
[PDF]
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S. Shimojo, M. Paradiso, and I. Fujita
What visual perception tells us about mind and brain
PNAS,
October 12, 2001;
(2001)
221383698.
[Abstract]
[Full Text]
[PDF]
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S. P. MacEvoy and M. A. Paradiso
Lightness constancy in primary visual cortex
PNAS,
July 5, 2001;
(2001)
161280398.
[Abstract]
[Full Text]
[PDF]
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K. Moutoussis and S. Zeki
A psychophysical dissection of the brain sites involved in color-generating comparisons
PNAS,
June 14, 2000;
(2000)
110570897.
[Abstract]
[Full Text]
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K. Moutoussis and S. Zeki
A psychophysical dissection of the brain sites involved in color-generating comparisons
PNAS,
July 5, 2000;
97(14):
8069 - 8074.
[Abstract]
[Full Text]
[PDF]
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S. P. MacEvoy and M. A. Paradiso
Lightness constancy in primary visual cortex
PNAS,
July 17, 2001;
98(15):
8827 - 8831.
[Abstract]
[Full Text]
[PDF]
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S. Shimojo, M. Paradiso, and I. Fujita
What visual perception tells us about mind and brain
PNAS,
October 23, 2001;
98(22):
12340 - 12341.
[Abstract]
[Full Text]
[PDF]
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TOP
ABSTRACT
INTRODUCTION
