| Volume 2, Number 3, Article 4, Pages 243-255 |
doi:10.1167/2.3.4 |
http://journalofvision.org/2/3/4/ |
ISSN 1534-7362 |
Facilitation of contrast detection by cross-oriented surround stimuli and its psychophysical mechanisms
Cong Yu |
School of Optometry, University of California, Berkeley, CA, USA |
|
Stanley A. Klein |
School of Optometry, University of California, Berkeley, CA, USA |
|
Dennis M. Levi |
School of Optometry, University of California, Berkeley, CA, USA |
|
Abstract
Neurophysiological and psychophysical evidence indicates that neuronal surround modulation at cross-orientation (orthogonal to the preferred orientation of the classical receptive field) plays a key role in intermediate-level visual tasks, such as textural segregation and perceptual pop-out. What is missing is a psychophysical description of cross surround modulation at the spatial filter level in low-level vision. Moreover, neurophysiological evidence for how cross surround modulation is expressed at the neuronal level has been inconsistent. Here we report evidence for psychophysical facilitation of contrast detection by cross surround stimuli (orthogonal to the target orientation) that may provide insights into both the neurophysiology and psychophysics of cross surround modulation. We found that cross surround facilitation is a surround-contrast dependent effect mainly evident at low surround contrasts, and is narrowly tuned to spatial frequency and broadly tuned to orientation. To understand whether cross surround facilitation results from low-level processing of signal-to-noise enhancement or is due to uncertainty reduction at a higher-level decision stage, we (1) studied cross surround facilitation with an equivalent noise protocol, (2) estimated the changes in the slope of the psychometric function and the uncertainty parameter, M, and (3) measured cross surround effects at the dipper of the TvC function. The converging evidence suggests that cross surround facilitation of contrast detection is mainly a result of low-level signal-to-noise enhancement, and is little affected by uncertainty change.
 |
|
History
Received November 20, 2001; published May 28, 2002
Citation
Yu, C., Klein, S. A., & Levi, D. M. (2002). Facilitation of contrast detection by cross-oriented surround stimuli and its psychophysical mechanisms.
Journal of Vision, 2(3):4, 243-255,
http://journalofvision.org/2/3/4/,
doi:10.1167/2.3.4.
Keywords
surround modulation, cross orientation, contrast detection, classical receptive field, uncertainty
for related articles by these authors
for papers that cite this paper |
Many researchers suggest that cross surround modulation
of response properties of the classical receptive fields in the primary visual
cortex plays a fundamental role in intermediate-level visual tasks, such as
textural segregation and perceptual pop-out
( Knierim & Van Essen, 1992;
Sillito, Grieve, Jones, Cudeiro, & Davis, 1995;
Levitt & Lund, 1997;
Sengpiel, Sen, & Blakemore, 1997;
Das & Gilbert, 1999;
Nothdurft, Gallant, & Van Essen, 1999;
Walker, Ohzawa, & Freeman, 1999;
Hupé, James, Girard, & Bullier,, 2001).
Psychophysical studies indeed link perceptual pop-out to excitatory connections
between orthogonal spatial filters mimicking V1 simple neurons
( Wolfson & Landy, 1999). However,
there have been contradictory reports on how neuronal responses are influenced
by cross surround stimuli (orthogonal to the preferred orientation) placed
outside the classical receptive fields. Some studies reported cross surround
facilitation in a significant portion of V1 neurons
( Sillito et al., 1995;
Levitt & Lund, 1997;
Nothdurft et al., 1999;
Hupé et al., 2001), while others
reported mostly cross surround suppression
( Knierim & Van Essen, 1992;
Sengpiel et al., 1997;
Das & Gilbert, 1999;
Walker et al., 1999). Psychophysical
investigation of surround modulation of low-level visual tasks such as contrast
detection using comparable stimuli would be expected to provide some insights
into the inconsistent neurophysiological data. These investigations could also
reveal detailed properties of interactions between orthogonal psychophysical
spatial filters and build the links between neurophysiology and higher-level
vision. However, in an influential paper
( Polat & Sagi, 1993), contrast
detection for a Gabor (Gaussian windowed sinusoidal grating) target was reported
unaffected by laterally placed Gabor flankers orthogonal to the target
orientation, though significant facilitation was evident when the same flankers
were collinear with the target. Lack of cross surround effects on contrast
detection at the visual psychophysical level has been cited by other researchers
( Chen & Tyler, 2001), but is
inconsistent with neurophysiological data, and if true would in some measure
cast doubt on the meaningfulness of cross surround effects at the neuronal
level.
Recently we reported significant cross surround
modulation of suprathreshold contrast discrimination
( Yu & Levi, 2000) and perceived contrast
( Yu, Klein. & Levi, 2001). We found that
contrast discrimination is generally facilitated by cross surround stimuli. At
high surround contrasts, masking can be completely eliminated by the cross
surrounds. Cross surrounds also enhance the perceived contrast of the center
stimuli, particularly when the surround has high contrast. These findings
prompted us to reconsider the previous experimental evidence for cross surround
modulation of contrast detection.
In the first half of the work, which includes
Experiments I, II, and III, we describe cross surround modulation of contrast
detection and its spatial properties. In these experiments, we measured cross
surround modulation with a wide range of surround contrast conditions and
demonstrated significant cross surround facilitation at low surround contrasts.
We also studied the spatial frequency and orientation tuning properties of cross
surround facilitation, as well as the roles of end and side portions of the
surround stimuli. The second half of this work (Experiments IV) deals with the
psychophysical mechanisms of cross surround facilitation: specifically, whether
cross surround facilitation is a result of low-level signal-to-noise
enhancement, or is due to uncertainty reduction at a higher-level decision
stage. We conducted three experiments: cross surround facilitation with the
target in noise (IVa), estimation of uncertainty from the slope of the
psychometric function (IVb), and cross surround facilitation at the dipper of
the TvC function (IVc). Our data indicate a major contribution of low-level
visual mechanisms to cross surround facilitation and little evidence for
uncertainty reduction. The findings of this study may help clarify some
controversies surrounding the issue of neurophysiological cross surround
modulation and link relevant neurophysiology to psychophysics and higher-level
visual
tasks.
Adult human observers with normal or
corrected-to-normal vision served in this study. Some earlier experiments were
carried out at the University of Houston and the later ones at the University of
California, Berkeley, so we were not able to use the same observers throughout
the study. All observers except S.T. and Y.C. were new to psychophysical
observations and received training prior to data collection. Only Y.C. was aware
of the purpose of the experiments.
The stimuli were generated by a VisionWorks computer
graphics system (Vision Research Graphics, Inc., Duham, NH) and presented on a
U.S. Pixel Px19 monochrome monitor (U.S. Pixel Corporation, Framingham, MA). The
monitor had a 1024 x 512
resolution, 117 Hz frame rate, 50
cd/m2 mean luminance, and
3.8o
x
3.0o usable screen size at the
viewing distance of 5.64 meters. The luminance of the monitor was made linear by
a 15-bit look-up table.
In most cases, the target
( Figure 1a) was a spatially localized D6
grating (a sixth derivative of a Gaussian) blurred along its long axis by a
Gaussian window (σ= 4.8 arcmin) and truncated at the target length (10
arcmin). The surround was a sinusoidal grating annulus at cross-orientation. The
inner and outer diameters of the surround annulus were 18 and 45 arcmin,
respectively. The peak spatial frequency of the target and the spatial frequency
of the surround stimuli were the same at 8 cycles per degree (cpd). Some
variations of the cross surrounds were also used, which will be detailed in
related experiments. In one occasion, we also used Gabor stimuli
( Figure 1b) to replicate experiments
conducted previously
( Polat & Sagi, 1993). Here the target
was a vertical Gabor grating flanked on the top and bottom by two orthogonal
Gabor gratings. These Gabor gratings had the same spatial frequency (8 cpd) and
circular Gaussian window (σ = 4.8 arcmin). The Gabor flankers were
separated from the central Gabor target by a center-to-center distance of 3
λ (λ= 7.5 arcmin).
For most experiments, contrast thresholds were measured
with a successive 2-alternative forced-choice (2AFC) staircase procedure. The
cross surround or Gabor flankers were presented in each of the two stimulus
intervals (400 msec each) separated by a 400 msec inter-stimulus interval. Each
stimulus interval was accompanied with an audio tone of the same duration. The
target was randomly presented in one of the two stimulus intervals with the same
onset and offset as the surround stimuli. The observers' task was to judge which
stimulus interval contained the target. Each trial was preceded by a 6.3'
x 6.3' fixation cross which
disappeared 100 msec before the beginning of the trial. Audio feedback was given
on incorrect responses. Each staircase consisted of four preliminary reversals
and eight experimental reversals. The step size of the staircase was 0.05 log
units. A classical 3-down-1-up staircase rule was followed, which resulted in a
79.4% convergence level of the staircase. The mean of the eight experimental
reversals was taken as the contrast threshold. Each datum represents the mean of
4 to 6 replications, and the error bars represent ±1 standard error of the
mean.
In one measurement of Experiment IV, a rating scale
method with constant stimuli
( Levi, Klein, & Aitsebaomo, 1984) was
used to obtain the psychometric function. In each block of 125 trials, the
target stimulus was presented at five near threshold contrasts, including one at
0 contrast (e.g., 0, 0.01, 0.02, 0.03, and 0.04). The observer responded with
numbers from 0 to 4 to indicate which contrast the target belonged to (0
referred to the zero contrast target, and 4 referred to the highest target
contrast). Feedback on the correct target contrast was given after each
response. One observer (J.E.) completed 19 blocks of trials, 11 blocks with two
sets of target contrasts for no surround and cross surround conditions and 8
blocks with another two sets of target contrasts. The other observer (M.L.)
completed 11 blocks with the same two sets of target contrasts. Further details
of the experiments and data analysis will be provided in Experiment IV.
A brief report of our data was presented at the Vision
Science Society conference in Sarasota, Florida, in May
2001).
Experiment I. Cross Surround Modulation of Contrast Detection and the Effects of Surround Contrast
We first measured detection thresholds for the D6
target ( Figure 1a) under the influence of
the annular cross surround at various contrasts ranging from 0.025 to 0.80.
Contrast thresholds for the D6 target only (with no surround) were also measured
as baselines. In contrast to previous reports, our data
( Figure 1a) show significant facilitation of
contrast detection by cross surrounds. However, unlike iso (collinear) surround
facilitation of contrast detection, which reportedly is unaffected by surround
contrast ( Polat & Sagi, 1993), cross
surround facilitation is a surround-contrast dependent effect. At lower surround
contrasts (0.05 and 0.10), the cross surrounds reduce contrast detection
thresholds by as much as 40%. However, at higher surround contrasts (0.40 and
0.80), the cross surrounds have very little or no effect on contrast detection.
The surround at the lowest contrast (0.025) also has little effect on contrast
detection, which may represent a threshold for cross surround
facilitation.
This contrast dependency of cross surround modulation
of contrast detection points to some potential limitations in previous
psychophysical (and probably neurophysiological) studies that used surrounds of
fixed high contrasts. To address this concern, we replicated the earlier
psychophysical experiment
( Polat & Sagi, 1993) that used Gabor
stimuli ( Figure 1b) and found ineffective
orthogonal flankers in contrast detection, except that we used a range of
flanker contrasts instead of a fixed one. Our data
( Figure 1b) do show consistent and
significant facilitation at lower flanker contrasts (0.10 and 0.20) with an
average 33% reduction of the contrast threshold, but little effect at 0.40, the
flanker contrast used previously
( Polat & Sagi, 1993).
Figure 1. Cross
surround modulation of contrast detection. a. The stimulus image shows a D6
center target surrounded by an annular sinusoidal grating at cross orientation.
The mean and individual data show cross surround effects on contrast thresholds
as a function of the surround contrast. A lower-than-baseline contrast threshold
indicates cross surround facilitation. b. The stimulus image shows a Gabor
target and two identical Gabor flankers at cross orientation. The mean and
individual data show flanker effects on Gabor detection as a function of the
flanker contrast.
Figure 2. The
contributions of different parts of the surround to the modulation of contrast
detection. a. Butterfly-shaped end and side surround flankers. Either the top
and bottom quadrants or the left and right quadrants of a full surround grating
( Figure 1a) were removed to form
butterfly-shaped end flankers (top, showing cross-orientation) and side flankers
(bottom, showing iso-orientation). The contrast of the surround stimuli was
0.10, a contrast associated with maximal cross-orientation facilitation in
Figure 1a. b. The effects of cross-oriented
side and end flankers and full surrounds on contrast detection. c. The effects
of iso-oriented side and end flankers and full surrounds on contrast detection
as a control measurement.
Experiment II. Contributions of the End and Side Components of the Surround Stimuli to Cross Surround Facilitation of Contrast Detection
There exists neurophysiological evidence that surround
modulation outside the classic receptive fields is not uniform
( Walker et al., 1999), and that
stimulating different parts of the surround area could produce either excitatory
or inhibitory modulation
( Kapadia, Westheimer, & Gilbert, 2000).
In psychophysics, for iso surround stimuli, only those placed near the ends of a
target (e.g., collinear flankers) reportedly facilitate detection, while those
placed on the sides or on both ends and sides (thus forming a full surround) are
ineffective
( Snowden & Hammett, 1998;
Solomon & Morgan, 2000). A two-stage
model was proposed
( Solomon & Morgan, 2000), in which a
second-stage spatial filter consists of excitatory lobes near the ends and
inhibitory lobes near the sides of the spatial filter center. Inhibition from
the side lobes thus would cancel excitation from the end lobes when a full
surround stimulus is used.
By using butterfly-shaped flankers at an optimal
contrast (0.10) covering only the end or side portions of the surround
( Figure 2a), we found that at
cross-orientation, both side and end flankers facilitate detection, though
facilitation by the full surround is the strongest
( Figure 2b). Therefore, the two-stage
spatial filter model
( Solomon & Morgan, 2000) may need to
be revised to accommodate cross surround modulation. For example, the side lobes
of the second-stage filter become excitatory when excited by cross surround
stimuli. On the other hand, our iso-orientation data
( Figure 2c) from a control measurement show
that only end-flankers facilitate detection while full- and side-flankers do
not, consistent with
Solomon and Morgan (2000). However,
neither previous data nor our current data show evidence for inhibition by iso
side-flankers that would directly support the existence of inhibitory side lobes
in second-stage spatial filters. An alternative and probably better explanation
might be drawn from a surround modulation model
( Li, 2000) that proposes that smooth contours
(collinear flankers in this case) may result in higher neural
responses. Experiment III. Spatial Frequency and Orientation Tuning of Cross Surround Facilitation of Contrast Detection
We used the full-surround stimulus configuration
( Figure 1a) again to study the spatial
frequency and orientation tuning properties of cross surround facilitation. For
studying spatial frequency tuning, the surround contrast was set to the optimal
(0.10) and the surround spatial frequency was varied from 4 to 16 cpd in half
octave steps. It is clear that cross surround facilitation of contrast detection
is sharply tuned to the target spatial frequency. For the D6 target at a peak
spatial frequency of 8 cpd, cross-orientation surround facilitation peaks at the
same spatial frequency and quickly diminishes when surround spatial frequency is
about half an octave away from the target spatial frequency
( Figure 3a). The sharp spatial frequency
tuning is also seen in cross surround modulation of suprathreshold contrast
discrimination ( Yu & Levi, 2000) and in
iso (collinear) surround modulation of contrast detection
( Polat & Sagi, 1993) and
suprathreshold contrast discrimination
( Yu & Levi, 2000).
While surround facilitation is narrowly tuned to
spatial frequency, it is very broadly tuned to orientation. Surround
facilitation of contrast detection was nearly unaffected by orientation
differences ranging from 90 degrees (cross orientation to the target) to as low
as 40 degrees ( Figure 3b) for the same
stimulus configuration, except that it was the surround orientation, rather than
the spatial frequency, which was varied. Surround facilitation is reduced at
smaller orientation differences and is completely eliminated at iso-orientation
(0 deg). These tuning properties suggest that neurons responding to the target
could receive surround inputs from a group of neurons narrowly tuned to target
spatial frequency but loosely tuned to cross-orientation, perhaps reflecting a
signal pooling over a large range of
orientations. Experiment IV. Psychophysical Mechanisms of Cross Surround Facilitation: Uncertainty Reduction Versus Signal-to-Noise Enhancement
Psychophysical cross facilitation of contrast detection
could be potentially interpreted in terms of two general visual processes:
low-level internal noise reduction and/or target signal enhancement, as well as
higher-level uncertainty reduction at a decision stage. It has been proposed
that contrast detection is limited by the visual system’s internal noise
and efficiency
( Burgess, Wagner, Jennings, & Barlow, 1981;
Pelli, 1981). Internal noise such as
sampling errors of visual receptors and spontaneous neural activities, etc.,
reduce the signal-to-noise ratio of neural responses. At a higher-level decision
stage, the visual system’s uncertainty about what constitutes the perfect
stimulus template, and, therefore, what spatial channels to monitor, impairs
efficiency and hinders contrast detection
( Burgess et al., 1981;
Pelli, 1981). Cross surrounds could
improve efficiency and facilitate detection by reducing stimulus uncertainty.
They could also facilitate detection by reducing the internal noise and/or
enhancing the stimulus signals. Meanwhile,
Lu and Dosher (1998) suggested that the
reduction of additive internal noise is quantitatively the same as signal
enhancement. Thus we will use “ signal-to-noise enhancement” in this
experiment to refer to low-level visual processing affecting contrast detection,
in contrast to higher-level uncertainty reduction.
We conducted three independent measurements to separate
the contributions of uncertainty reduction and signal-to-noise enhancement to
cross surround facilitation of contrast detection.
a. Measuring cross surround facilitationin external visual noise
First we adapted an equivalent noise protocol
( Pelli, 1981;
Pelli & Farell, 1999) and measured
cross surround effects with the target in external visual noise. In this
protocol, contrast detection is measured with the target presented in different
amounts of external noise. At high external noise, any effect of internal noise
would be masked, so that changes of efficiency and associated uncertainty due to
cross surround facilitation can be
isolated. Figure 3. The
spatial frequency and orientation tuning of cross surround facilitation of
contrast detection. a. Spatial frequency tuning. The peak spatial frequency of
the D6 target was constant at 8 cpd. b. Orientation tuning. The D6 target was at
0 deg orientation. In both experiments, the surround contrast was constant at a
contrast of 0.10.
In the study, we added external Gaussian noise of
various intensities to the target
( Figure 4a, see figure legend for details of
noise properties) and measured TvN (thresholds vs. noise) functions
( Figure 4b) with and without the presence of
cross surrounds. Results ( Figure 4b)
indicate contrast facilitation at all levels of external noise, though the
effects are smaller when noise is intense. To characterize internal noise and
efficiency changes, we fit the data with the function Th =
k(N i2 + N e2) 1/2, where Th
is the contrast threshold, N e is external noise in noise threshold
units, and k and N i are free parameters. Noise threshold is 0.12 for
Y.C. and 0.09 for the other two observers. For the TvN functions measured with
no surround (simple detection), k is the high noise slope on linear axes and
k 2 is inversely proportional to efficiency (large k 2
indicates poorer efficiency), and N i is the equivalent internal noise
(in noise threshold units). Data fitting indicates that the cross surround
reduced both N i and k ( Figure 4b,
Table 1). The reduction of k represents a
downward shift (facilitation) of the entire TvN curve, and the reduction of
N i accounts for the remaining facilitation at zero and low external
noise. For observers S.T. and Y.C., the cross surround/no surround ratio of
N i (R Ni) is 0.80 ± 0.13 and 0.64 ± 0.07, and the
cross surround/no surround ratio of k is 0.72 ± 0.05 and 0.74 ± 0.06,
respectively. Because S.T.’s R Ni reduction is relatively small,
most of this observer’s facilitation comes from the change of k, while
R Ni and k have similar contribution to Y.C.’s
facilitation.
The cross surrounds might have reduced k (which is
determined by the facilitation at high noise) by two means. First, the cross
surrounds could reduce stimulus uncertainty by providing the visual system with
better stimulus information, such as the location and spatial frequency cues, so
that the visual system could place heavier weights on the relevant channels and
exclude irrelevant ones. Second, the cross surrounds at high external noise
could enhance the signal-to-noise ratio of the relevant channel. This could be
done by suppressing multiplicative noise (whose amplitude is proportional to
stimulus energy), a factor not included in the Pelli uncertainty model, but is
considered in Lu and Dosher's Perceptual Template Model
( Lu & Dosher, 1999), or by enhancing
stimulus signals through low-level neural interactions even at high noise. The
two stages that we consider are depicted in
Figure 7 of the “Discussion.”
The following control experiment measured
iso surround modulation of contrast detection in external noise and the results
helped rule out the uncertainty reduction
explanation. With other stimulus parameters
identical to the cross stimuli ( Figure 4a),
the surround ( Figure 4c) is now in iso
(collinear) orientation and butterfly shaped (a full iso surround would have no
effect; see Figure 2c). Results
( Figure 4d) indicate that iso surrounds only
facilitate contrast detection at low noise and have no effect at external noise
2 to 3 times the noise detection threshold, which results in a significant
change of N i but no change of k ( Table 1).
The iso surrounds here provide not only the same temporal and spatial cues of
the target (when, where, and what spatial frequency) as do the cross surrounds
( Figure 4a), but also additional orientation
and phase cues (it is also easier to compare spatial frequencies of collinear
gratings). However, these target cues appear not useful to, or not used by, the
visual system to reduce stimulus uncertainty and form a better stimulus
template. It is unlikely that a threshold reduction at high noise due to these
target cues is offset by iso surround suppression, because the butterfly-shaped
iso surrounds at the current contrast (0.10) produce strong facilitation at low
noise. On the basis of these iso surround data, we suspect that cross surrounds
would have no effect on stimulus uncertainty. Therefore, facilitation at high
noise and associated k reduction are mainly contributed by lower-level visual
mechanisms, either multiplicative noise reduction or signal enhancement or their
combination.
According to Pelli’s equivalent noise model
( Pelli, 1981;
Pelli & Farell, 1999), if uncertainty
is not reduced at high noise levels, it is also not reduced at low (or zero)
noise levels, assuming a strong correlation between efficiency and uncertainty.
Therefore, we would conclude that cross facilitation at zero or low external
noise is only contributed by signal-to-noise enhancement. However, other models
might allow independent mechanisms at low and high noise (e.g.,
Lu & Dosher, 1999). Thus, in order to
make our conclusions less model dependent, we examined whether cross surrounds
could affect uncertainty at zero and low noise, even though these surrounds are
not effective in reducing uncertainty at high noise levels. The following two
experiments served this
purpose.
|
|
cross
surround
|
|
|
|
iso surround
|
|
|
|
Ni
|
k
|
|
|
Ni
|
k
|
|
ST
|
|
|
|
AJ
|
|
|
|
w/o sur
|
1.38 ± 0.13
|
0.022 ± 0.001
|
|
w/o sur
|
1.16 ± 0.10
|
0.026 ± 0.001
|
|
w/ sur
|
1.11 ± 0.14
|
0.016 ± 0.001
|
|
w/ sur
|
0.62 ± 0.04
|
0.026 ± 0.000
|
|
ratio
|
0.80
± 0.13
|
0.72
± 0.04
|
|
ratio
|
0.53
± 0.06
|
0.99
± 0.04
|
|
YC
|
|
|
|
YC
|
|
|
|
w/o sur
|
1.81 ± 0.15
|
0.020 ± 0.001
|
|
w/o sur
|
1.73 ± 0.36
|
0.018 ± 0.003
|
|
w/ sur
|
1.16 ± 0.09
|
0.015 ± 0.001
|
|
w/ sur
|
0.96 ± 0.22
|
0.018 ± 0.002
|
|
ratio
|
0.64
± 0.07
|
0.74
± 0.05
|
|
ratio
|
0.55
± 0.17
|
0.98
± 0.20
|
Table 1. Summary of fitting
parameters (N i and k) and
their ratios
Figure 4. Cross surround
facilitation of contrast detection in noise. a. Stimuli with full cross
surrounds. The stimuli consisted of the same D6 target and cross-oriented
surround as in Figure 1a except that a
static two-dimensional Gaussian noise abutting the inner edge of the surround
was added to the target. The surround contrast was 0.10. The random Gaussian had
a central spatial frequency of 8 cpd and a bandwidth of 3 octaves. Noise with
contrasts equal to 1 to 4 times the noise detection threshold was added to the
target. The Gaussian noise was randomized for each trial. b. Threshold versus
noise (TvN) functions and data fitting under baseline and cross surround
conditions. Fitting parameters are summarized in
Table 1. The sloping dashed lines indicate
kN e and the horizontal
dashed lines indicate kN i.
The reduction of N i is
indicated by the horizontal difference of two bars on the x axis, and the
reduction of k is indicated by the vertical shift of the two sloping dashed
lines. c. Stimuli with butterfly-shaped iso surrounds. The target and noise
conditions, as well as the surround contrast, are identical to those of the
cross stimuli in “a.” d. Iso TvN functions and data fitting curves.
The noise detection threshold was 0.09 for A.J. and 0.12 for Y.C. Fitting
parameters are summarized in Table 1.
b. Estimating cross surroundinduced changes of the slope (β) of the psychometric function and the uncertainty parameter (M)
The uncertainty model
( Cohn & Lasley, 1974;
Pelli, 1985) assumes that for contrast
detection, the observer needs to monitor a number of independent spatial
channels to make a decision about the stimulus. Because of uncertainty about the
relevant channel, some of the monitored channels are irrelevant. The number of
the spatial channels the observer is monitoring, and therefore the uncertainty,
is indicated by the parameter M. M is equal to 1 at zero uncertainty, and larger
M indicates larger uncertainty. Higher uncertainty results in higher threshold
and steeper slope of the psychometric function because of a maximum-of-channels
rule that we assume for the decision stage (see “Discussion”). The
Weibull β, a common index of the slope,
is approximately 1.4 when M = 1
( Pelli, 1985). This experiment measured
the slope change of the psychometric function under the influence of cross
surround and the concurrent change of the uncertainty parameter (M).
Because our earlier data were collected with a 2AFC
staircase method that did not allow a precise estimation of the slope (β)
and the uncertainty parameter (M), we collected new data using a 5-level
rating-scale method of constant stimuli (see “Methods”). The
d’ values ( Figure 5a) for different
target contrasts in an individual trial block were first determined using a
maximum likelihood fit to the rating scale data. In order to carry out a
standard uncertainty analysis, we converted these d’ values to percentage
correct in a 2AFC method. The standard errors of the percent correct data were
calculated by a Monte Carlo simulation based on the standard errors of d'.
We first fit these percentage correct data with a
Weibull
function:  | | (1) |
to estimate the threshold
( th) at the 75% correct level and the
slope of the psychometric functions
( β). Here
c in the equation is the target
contrast. A nonlinear least square method (the Matlab lsqnonlin function) was
used for optimization. Because of the large run-to-run differences of
β within the same observer, we
constrained β to be the same
across runs, with threshold being variable from run to run. The left half of
Table 2 gives each observer’s mean
thresholds (weighted mean across individual blocks) and
β.
Figure 5b shows each observer’s mean
percent correct data converted from d’ and the simulated psychometric
functions based on each observer’s mean threshold and
β under surround and no surround
conditions. Table 2 shows cross surround
facilitation (reduced contrast threshold) in both observers. For observer J.E.,
β is unchanged by the cross
surround (1.53 ± 0.19 vs. 1.58 ± 0.18), implying no uncertainty
change. However, for observer M.L., β is reduced but the change is not
significant (1.83 ± 0.20 vs. 1.53 ± 0.16 with a change of 0.30 ±
0.26). The slope data therefore do not provide strong support for uncertainty
reduction in cross surround facilitation. In
addition to the Weibull fit, we also fit the data with an uncertainty model
where the observer attends to M channels in each of the two intervals
( Pelli, 1985). Only one of the M channels
carries a signal. The equation used to fit
the data is written
as:  | | (2) |
Here c
is the target contrast, f(x) is the
Gaussian probability density function,
F(x) is the cumulative Gaussian,
k is the sensitivity or gain parameter,
and M is the uncertainty parameter. We
used a maximum rule whereby the observer is assumed to choose the interval that
contains the maximum response. The first term gives the probability that the
channel with the signal has the maximum output; the second term is the
probability that a noise channel in the signal interval has maximum output. The
data were fit by a method similar to that used for fitting the Weibull function.
There were as many gain parameters (gain is the theoretical sensitivity when
M=1) as there were repeated runs for a
given surround condition. An additional parameter specified
M, the number of attended channels on
each stimulus presentation. The weighted mean of the gain parameters and
uncertainty parameters for each observer are listed in the right half of
Table 2.
Figure 5c shows each observer’s mean
percent correct data and the simulated psychometric functions based on each
observer’s mean gain and M
values. Results show unchanged M (2.0
± 1.2 vs. 1.9 ± 1.1) for J.E. and insignificantly reduced
M (6.0 ± 3.6 vs. 1.9 ± 1.0)
for M.L. because of the large errors, again not supporting a significant
uncertainty reduction in cross surround facilitation. Meanwhile, the gain is
increased for observer J.E. (from 0.50 ± 0.03 to 0.65 ± 0.04) but
unchanged for observer M.L. (0.64 ± 0.04 vs. 0.65 ± 0.03).
In summary, these two observers’ data do
not support uncertainty reduction in cross surround facilitation. As
Table 2 suggests, the number of monitored
channels with no surround is very small (2-6), very low when compared to M >
100 at high uncertainty situations
( Pelli, 1985). There is really not much
uncertainty even with no surround in our tasks for these two observers. This is
especially seen in observer J.E. with M=2.0 ± 1.2. This low value of M
suggests that the surround is not able to do much uncertainty
reduction.
|
|
Weibull fit |
|
M fit |
|
|
|
threshold |
beta |
|
gain |
M |
|
JE |
baseline |
2.33
+
0.11 |
1.53
+
0.19 |
|
0.50
+
0.03 |
2.0
+
1.2 |
|
cross |
1.75
+
0.08 |
1.58
+
0.18 |
|
0.65
+
0.04 |
1.9
+
1.1 |
|
|
|
|
|
|
|
|
|
|
|
|
ML |
baseline |
2.37
+
0.10 |
1.83
+
0.20 |
|
0.64
+
0.04 |
6.0
+
3.6 |
|
cross |
1.84
+
0.07 |
1.53
+
0.16 |
|
0.65
+
0.03 |
1.9
+
1.0 |
Table 2. Summary of parameters
from Weibull fit ( Figure 5b) and M fit
( Figure 5c). Thresholds and gains are
averaged from fitting of individual data sets (see text).
Figure 5.
Estimating changes of the psychometric function slope and the uncertainty factor
(M) under the influence of the cross surround. a. d’ for each target
contrast. The empty symbols indicate d’ for individual blocks, and the
filled symbols indicate the mean d’. J.E. had two sets of target contrasts
for baseline and cross surround conditions. b. Mean percent correct data
converted from d’ (filled symbols) and Weibull fits
( Table 2, left). c. Mean percent correct data
(filled symbols) and M fits ( Table 2, right).
The curves in both b and c do not optimally match the mean d’ data because
the fitting was done on individual data sets rather than on the mean d’s
(see text).
c. Measuring cross surround facilitation at the dipper of the TvC function
We also studied the effect of cross surrounds on
near-threshold contrast discrimination, which we believe provides a more robust
means to examine the role of uncertainty in cross surround facilitation. It is
well known that contrast threshold for a target presented on a near-threshold
pedestal is lower than the detection threshold, which forms a dipper in the TvC
function. Pelli’s uncertainty model
( Pelli, 1985) explains such contrast
facilitation as the reduction of uncertainty.
Legge, Kersten, and Burgess (1987) showed
that the log-log d’ slope of the psychometric function reduces from around
2 for detection to around 1.5 for near-threshold discrimination. According to
the uncertainty model, a slope decrease would indicate diminished uncertainty
(Weibull β is nearly 1.41 when M = 1). Moreover, as
Table 2 indicates, uncertainty for detecting
the target stimulus is not very high (β = 1.53 and 1.83 and M = 2.0 and 6.0
for two observers, respectively). If the sole function of the cross surround is
to reduce uncertainty, it would not have much uncertainty to reduce when a
near-threshold pedestal is already there. Therefore, it can be predicted that a
cross surround would not be able to significantly reduce the contrast threshold
at the dipper. On the other hand, if the cross surround improves the gain
through signal-to-noise enhancement, it would reduce the already low threshold
at the dipper and form a “super dipper.” To test these predictions,
we measured near-threshold discrimination with or without the cross surround
presentation and compared it with cross surround facilitation of contrast
detection.
The same three observers in Experiment 1
( Figure 1) participated in this experiment
and contrast thresholds were again measured with a 2AFC staircase method. The
stimulus configuration was the same as that in
Figure 1, except that the surround contrast
was constant at 0.10 and a circular-windowed sinusoidal grating pedestal was
added. The pedestal abutted the surround grating from inside (pedestal diameter
= surround inner diameter), had the same spatial frequency and orientation as
the target (8 cpd, vertical), and had contrasts ranging from 0 to 0.10.
Figure 6 shows that (1) baseline thresholds
with no surround presentation were reduced from detection to near-threshold
discrimination (mean thresholds from 0.03 at 0 pedestal contrast to 0.02 at 0.05
pedestal contrast), showing the dipper effect typically seen in a TvC function.
(2) The cross surround greatly reduced contrast thresholds, not only for
detection, but also for near-threshold discrimination at the dipper.
Facilitation for near-threshold discrimination was consistent among all three
observers and the average threshold at the dipper was reduced from 0.02 to as
low as 0.01 at 0.05 pedestal contrast, indicating the formation of a
“super dipper”! This evidence argues strongly against an
uncertainty-reduction explanation of cross surround facilitation and favors a
lower-level signal-to-noise enhancement
theory. Figure 6. Cross
surround effects on near-threshold contrast discrimination.
Our experimental findings can be summarized as
following: (1) The cross surround stimuli, whether they are full- or
partial-annular gratings or Gabor patches, can facilitate contrast detection
under appropriate contrasts
( Figure 1- 2).
(2) Cross surround facilitation is sharply tuned to target spatial frequency
( Figure 3a) but only loosely tuned to cross
orientation ( Figure 3b). (3) Low-level
psychophysical mechanisms of signal-to-noise enhancement, rather than
higher-level uncertainty reduction, make a major contribution to cross surround
facilitation, as indicated by three separate measurements in Experiments 4a, 4b,
and 4c.
The general class of models that we are considering is
shown in Figure 7. This example has nine
mechanisms feeding into three second-stage collator channels
( Mussap & Levi, 1995). Only one of the nine
mechanisms (R) is carrying relevant information. We assume that the second stage
mechanisms linearly summate the first stage inputs with weights that can be
modulated by the surround. Because the initial mechanisms are assumed to have
independent noise, the ideal summation corresponds to d' summation with a
Minkowski exponent of two ( Quick, 1974).
We further assume that the outputs of the second
Figure 7. A general
uncertainty model. The responses of the relevant mechanism (R) and irrelevant
mechanisms (I) (circles) are first linearly summated by second-stage collator
channels (ellipses). The outputs of collator channels are then combined
following a maximal rule at the decision stage (rectangle). The presence of
irrelevant channels at the decision stage produces uncertainty.
stage channels are combined by a maximum rule
(Max), rather than by linear summation. The Max rule summation corresponds to d'
summation with a Minkowski exponent of infinity. When the maximum rule summation
take place at the decision stage, late in visual processing, it is commonly
referred to as the uncertainty explanation
( Pelli, 1985) because the presence of
irrelevant channels at the decision stage is called “uncertainty.”
This two-stage model is able to handle a wide variety of data that include
uncertainty manipulations
( Cohn & Lasley, 1974;
Pelli, 1985).
Experiment 4a used noise masking to show that the
cross surround produced more facilitation than did the iso surround at high
noise masking. We argued that if the facilitation were due to a reduction of
uncertainty then the iso surround should have produced more facilitation because
it provides more cues to the relevant mechanisms than does the cross surround.
We further argued that the lack of uncertainty reduction at high noise levels
should also apply to the zero noise level that is the primary interest of this
work. However, because it is possible that uncertainty reduction could work
differently at high and low noise
( Lu & Dosher, 1998), we carried out two
further experiments.
Experiment 4b examined the shape of the psychometric
function with and without a cross surround with no noise present. The logic of
these experiments was that if the cross surround reduced the number of
irrelevant channels at the decision stage (uncertainty reduction), then both the
psychometric function slope (the Weibull β parameter) and the uncertainty
parameter, M (the total number of channels feeding into the stage where the
maximum summation rule is applied), would be reduced. We used the method of
constant stimuli to measure d' at four stimulus levels near threshold. The d's
were fitted with a 2AFC Weibull function and with a 2AFC uncertainty function.
In a 2AFC experiment, there are a total of 2M-1 irrelevant channels and one
relevant channel at the max rule stage. The Weibull fit of both observers showed
that the cross surround produces a 30% reduction of threshold, compatible with
our other studies. Observer J.E. showed that the threshold reduction did not
involve a change in psychometric function shape in that the Weibull β
parameter and the uncertainty M parameter were unchanged by the surround. The
threshold reduction was achieved by an increase in the gain of the signal
channel. For observer M.L., on the other hand, the threshold reduction was
achieved by a reduction of M rather than by a change in gain. However, the large
standard errors in estimates of M make us cautious about claiming that the
change of M is significant. The striking thing about the psychometric functions
is that they have relatively shallow slopes (low values of β and M) with or
without a surround. The largest value of M is 6.0 ± 3.6, which is quite low
when compared to the uncertainty levels found in other studies
( Pelli, 1985). Thus we believe that under
the conditions of our experiments and with our trained observers, the
uncertainty was always small.
Experiment 4c compared the amount of facilitation at
the trough of the dipper function both with and without the surround. We found
that the presence of the surround produced about the same amount of facilitation
at the trough of the dipper as it did at the detection threshold. If the
surround facilitation had been produced by uncertainty reduction, then we would
expect that the presence of the pedestal would have removed most of the
uncertainty and in the presence of the cross surround the dipper would have been
shallower than the no surround case.
Neurophysiological surround modulation has been known
to be contrast dependent
( Toth, Rao, Kim, Somers, & Sur, 1996;
Levitt & Lund, 1997;
Polat, Mizobe, Pettet, Kasamatsu, & Norcia, 1998;
Kapadia et al., 2000). The surround
contrast dependence of cross surround facilitation resembles some recent
neurophysiological data of surround modulation.
Kapadia et al. (2000) reported that iso
surround modulation of classical receptive fields in alert monkeys is
facilitative at low surround contrasts and suppressive at high surround
contrasts. They suggested that low-contrast surround stimuli produce direct
excitatory inputs to visual neurons, but high-contrast surround stimuli also
produce additional inhibitory inputs through inhibitory inter-neurons that
cancel excitation. We speculate that the cross surround facilitation evident in
our psychophysical experiments could reflect similar excitation-inhibition
dynamics.
Our psychophysical evidence for cross surround
facilitation in low-level vision at least partially supports Wolfson and
Landy’s model
( Wolfson & Landy, 1999) regarding
the roles of spatial filter interactions in texture segregation and visual
search. Their model attributes superior performance of detecting or searching a
textural element surrounded by orthogonal elements to excitatory interactions
between orthogonal spatial filters and poorer performance with iso surround
elements to inhibitory interactions between iso spatial filters. However, this
performance asymmetry could also be explained as a result of stronger surround
inhibition at iso orientation and reduced suppression at cross orientation as
pointed out by Walker et al. (1999), who
reported weak neuronal cross surround suppression but no facilitation. Our data
taken together with recent physiological studies
( Kapadia et al., 2000) suggest that
excitatory interactions do exist between orthogonal spatial filters at low-level
vision and can make a contribution.
On the other hand, poor visual search performance under
iso surround textural conditions and inhibitory interactions between iso spatial
filters proposed by
Wolfson and Landy (1999) are
inconsistent with iso surround facilitation of contrast detection
( Polat & Sagi, 1993), but are
supported by other low-level evidence like iso surround suppression of perceived
contrast ( Cannon & Fullenkamp, 1991).
The usefulness of iso surround facilitation in intermediate-level visual tasks
such as contour integration has been recently questioned
( Hess & Field, 1999). Our
psychophysical data indeed suggest that iso surround facilitation is a very
delicate effect and is easily disturbed by either weak noise (2-3 times noise
threshold, Figure 4b) or by a full iso
surround ( Figure 2c) In contrast, cross
surround facilitation is more robust and less affected by external visual noise.
It is plausible that weak iso surround facilitation may be masked in complex
stimulus configurations, and plays very little role in intermediate-level
vision.
This research was supported by National Institutes of
Health Grants R01EY01728 and R01EY04776. We thank Preeti Verghese for providing
Matlab code for fitting the uncertainty parameter in Experiment IVb. Commercial
relationships:
none.
Burgess, A. E., Wagner, R.
F., Jennings, R. J., & Barlow, H. B. (1981). Efficiency of human visual
signal discrimination. Science, 214,
93-94.
[PubMed]
Cannon, M. W., &
Fullenkamp, S. C. (1991). Spatial interactions in apparent contrast: Inhibitory
effects among grating patterns of different spatial frequencies, spatial
positions and orientations. Vision Research,
31, 1985-1998.
[PubMed]
Chen, C. C., & Tyler, C.
W. (2001). Lateral sensitivity modulation explains the flanker effect in
contrast discrimination. Proceedings of the
Royal Society of London. Series B: Biological Sciences, 268, 509-516.
[PubMed]
Cohn, T. E., & Lasley, D.
J. (1974). Detectability of a luminance increment: Effect of spatial
uncertainty. Journal of Optical Society of
America A, 64, 1715-1719.
[PubMed]
Das, A., & Gilbert, C. D.
(1999). Topography of contextual modulations mediated by short-range
interactions in primary visual cortex. Nature,
399, 655-661.
[PubMed]
Hess, R., & Field, D.
(1999). Integration of contours: New insights.
Trends in Cognitive Science, 3,
480-486.
Hupé, J. M., James, A.
C., Girard, P., & Bullier, J. (2001). Response modulations by static texture
surround in area V1 of the macaque monkey do not depend on feedback connections
from V2. Journal of Neurophysiology,
85, 146-163.
[PubMed]
Kapadia, M. K., Westheimer,
G., & Gilbert, C. D. (2000). Spatial distribution of contextual interactions
in primary visual cortex and in visual perception.
Journal of Neurophysiology, 84,
2048-2062.
[PubMed]
Knierim, J. J., & Van
Essen, D. C. (1992). Neuronal responses to static texture patterns in area V1 of
the alert macaque monkey. Journal of
Neurophysiology, 67, 961-980.
[PubMed]
Legge, G. E., Kersten, D.,
& Burgess, A. E. (1987). Contrast discrimination in noise.
Journal of the Optical Society of America A,
4, 391-404.
[PubMed]
Levi, D. M., Klein, S. A.,
& Aitsebaomo, P. (1984). Detection and discrimination of the direction of
motion in central and peripheral vision of normal and amblyopic observers.
Vision Research, 24, 789-800.
[PubMed]
Levitt, J. B., & Lund,
J. S. (1997). Contrast dependence of contextual effects in primate visual
cortex. Nature, 387, 73-76.
[PubMed]
Li, Z. (2000). Pre-attentive
segmentation in the primary visual cortex.
Spatial Vision, 13, 25-50.
[PubMed]
Lu, Z. L., & Dosher, B. A.
(1998). External noise distinguishes attention mechanisms.
Vision Research, 38, 1183-1198.
[PubMed]
Lu, Z. L., & Dosher, B. A.
(1999). Characterizing human perceptual inefficiencies with equivalent internal
noise. Journal of the Optical Society of
America A, 16, 764-778.
[PubMed]
Mussap, A. J., & Levi,
D. M. (1996). Spatial properties of filters underlying vernier acuity revealed
by masking: Evidence for collator mechanisms.
Vision Research,
36, 2459-2473.
[PubMed]
Nothdurft, H. C.,
Gallant, J. L., & Van Essen, D. C. (1999). Response modulation by texture
surround in primate area V1: Correlates of "popout" under anesthesia.
Visual Neuroscience, 16, 15-34.
[PubMed]
Pelli, D. G. (1981). Effects
of visual noise (Doctoral dissertation,
University of Cambridge, Cambridge, UK, 1981).
Pelli, D. G. (1985).
Uncertainty explains many aspects of visual contrast detection and
discrimination. Journal of the Optical Society
of America A, 2, 1508-1532.
[PubMed]
Pelli, D. G., & Farell,
B. (1999). Why use noise? Journal of the
Optical Society of America A, 16, 647-653.
[PubMed]
Polat, U., Mizobe, K.,
Pettet, M. W., Kasamatsu, T., & Norcia, A. M. (1998). Collinear stimuli
regulate visual responses depending on cell's contrast threshold.
Nature, 391, 580-584.
[PubMed]
Polat, U., & Sagi, D.
(1993). Lateral interactions between spatial channels: Suppression and
facilitation revealed by later masking experiments.
Vision Research, 33, 993-999.
[PubMed]
Quick, R. F. (1974). A vector
magnitude model of contrast detection.
Kybernetik, 16, 65-67.
[PubMed]
Sengpiel, F., Sen, A.,
& Blakemore, C. (1997). Characteristics of surround inhibition in cat area
17. Experimental Brain Research, 116,
216-228.
Sillito, A. M., Grieve, K.
L., Jones, H. E., Cudeiro, J., & Davis, J. (1995). Visual cortical
mechanisms detecting focal orientation discontinuities.
Nature, 378, 492-496.
[PubMed]
Snowden, R. J., &
Hammett, S. T. (1998). The effects of surround contrast on contrast thresholds,
perceived contrast and contrast discrimination.
Vision Research, 38, 1935-1945.
[PubMed]
Solomon, J. A., &
Morgan, M. J. (2000). Facilitation from collinear flanks is cancelled by
non-collinear flanks. Vision Research,
40, 279-286.
[PubMed]
Toth, L. J., Rao, S. C., Kim,
D., Somers, D., & Sur, M. (1996). Subthreshold facilitation and suppression
in primary visual cortex revealed by intrinsic signal imaging.
Proceedings of the National Academy of Science
of the United States of America, 93, 9869-9874.
[PubMed]
Walker, G. A., Ohzawa, I.,
& Freeman, R. D. (1999). Asymmetric suppression outside the classical
receptive field of the visual cortex. Journal
of Neuroscience, 19, 10536-10553.
[PubMed]
Wolfson, S. S., &
Landy, M. S. (1999). Long range interactions between oriented texture elements.
Vision Research, 39, 933-945.
[PubMed]
Yu, C., Klein, S. A., &
Levi, D. M. (2001). Surround modulation of perceived contrast and the role of
brightness induction. Journal of Vision,
1, 18-31.
Yu, C., & Levi, D. M.
(2000). Surround modulation in human vision unmasked by masking experiments.
Nature Neuroscience, 3, 724-728.
[PubMed]
|