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BOLD fMRI Response of Early Visual Areas to Perceived Contrast
in Human Amblyopia
BRADLEY G. GOODYEAR,1,2 DAVID A. NICOLLE,3 G. KEITH HUMPHREY,4 AND RAVI S. MENON1,2,5
1
Laboratory for Functional Magnetic Resonance Research, The John P. Robarts Research Institute, London, Ontario N6A
5K8; 2Department of Medical Biophysics, The University of Western Ontario, London, Ontario N6A 5C1; 3Department of
Ophthalmology, London Health Sciences Centre, London, Ontario N6A 5A5; 4Department of Psychology, The University of
Western Ontario, London, Ontario N6A 5C2; and 5Department of Diagnostic Radiology and Nuclear Medicine,
The University of Western Ontario, London, Ontario N6A 5A5, Canada
Received 5 November 1999; accepted in final form 6 July 2000
Goodyear, Bradley G., David A. Nicolle, G. Keith Humphrey,
and Ravi S. Menon. BOLD fMRI response of early visual areas
to perceived contrast in human amblyopia. J Neurophysiol 84:
1907–1913, 2000. In this study, we used a temporal two-alternative
forced choice psychophysical procedure to measure the observer’s
perception of a 22% physical contrast grating for each eye as a
function of spatial frequency in four subjects with unilateral amblyopia and in six subjects with normal vision. Contrast thresholds were
also measured using a standard staircase method. Additionally, bloodoxygenation-level– dependent (BOLD) functional magnetic resonance
imaging (fMRI) was used to measure the neuronal response within
early visual cortical areas to monocular presentations of the same 22%
physical contrast gratings as a function of spatial frequency. For all six
subjects with normal vision and for three subjects with amblyopia, the
psychophysically measured perception of 22% contrast as a function
of spatial frequency was the same for both eyes. Threshold contrast,
however, was elevated for the amblyopic eye for all subjects, as
expected. The magnitude of the fMRI response to 22% physical
contrast within “activated” voxels was the same for each eye as a
function of spatial frequency, regardless of the presence of amblyopia.
However, there were always fewer “activated” fMRI voxels during
amblyopic stimulation than during normal eye stimulation. These
results are consistent with the hypotheses that contrast thresholds are
elevated in amblyopia because fewer neurons are responsive during
amblyopic stimulation, and that the average firing rate of the responsive neurons, which reflects the perception of contrast, is unaffected in
amblyopia.
INTRODUCTION
Amblyopia, clinically defined as a reduction in visual acuity
in an otherwise healthy and properly corrected eye, is found in
1– 4% of the North American population (Ciuffreda et al. 1991;
Daw 1995; Kiorpes and Movshon 1996; von Noorden 1990).
The study of amblyopia in humans has almost entirely been by
psychophysical means, where it has been demonstrated that the
disorder produces a variety of spatial vision abnormalities
(Carkeet et al. 1996; Hess et al. 1978; McKee et al. 1992; Reed
et al. 1996; von Noorden 1990). A ubiquitous finding is a
reduction in contrast sensitivity, the reciprocal of the contrast
Address for reprint requests: B. G. Goodyear, Laboratory for Functional
Magnetic Resonance Research, The John P. Robarts Research Institute, 100
Perth Dr., PO Box 5015, London, Ontario N6A 5K8, Canada (E-mail:
[email protected]).
www.jn.physiology.org
required to visually detect a target (for review, see Ciuffreda et
al. 1991), which for the normal eye is maximum between 2 and
5 cycles per degree (cpd) (see for example, Blakemore and
Campbell 1969; Campbell and Robson 1968). For the amblyopic eye, the reduction in contrast sensitivity becomes more
pronounced at higher spatial frequencies, and in some cases,
maximum sensitivity occurs at a spatial frequency lower than
that for the normal eye (Bradley and Freeman 1981; Hess and
Pointer 1985; Hess et al. 1978).
Contrast detection thresholds are dependent on the “noise”
present in the visual system (e.g., Graham 1989). That is,
neural firing rates (integrated over some region) must exceed
some signal-to-noise ratio threshold in order for a contrast
pattern to be detected by the observer. In the case of amblyopia, more contrast may be required to surpass this threshold
signal-to-noise ratio. Decreases in signal could result from
fewer responsive neurons during stimulation of the amblyopic
eye or from neural firing rates that are less during amblyopic
eye stimulation than during normal eye stimulation, while
increases in noise could result from a loss of neural connections or a rearrangement of connections within the cortex (for
discussion see Kiorpes and McKee 1999; Kiorpes et al. 1999;
Levi 1991). In contrast-matching studies performed well above
threshold, targets viewed separately with the amblyopic and
normal eye appear to have the same contrast (Hess and Bradley
1980; Hess et al. 1983; Loshin and Levi 1983). A possible
interpretation of this result is that once the detection signal-tonoise ratio of neural activity has been surpassed, the perception
of contrast may depend on the average firing rate of the
responsive neurons, which appears not be impaired in amblyopia (Levi 1991).
Animal models have demonstrated that neural substrates of
amblyopia are evident in visual areas as early as primary visual
cortex (area V1) in the form of a reduction in binocular
processing and/or a marked shift in the ocular dominance of
neuronal response away from the amblyopic eye (Crawford
and von Noorden 1979, 1980; Hubel et al. 1977; Kiorpes et al.
1998; LeVay et al. 1980; Movshon et al. 1987). Although
studies of human amblyopia have also demonstrated a decrease
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1907
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GOODYEAR, NICOLLE, HUMPHREY, AND MENON
FIG. 1. Method of determining the perception of 22% contrast as a function of spatial frequency. A: an example of 2 trials. The
spatial frequency being tested (i.e., stimulus ‘1’) is presented for 500 ms, followed by a blank gray screen for 500 ms, and then
the reference frequency (i.e., stimulus ‘2’), which is common to all trials is presented for 500 ms at 12, 17, 22, 27, or 32% contrast.
The subject then chooses the target (‘1’ or ‘2’) that appeared to have the greater contrast. In the example 1st trial, the subject
probably chooses ‘2’. In the next trial, the contrast of ‘1’ is kept at 22%, and the contrast of ‘2’ is randomly chosen from 1 of the
above-mentioned 5. In this example 2nd trial, the subject probably chooses ‘1’ as having the greater contrast. B: an example of a
response function corresponding to 1 test spatial frequency. The percentage of subject responses indicating the reference frequency
(i.e., stimulus ‘2’) had the greater contrast is plotted vs. the actual contrast of stimulus ‘2’. The contrast of stimulus ‘2’ that matches
the contrast of stimulus ‘1’ is taken as the 50% point on a curve fitted to the data. In this example, the 22% contrast test frequency
appears to be the same as a 19.8% contrast reference frequency. One response function is obtained for each tested spatial frequency.
in binocular interaction (Holopigian et al. 1986; Horton et al.
1997; Levi et al. 1979), histological studies of human visual
cortex demonstrate no shift in ocular dominance away from the
amblyopic eye (Horton and Hocking 1996; Horton and Stryker
1993). However, this may have been due to the onset of
amblyopia being after the critical period of ocular dominance
column development (Daw 1995).
Neuroimaging studies of human amblyopia in living human
brain using positron emission tomography (PET) (Demer et al.
1988) and single photon emission computed tomography
(SPECT) (Kabasakal et al. 1995) have demonstrated that the
measured signal within V1 during monocular stimulation of the
amblyopic eye is less than that measured during monocular
stimulation of the normal eye. However, no psychophysical
assessment of the perception of contrast was determined. Magnetoencephalography (MEG) has demonstrated interocular differences in the magnitude of evoked magnetic responses to
chromatic gratings throughout the entire occipital cortex of
amblyopes; however, no correlation with contrast sensitivity of
the amblyopic eye was found (Anderson et al. 1999). Because
the magnitude of the measured signal within an image voxel
during functional magnetic resonance imaging (fMRI) is
thought to be correlated with the amount of neural activity
within that voxel (for a review, see Ogawa et al. 1998), fMRI
is well suited for noninvasively measuring the neuronal response to suprathreshold contrast. We investigated the perception of contrast using both psychophysical and fMRI measurements to understand the relationship between these very
different methods and to determine the neural correlates of
contrast perception in human amblyopia.
METHODS
Subjects
Four subjects with unilateral amblyopia developed during early
childhood or infancy were recruited through the Department of Ophthalmology at the London Health Sciences Center, London, Ontario,
Canada. Each subject had been previously evaluated clinically by
orthoptic assessment. During all experiments, each subject’s vision
was optically corrected using their existing prescription lenses. Six
subjects with no known visual deficits were recruited from the academic environment of the University of Western Ontario (UWO) to
act as control subjects. All subjects had no previous experience with
MR imaging. The experimental protocol was approved by the UWO
Human Subjects Review Board.
Visual stimuli
Visual stimuli consisted of stationary vertical sinusoidal gratings at
six spatial frequencies [0.5, 1, 2, 4, 8, 12 cycles per degree (cpd)] and
at a mean luminance of 20 cd/m2. Contrast and luminance of each
grating were measured using a Minolta CS-100 Chroma Meter (Minolta Camera, Osaka, Japan). Contrast was defined in the usual way as
the maximum luminance of the grating minus the minimum luminance, divided by twice the mean luminance. Each grating was
confined to a circle that subtended 12° of visual angle, and was
reduced in contrast near the edge of the circle to eliminate sharp
edges. The surrounding area of the display was gray at a luminance of
20 cd/m2. Visual stimuli were presented on a projection screen that
was mounted onto the patient bed of the MR scanner, and was located
1.25 m from the subject’s eyes. An angled mirror, positioned above
the subject’s eyes, provided a full view of the screen. Subjects wore
a pair of liquid crystal shutter glasses (Milgram 1987), allowing the
experimenter to control when each eye viewed the stimulus.
Psychophysical measurements of the perception of contrast
Psychophysical experiments were conducted while the subject lay
in the MR scanner. The perception of 22% physical contrast was
measured at each spatial frequency by obtaining the matching contrast
of a standard reference frequency (1 cpd for amblyopes, 4 cpd for
normals) using a temporal two-alternative forced choice procedure
shown by example in Fig. 1A. The eye being tested was presented
with one of the six test frequency gratings for 500 ms at 22% contrast
with the eyepiece of the shutter glasses opaque for the fellow eye. This
was followed by a 500-ms presentation of an isoluminant gray screen
matched in mean luminance to the grating. Finally, the reference
frequency, which did or did not differ in physical contrast from that of
the test frequency, was presented for 500 ms. The subject was then
asked to choose the grating that contained the greater contrast. This
was repeated to obtain five responses at each of five contrasts of the
FMRI
RESPONSE TO CONTRAST IN HUMAN AMBLYOPIA
reference frequency (12, 17, 22, 27, and 32%; this range of contrasts
was selected on the basis of pilot studies), which were paired with the
test frequency in random order. For one-half of the trials, the order of
presentation was reversed. The perceived contrast of the test frequency grating was then obtained as the matching contrast of the
reference frequency by taking the 50% point on a fitted curve to the
corresponding response function (see Fig. 1B) (Wetherill and Levitt
1965). This procedure was then repeated for the remaining test frequencies, and then the whole procedure was repeated for the other
eye.
An additional measurement of the perception of contrast was made
to compare contrast perception across eyes. To accomplish this, the
22% contrast reference frequency was presented to one of the eyes for
500 ms. The eyepiece of the glasses was then made opaque for that
eye. Then, the fellow eyepiece was made transparent, and the reference frequency was shown to the other eye at one of the above five
contrasts for 500 ms. The same forced-choice procedure was then
used to match the contrast of the 22% reference frequency as seen
with one eye to that seen with the other eye.
Finally, contrast threshold measurements were taken for each eye
separately using a standard staircase method. Because contrast perception measurements were obtained as matches to a fixed reference
frequency, only the contrast threshold of the reference frequency was
measured.
fMRI
All imaging experiments were performed on a Varian/Siemens
Unity INOVA 4 Tesla whole-body MR scanner, equipped with 25
mT/m whole-body gradients. An 8-cm-diameter quadrature radio frequency (RF) surface coil was placed at the back of the subject’s head
near the occipital pole to transmit and receive the MR signal. The
subject’s head was immobilized using a well-padded head vice that
was mounted onto the same platform that housed the RF coil. Seven
imaging planes were prescribed parallel to the calcarine fissure of the
visual cortex, which was identified within each subject with the aid of
a sagittal localizer anatomical image. The functional image data
acquisition scheme was a T*2-weighted, eight-segment, slice-interleaved, echo-planar imaging sequence (Menon and Goodyear 1999)
[128 ⫻ 128 matrix, 14 ⫻ 14 cm field of view, 3 mm slice thickness,
echo time (TE) ⫽ 15 ms, volume repetition time (TR) ⫽ 4 s, flip
angle ⫽ 35°]. During image acquisition, each spatial frequency grating was presented separately and monocularly at 22% contrast, in
random order, a total of three times, with each presentation lasting 3 s
every 20 s. The remaining 17 s of each trial was a luminance-matched
gray screen. At the end of the experiment, anatomical reference
images were collected using a three-dimensional, T1-weighted
FLASH imaging sequence [256 ⫻ 256 ⫻ 32 matrix, 14 ⫻ 14 ⫻ 4.8
cm field of view, inversion time (TI) ⫽ 0.5 s, TE ⫽ 6.3 ms, TR ⫽ 11.7
ms, flip angle ⫽ 11°]. Before data analysis, all images were motioncorrected using SPM96 (Friston et al. 1995), leaving five slices per
subject for analysis.
Including the setup time of the experiment, imaging time for
anatomical localizer scans, anatomical reference scans, and a short
break between psychophysical and imaging experiments, the total
time to conduct all experiments for each subject was nearly 2 h.
Hence, to relieve subject boredom and reduce subject motion, we used
only five repetitions of the standard frequency within trials of the
psychophysical tasks and three presentations of each spatial frequency
target during imaging.
Data analysis
With the aid of the anatomical reference images, regions of interest
(ROIs) for analysis were selected to include primary visual cortex
(V1) and possibly other early visual areas (V2). All analyses were
performed on an individual subject basis and separately for each eye.
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1. Classification of amblyopia for each subject by
orthoptic assessment
TABLE
Refractive Correction
Subject,
Age (yr),
Sex
Strabismic
Sphere Cylinder Axis, deg Snellen
Deviation
Eye (diopters) (diopters) (rotation) Acuity (Prism Diopters)
Strabismus
DA, 42, M
MA, 56, F
R
L
R
L
⫹0.50
⫹0.00
⫹6.00
⫹5.25
⫹1.00
⫹1.00
⫹0.75
90
97
86
20/20
20/200
20/400
20/30
L.XT., 50
R.XT., 40
Strabismus/Anisometropia
LL, 39, F
CB, 51, F
R
L
R
L
⫹6.00
⫹3.75
⫹2.50
⫹1.50
⫹1.00
⫹2.00
30
180
20/250
20/20
20/125
20/25
R.XT., 30
R.ET., 4
L.XT., left exotropia; R.XT., right exotropia; R.ET., right esotropia.
Using a box-car input correlation function incorporating a temporal
delay to allow for the intrinsic delay of the hemodynamic response,
one functional map of image voxels showing a significant increase
(P ⬍ 0.01) in MR signal above baseline was created for each and
every spatial frequency. These maps were combined as a “logical OR”
to create one map of voxels to be used in further analyses. The average
fMRI response over the three presentations for each spatial frequency
was then computed for each voxel (expressed as a percent increase in
MR signal above baseline).
To estimate the noise in the fMRI signal during visual stimulation,
the magnitude of the MR signal as a function of time (i.e., the MR
time course) for each image voxel within our selected ROIs (all voxels
in the raw image data, not merely the resulting functional map) was
Fourier transformed, multiplied by a high-pass frequency filter, and
inverse-Fourier transformed to regain the MR time course. This
method removed components of the MR signal that were in phase
with the presentation of the visual stimuli (as well as all lower
frequency signals), and maintained the high-frequency noise. The
standard deviation of the magnitude of the MR signal for time points
corresponding to stimulation of the eye was then computed as an
estimate of the noise during stimulation of the eye.
RESULTS
The orthoptic assessment for each subject with amblyopia is
summarized in Table 1. The severity of anisometropic and
strabismic amblyopia varied across subjects, ranging from 4 to
50 prism diopters of strabismic deviation and a 0.25- to 2.25diopter difference in either spherical or cylindrical refractive
correction. Only subjects with a spherical or cylindrical correction ⬎1 were considered anisometropic.
Figure 2 shows each subject’s perception of 22% contrast as
a function of spatial frequency measured with each eye for the
four subjects with unilateral amblyopia as well as the average
perception for the six subjects with normal vision. All subjects
correctly perceived the reference frequency as a 22% contrast
grating (i.e., physical contrast agreed with perceived contrast).
One subject, subject CB, was unable to detect the 12 cpd target
with the amblyopic eye. Thus data for subject CB at this spatial
frequency was not analyzed. The curves in each graph (and in
all subsequent similar graphs) were obtained by fitting the data,
S, to a function of the form
S ⫽ a ␻ b e ⫺c ␻
(1)
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GOODYEAR, NICOLLE, HUMPHREY, AND MENON
FIG. 2. Psychophysical measurements of the perception of 22% contrast as
a function of spatial frequency for 4 subjects with unilateral amblyopia and the
average for 6 subjects with normal vision. Error bars represent SE.
where ␻ is spatial frequency, and a, b, and c ⬎ 0 are fitted
parameters. For all subjects with normal vision and for three of
the four subjects with amblyopia, the perception of contrast
was the same for both eyes. For each of these three amblyopes,
there was little or no difference in the location of the maximum
of the curve fitted to the data for each eye [DA: 2.5 cpd
(preferred eye), 2.1 cpd (amblyopic eye); MA: 2.5, 1.9; CB:
1.8, 1.8]. Subject LL exhibited a decrease in the perception of
contrast measured with the amblyopic eye, and this decrease
was more pronounced at higher spatial frequencies. In this
case, the maximum of the curve fitted to the amblyopic eye
data occurred at 0.8 cpd, and at 2.4 cpd for the preferred eye
data.
Figure 3 shows that the magnitude of the fMRI response as
a function of spatial frequency was the same for each eye for
the subjects with normal vision and for the same three amblyopes that exhibited the same psychophysical response for
each eye. However, the magnitude of the fMRI response to
stimulation of the amblyopic eye for subject LL was smaller at
higher spatial frequencies compared with the fMRI response to
stimulation of the normal eye, in agreement with the psychophysical data.
Figure 4 correlates the results of Figs. 2 and 3 to show that
regardless of spatial frequency the magnitude of the fMRI
response reflects the perception of contrast and is the same for
each eye, even for subject LL. That is, even though the perception of 22% contrast measured with the amblyopic eye of
LL was reduced, the correlation between perceived contrast
and fMRI response was the same as that for the preferred eye.
This remarkable relationship between fMRI response and level
of contrast is consistent with a model that predicts a power
relationship between the two at low contrast levels (Boynton et
al. 1999), i.e., fMRI response ⬀ (perceived contrast)b, where b
is usually ⬎2. For our data, b was 4.54 (R2 ⫽ 0.9).
The threshold contrast of the reference frequency for the
amblyopic eye was elevated for all subjects [DA: 2.4% (amblyopic eye), 1.5% (preferred eye); MA: 2%, 1.2%; CB: 1.9%,
FIG. 3. Functional magnetic resonance imaging (fMRI) response to 22%
physical contrast (expressed as a percentage increase in MR signal above
baseline) of image voxels within early visual areas as a function of spatial
frequency for 4 subjects with unilateral amblyopia and the average for 6
subjects with normal vision. Error bars represent SE.
1.5%; LL: 3%, 2.2%]. Figure 5A shows the perceived contrast
as a function of spatial frequency expressed in multiple units of
the threshold contrast for each eye (i.e., the perceived contrast
divided by threshold contrast), averaged over the four subjects
with amblyopia. Figure 5B shows the number of activated
voxels that were in each of the functional maps created at each
spatial frequency before they were combined. Although Fig. 4
suggests that the magnitude of the fMRI response reflects the
perception of contrast and is not dependent on the presence of
amblyopia, Fig. 5 suggests that the total neural activity within
early visual areas contributing to a detectable fMRI response is
not the same for each eye. The reduction in the number of
activated voxels resulting from amblyopic eye stimulation was
FIG. 4. The fMRI responses of Fig. 3 plotted against the corresponding
psychophysical measurements of the perception of 22% contrast of Fig. 2 for
the 4 subjects with unilateral amblyopia and the average for the 6 subjects with
normal vision. Error bars represent SE.
FMRI
RESPONSE TO CONTRAST IN HUMAN AMBLYOPIA
FIG. 5. A: average psychophysical measurements of the perception of 22%
contrast expressed in multiples of threshold contrast for the 4 subjects with
unilateral amblyopia. B: the average number of voxels within the fMRI maps
as a function of spatial frequency for the 4 subjects with amblyopia (* P ⬍
0.05). Error bars represent SE.
significant (P ⬍ 0.05, paired t-test at each spatial frequency
across subjects) only at higher spatial frequencies, but the trend
is quite clear. In support of the finding that the total neural
signal in early visual areas is smaller during stimulation of the
amblyopic eye than it is during stimulation of the normal eye,
it was found that on average across subjects with amblyopia,
the underlying high-frequency noise in the fMRI signal during
stimulation of the amblyopic eye was 0.20 ⫾ 0.04% (mean ⫾
SE). This did not differ from the noise during stimulation of the
good eye (0.22 ⫾ 0.03%), nor different from the noise during
stimulation of either eye of those subjects with normal vision
(0.19 ⫾ 0.02%).
DISCUSSION
Using brief stimuli (⬍4 s) is key in high spatial resolution
fRMI studies to maintain the spatial specificity of the fMRI
response by preventing saturation of the local hemodynamic
response (Das and Gilbert 1995; Malonek and Grinvald 1996)
and minimizing adaptation effects. We have previously shown
that an unsaturated hemodynamic response is also more likely
to maintain proportionality between neural activity and bloodoxygenation-level– dependent (BOLD) fMRI signal (Menon
and Goodyear 1999). Our findings may not have been possible
using a sustained visual stimulus, as any linearity between
neural activity and fMRI response would have likely been lost.
As well, relatively minor changes in the perceived contrast of
the stimulus would have been masked by the spreading of the
vascular response to areas unassociated with the neural activity.
Previous fMRI analysis techniques for the study of contrast
response include preselecting voxels for analysis on the basis
of functional localizer experiments using high stimulus contrasts (Boynton et al. 1999). This removes any statistical biases
toward any one contrast level by fully saturating the fMRI
response. In our study, however, only 22% physical contrast
was used. We did not use the reference frequency to preselect
voxels for analysis because this would have favored that spatial
frequency. Our approach of creating a statistical map for each
1911
and every spatial frequency and then combining the maps to
create one group of voxels for further analysis removes any
bias toward one spatial frequency.
Of the four subjects shown in Table 1, subject LL demonstrated the most severe case of anisometropia (i.e., the greatest
difference between the eyes in terms of refractive correction).
The reduction in contrast perception for subject LL (Fig. 2) as
measured with the amblyopic eye is consistent with previous
findings (Hess and Pointer 1985) demonstrating that in moderate-to-severe cases of anisometropia, there is an elevation in
the level of contrast at which the performance of the two eyes
equalizes. Hence, our visual stimulus parameters may have
been such that a 22% contrast was not sufficient for subject LL
to overcome the perceptual deficits of the ambylopic eye at low
contrast. This was shown as well in the fMRI response to
stimulation of the amblyopic eye with the same visual targets
(Fig. 3). These data, as well as the data for the other three
amblyopes and for the subjects with normal vision, clearly
demonstrate that fMRI response, and consequently the level of
neural activity, in early visual areas of the visual cortex correlates with the perception of contrast. These results are consistent with previous work showing that the fMRI response
reflects the level of contrast (Goodyear and Menon 1998;
Tootell et al. 1998), and further that the coding of contrast
within monocular neurons is spared in amblyopia (Kiorpes et
al. 1998; Movshon et al. 1987). Of course, the voxels of our
MR images contain many types of neurons, not merely monocular neurons. Hence we cannot claim that the measured
fMRI response is a direct measure of the activity of neurons
that respond preferentially to stimulation of one eye. The exact
contribution of the activity of these types of neurons to the
fMRI signal is difficult to determine given the practical spatial
resolution restrictions of fMRI. Nonetheless, our results show
that magnitude of neural activity per image voxel is not impaired in the presence of amblyopia when contrast is sufficient
to equate the perception of that contrast across the eyes.
Figure 5B illustrates, however, that there is a reduction in the
number of “activated” image voxels in the presence of amblyopia. Because no change in image signal-to-noise is expected
across the eyes during the experiment, the presence of fewer
voxels in our functional maps for stimulation of the amblyopic
eye as a function of spatial frequency cannot be explained as an
imaging artifact. Statistical methods of generating functional
maps depend on signal magnitude and signal variance to determine whether a voxel is significantly “active.” Our analysis
has shown that the underlying high-frequency noise in the
fMRI signal during visual stimulation is unchanged in the
presence of amblyopia, and thus a difference in signal magnitude must be responsible for a difference in the number of
activated voxels. A reduction in the number of voxels in our
functional maps for amblyopic eye stimulation is consistent
with low spatial resolution results obtained from PET (Demer
et al. 1988), SPECT (Kabasakal et al. 1995), and MEG studies
(Anderson et al. 1999), since total (or pooled) activity measured by these methods in the visual cortex would be related to
the product of the magnitude of our fMRI signal change and
the number of voxels in our maps. A reduction in pooled neural
activity within the visual cortex has also been proposed as a
possible mechanism for elevated contrast thresholds in amblyopia (for a review, see Levi 1991). When perceived contrast is
expressed in multiple units of the threshold contrast (Fig. 5A),
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GOODYEAR, NICOLLE, HUMPHREY, AND MENON
our data seem to suggest that the number of detectable voxels
at some statistical threshold using fMRI (Fig. 5B) may be
related to the difference in threshold contrast between the
normal and amblyopic eyes since that difference is signal-tonoise dependent. This is merely suggestive, of course, since
our measurements are made at 22% contrast, not at threshold.
However, we speculate that at all perceptually equivalent contrasts, the relative number of detectable voxels during stimulation of the normal and amblyopic should remain approximately constant. Once the perception of contrast becomes
reduced for the amblyopic eye, the relative number of image
voxels will probably favor normal eye stimulation since we
expect that the magnitude of the fMRI signal will decrease for
the amblyopic eye (as for example, subject LL in Fig. 3) as
contrasts approach threshold. The direct investigation of contrast threshold response versus suprathreshold contrast response using fMRI will require stimuli restricted to the fovea
or to a narrow range of eccentricities since unlike psychophysical judgements of suprathreshold contrast (see for example,
Cannon and Fullenkamp 1988), contrast threshold judgements
are heavily eccentricity dependent (e.g., Robson and Graham
1981; Savoy and McCann 1975).
Further elucidation of the neural substrates governing contrast sensitivity loss in amblyopes must be performed with
detailed retinotopy (Tootell et al. 1998) to examine the contribution of areas outside V1. In addition, fMRI at higher spatial
resolution will allow an evaluation of the response of the ocular
dominance columns (Menon and Goodyear 1999) to stimulation of amblyopic eye. Nonetheless, our current results clearly
demonstrate that fMRI of the visual cortex of amblyopes is
sensitive to the reduction in pooled neural activity in response
to stimulation of the amblyopic eye as a function of spatial
frequency. As well, fMRI is also sensitive to neural populations whose contrast coding seems to be spared at suprathreshold contrast, even in the presence of amblyopia. Although,
based on the results of this study, we cannot specify the neural
mechanisms underlying amblyopia, we have demonstrated that
fMRI is a useful noninvasive tool in the investigation of
amblyopia at the cortical level.
The authors thank Dr. David Heeger at Stanford University for input and
helpful suggestions.
This work was supported by National Eye Institute Grant 1R01EY-11551
and the Medical Research Council (Canada).
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