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Vol. 96, Issue 9, 5245-5250, April 27, 1999
Neurobiology
Mach bands as empirically derived associations
R. Beau
Lotto,
S. Mark
Williams, and
Dale
Purves*
Department of Neurobiology, Box 3209, Duke University Medical
Center, Durham, NC 27710
Contributed by Dale Purves, February 24, 1999
 |
ABSTRACT |
If Mach bands arise as an empirical consequence of real-world
luminance profiles, several predictions follow. First, the appearance of Mach bands should accord with the appearance of naturally occurring highlights and lowlights. Second, altering the slope of an ambiguous luminance gradient so that it corresponds more closely to gradients that are typically adorned with luminance maxima and minima in the
position of Mach bands should enhance the illusion. Third, altering a
luminance gradient so that it corresponds more closely to gradients
that normally lack luminance maxima and minima in the position of Mach
bands should diminish the salience of the illusion. Fourth, the
perception of Mach bands elicited by the same luminance gradient should
be changed by contextual cues that indicate whether the gradient is
more or less likely to signify a curved or a flat surface. Because each
of these predictions is met, we conclude that Mach bands arise because
the association elicited by the stimulus (the percept) incorporates
these features as a result of past experience.
 |
INTRODUCTION |
Whereas the specific stimulus used to elicit the Mach band
illusion occurs only rarely outside the laboratory, similar luminance gradients generated by curved surfaces typically have photometric highlights and lowlights in the position of the illusory bands (1).
Thus, in considering how luminance gradients induce illusory bands of
lightness and darkness, Mach and others failed to notice that the
perceptual profile of the bands is remarkably similar to the overall
luminance profile of curved surfaces, which are typically adorned by
photometric maxima and minima. This similarity raises the possibility
that luminance gradients induce the perception of Mach bands because
the visual system associates these stimuli with the photometric
highlights and lowlights that often adorn them.
If this idea is correct, then several predictions follow:
(i) a depiction of the natural source of the Mach band
luminance profile (i.e., a linear gradient preceding an attached
shadow) should elicit Mach bands in the position that highlights and
lowlights normally occupy; (ii) the salience of illusory
highlights and lowlights should be enhanced when the stimulus is made
more like gradients normally adorned by highlights and lowlights;
(iii) the salience of the illusion should be diminished when
the stimulus is made more like gradients that typically lack highlights
and lowlights; and (iv) the salience of Mach bands in
response to a given luminance gradient should be changed by ancillary
information that indicates whether the gradient pertains to a curved or
a flat surface.
The present study examines each of these predictions in turn.
 |
METHODS |
Computer Graphics.
The graphical methods used here are the
same as those described in the companion paper (1).
Generation of Luminance Gradients with Different
Characteristics.
The penumbral gradients presented in Fig. 2 were
generated by illuminating one edge of an opaque card with diffuse light
from an extended source (a 75 W halogen lamp) illuminating a white matte cardboard surface. The shape of the light source was controlled by a square occluder placed directly over the lamp, which also was
fitted with a white plastic diffuser; the square aperture could be
rotated through 90°. The images of these gradients were taken with a
Polaroid PDC-2000 digital camera and analyzed as previously described
(1).
Subjects.
The subjects, whose responses are reported in Table
1, were faculty, students, or staff in the Department of Neurobiology at Duke University. All had normal vision, were naive about the purposes of the test or the study more generally, and volunteered their
time (~10 min to have the task explained to them and to report their
perceptions; see legend of Table 1 for details).
 |
RESULTS |
Mach Bands Appear in the Position of Highlights and Lowlights on
Computer-Rendered Objects that Lack These Adornments.
Fig.
1 compares a digital photograph
of a curved real-world surface with a computer-generated version of the
same object. Whereas the luminance gradient across the curved edge of
the cube in the photograph in Fig. 1A is adorned by
a photometrically measurable highlight and lowlight, these features
have been omitted on the gradient across the depicted cube in Fig.
1B. Brightness maxima and minima are nonetheless apparent at
the initiation and termination of the luminance gradient across the
curved surface of the rendered cube. Although the perceived intensity
of the illusory bands is less than the intensity of the real highlights
and lowlights, the brighter Mach band in Fig. 1B falls in
the position of the highlight in Fig. 1A, and the
dark Mach band falls in the position of the lowlight.

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Fig. 1.
Similarity of photometric maxima and minima
generated by a curved surface and illusory Mach bands. (A)
Digital photograph of a real-world cube manifesting a photometric
highlight and lowlight (as indicated in the luminance profile beneath
the photo). (B) A computer-generated image of a similar
object, but lacking the highlight and lowlight. Despite the objective
absence of these adornments, brightness maxima and minima (Mach bands)
are apparent in the positions of their photometric counterparts in
A.
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The Perception of Mach Bands is Enhanced by Luminance
Gradients Typically Adorned with Highlights and Lowlights and Is
Diminished by Those that Lack Them.
The implication of the
preceding section is that Mach bands arise because illusory brightness
maxima and minima are generated by the visual system in the presence of
unusual stimuli that share the features of luminance gradients that are
typically adorned by these bands as photometric realities (e.g.,
Mach's spinning disk, or the linear penumbral gradient in Fig. 3 of
ref. 1). If this interpretation is correct, then observers should
experience a systematic change in the salience of Mach bands as the
luminance profile of a stimulus that normally occurs with highlights
and lowlights (e.g., a profile generated by a curved surface) is
progressively transformed into a profile that ordinarily occurs without
highlights or lowlights (e.g., a shadow penumbra generated by the sun).
Fig. 2 shows a simple method of
testing this prediction. As can be seen in Fig. 2, when a square
occluder is oriented such that one of its sides is aligned parallel to
the edge of the shadow-casting object, prominent Mach bands are
experienced (Fig. 2A). When, however, the occluder
is rotated away from this position, the illusion is diminished, being
least when the diagonal of the occluder is orthogonal to the edge of
the shadow-casting object (Fig. 2B and C).

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Fig. 2.
Salience of Mach bands as a function of the
relative linearity of the luminance gradient stimulus [generated here
by a square occluder interposed between the light source and the
surface on which the shadow is cast, as indicated (Top); see
Methods for details]. (A) Linear luminance
gradient generated when the leading edge of the square occluder
(Top) is oriented parallel to the edge of the shadow-casting
object. (B) Ambiguous gradient created when the occluder is
partially turned. (C) Sigmoidal gradient created when the
occluder is turned 45°. The salience of the Mach band illusion in the
digital photographs of the gradients created in this way
(Middle) is greatest when the penumbral gradient is linear,
and least when it is sigmoidal. (Bottom) The photometric
gradients measured for each of these stimuli. The geometrical rationale
for this demonstration is given in the Appendix.
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|
The basis of the effect experienced in viewing Fig. 2 is that
when an edge of the square occluder is parallel to the shadow-casting edge, the linear luminance gradient produced is similar to the gradient
produced by a convexly curved surface, although lacking the photometric
highlight and lowlight that usually adorn such stimuli. Conversely,
when the occluder is rotated such that one of its corners is directed
towards the axis of the shadow-casting edge, the luminance gradient
produced is similar to the sigmoidal profile of a cast penumbra, which
normally lacks these photometric adornments (Fig. 2 and
Appendix). Indeed, in addition to Mach bands, a curved
surface coming out of the plane of the paper is typically seen in Fig.
2A, but not in Fig. 2B or
C, consistent with the probable sources of these different gradients.
The Perception of Mach Bands Elicited by the Same Luminance
Gradient Is Changed by Altering Information About the Most Probable
Source of the Stimulus.
A final prediction is that the perception
of Mach bands in response to the same luminance gradient should vary as
a function of information in the stimulus that makes it more or less
likely that the gradient represents an object adorned by highlights and lowlights (i.e., information that alters the probability of the source
being a curved or a flat surface). Fig.
3 examines this prediction, using
texture, perspective, and shadowing to enhance the probability that the
source of the gradient in the upper part of the figure is on a curved
surface and that the source of the identical gradient in the lower part
of the scene is the penumbra of a shadow cast on a flat surface. When
the perception of the differently depicted gradient was tested in 23 individuals naive about Mach bands and their possible significance, all
subjects reported that the illusory bands were more salient (by an
average factor of about 3) across the curved surface than across the
same gradient depicted as a shadow penumbra on a flat surface (Table 1).

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Fig. 3.
The perception of Mach bands elicited by a given
gradient is changed by information in the stimulus that alters the
probability of the source being a curved or a flat surface.
(A) Depiction of a luminance gradient in two different
contexts. Using texture, shadow, and perspective, the gradient in the
upper portion of the figure is depicted as arising from a curved
surface; the same gradient in the lower part of the figure is depicted
as the penumbra of a shadow cast on a flat surface. (B)
Diagram indicating location of the gradients tested. As indicated in
Table 1, subjects invariably perceived the Mach bands associated with
the curved surface to be more salient than the bands associated with
the penumbra of the shadow cast on the flat surface.
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 |
DISCUSSION |
In a recent study of simultaneous brightness contrast (2,
3), we concluded that illusions based on the juxtaposition of
contrasting territories are the manifestations of empirically driven
neural associations (percepts) determined by the relative probabilities
of the possible real-world sources of the light returned to the eye
rather than the actual qualities of the object or the properties of the
stimulus per se. The argument for this statistical strategy
of brightness perception is summarized in Fig.
4A. In brief,
the luminance profile in Fig. 4A is a conventional stimulus for eliciting a simultaneous contrast illusion: the gray diamond on the dark square appears lighter than the diamond on the
lighter square, even though the two test diamonds are equiluminant. In
fact, the "scene" in Fig. 4A is profoundly
ambiguous: the luminance profile could be an evenly illuminated card
with different reflectance properties (Fig. 4B) or a card
having the same surface properties but differently illuminated (Fig.
4C) (note that by ambiguity we simply mean a stimulus that
has more than one potential real-world source). We therefore proposed
that the visual system uses past experience to elicit percepts
constructed on the basis of the relative likelihood of the various
sources of the stimulus rather than the objective qualities of the
stimulus or its retinal effects (recall that a common interpretation of
such illusions is that they arise from a direct perception of distorted
lower order computations of local or global contrast engendered by
lateral interactions). Since the profile in Fig. 4A
would only sometimes have represented an evenly illuminated surface
(the only circumstance in which the two equiluminant test patches
would, in reality, have returned the same amount of light to the eye),
the perceptual association elicited by the scene is elaborated
empirically according to the relative probabilities of the continuum of
possible sources underlying the stimulus.

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Fig. 4.
Mach bands explained in the same framework
used to rationalize simultaneous brightness contrast illusions.
(Upper) When two equiluminant patches (the diamonds) are
presented on dark and light backgrounds, respectively, the diamond on
the dark background appears lighter than the diamond on the light
background (A). This standard stimulus for eliciting
illusions of simultaneous brightness contrast is ambiguous: it could
represent an evenly illuminated card with different surface qualities
accounting for the dark and light surrounds of the equiluminant test
diamonds (B), or a card with uniform surface properties,
half of which is shadowed (C) (among other possibilities).
Because the underlying sources of the stimuli in B and
C are different, they will require different visually guided
behaviors: to respond appropriately, the visual system must therefore
determine the significance of the stimulus in A from
the limited information available. Since there is no way to compute the
"right answer" (i.e., the actual source of the stimulus) based on
a logical principle that could be expressed algorithmically, we have
proposed that the visual system generates percepts empirically, the
stimulus in A eliciting an association (the percept)
according to what the stimulus has most often turned out to be.
(Lower) We now propose the same explanation for Mach bands,
which are elicited by luminance gradients rather than luminance
boundaries. Like the stimulus in A, the luminance gradient
in D is ambiguous: as demonstrated in earlier figures, the
profile could be the penumbra of a cast shadow (E) or the
gradient generated by a curved surface (F). The penumbral
gradients of cast shadows lack photometric highlights and lowlights,
whereas the gradients generated by curved surfaces typically have
luminance maxima and minima. We take the Mach bands elicited by the
ambiguous stimulus in D to be an association engendered
empirically by past experience (see text).
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The biological rationale of this strategy is that by triggering
associations weighted in this way by past experience (presumably both
phylogenetic and ontogenetic), ambiguous visual stimuli will always
generate percepts that have the greatest likelihood of representing the
stimulus for what it has most often turned out to be. This empirical
strategy of experiencing visual stimuli allows the observer to produce
an optimal behavioral response to the ambiguous luminance profile in
Fig. 4A, or indeed to any luminance profile.
Our explanation of Mach bands simply carries this theory of vision into
a related domain of brightness perception in which the stimuli are
luminance gradients rather than contrasting territories. For instance,
the luminance gradient in Fig. 4D is, like the stimulus in
Fig. 4A, ambiguous: this standard stimulus for the
Mach band illusion (see Figures 1 and 3 in ref. 1) could represent a shadow cast on a flat surface (Fig. 4E) or a gradient
preceding an attached shadow on a curved surface (Fig. 4E)
(as well as a painted surface, which is the source of the stimulus in
the laboratory). According to our hypothesis, the association elicited
in response to any such gradient is a construct based on the relative
probabilities of the possible real-world sources of the stimulus
(determined by the observer's and the species' past experience with
similar stimuli whose significance will have been ascertained
empirically by whether the ensuing visually guided behavior was
successful). In the case of the stimulus in Fig. 4D, the
features of this linear luminance profile
like the features of Mach's
spinning disk
will often have been adorned by highlights and
lowlights; consequently, the stimulus triggers an association that
incorporates these features according to the relative probability of a
source adorned in this way.
In support of this interpretation, when the stimulus is made more like
an ordinary penumbra (by making the luminance gradient increasingly
sigmoidal), the perception of Mach bands is diminished (see Fig. 2).
This diminishment presumably occurs because the altered stimulus, for
the same statistical reasons, now triggers an association that reflects
the increased likelihood of a source that lacks highlights and
lowlights. Conversely, when a luminance gradient is made more linear,
the Mach-band illusion is enhanced, in this case because the
association induced by the stimulus is now influenced by the greater
probability that a linear gradient will be adorned with a photometric
highlight and lowlight. The ability to alter the salience of Mach bands
elicited by the same luminance gradient through manipulating
information about the provenance of the gradient (see Fig. 3) similarly
supports this interpretation.
Finally, we note that the conventional explanation of Mach bands
as perceptions arising directly from lateral interactions among the
retinal ganglion cells or other lower order visual neurons (see refs. 4
and 5 for extensive reviews) is undermined by the fact that the
perception of the illusory bands is diminished or absent when subjects
view a step change in luminance between two adjacent surfaces (i.e., an
edge) (see, for example, refs. 6 and 7). If reciprocal lateral
interactions were at the root of the illusion, Mach bands should be
most salient when viewing luminance boundaries between two surfaces,
not luminance gradients. In contrast, the concept of Mach bands as the
result of an empirical strategy of vision correctly predicts the
diminished salience of the illusion in response to step gradients
(because such edges are not, in reality, typically adorned by
highlights and lowlights).
Conclusion.
Luminance gradients that elicit the
perception of Mach bands are, by virtue of the physical properties of
reflected light and the prevalence of curved surfaces in the
environment, frequently adorned with photometric highlights and
lowlights, a statistical conjunction that we take to be the source of
this illusion. The facts that support this conclusion are:
(i) stimuli of the sort used by Mach and others to elicit
this illusion in the laboratory are unusual, whereas similar luminance
gradients adorned by highlights and lowlights are commonplace in
natural settings; (ii) the appearance of Mach bands accords
with the appearance of real-world highlights and lowlights;
(iii) the perceptual prominence of Mach bands can be
modulated by altering the configuration of the stimulus gradient to
make the stimulus either more or less consistent with a real-world source that is normally adorned with highlights and lowlights; (iv) the perception of Mach bands elicited by the same
luminance gradient can be altered by contextual information that
indicates whether the gradient lies on a curved or flat surface; and
(v) Mach bands are most strongly perceived in response to
luminance gradients and least prominent at a step edge between two
surfaces. The neuronal basis of the percepts triggered by the luminance gradients we have examined is presumably patterns of synaptic connectivity engendered by both phylogenetic and ontogenetic experience.
The behavior of Mach bands appears in all respects similar to the
genesis of simultaneous brightness contrast illusions (2, 3). In fact,
such distorted percepts of luminance
Mach bands now included
are no
more or less illusory that any other visual percepts, all of which we
take to signify the probabilistic operation of the visual system as it
disambiguates scenes according to a fundamentally empirical strategy.
 |
FOOTNOTES |
*
To whom reprint requests should be addressed. e-mail:
purves{at}neuro.duke.edu.
 |
APPENDIX |
Computation of the Luminance Gradients Associated with the
Penumbras of Shadows in Sunlight.
The amount of light (L) reaching
any point (P) on the surface on which a shadow and its penumbra are
cast can be determined by multiplying the amount of light
(LF) reaching any fully illuminated point by the ratio of
the exposed area of the sun's disk (AV) to the total area
of the disk (AT). Thus,
|
[ 1 ]
|
Determining the solution of Eq. 1
entails two subsidiary problems: (i) finding the length of
line (XV) from the perimeter of the sun's disk to the edge
of the exposed portion to the disk as seen from point P (see Diagram D1)
and (ii) using XV, determining the exposed area
of the sun's disk at P (that is, determining AV).
With respect to determining XV,
|
[ 2 ]
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and
|
[ 3 ]
|
When
|
[ 4 ]
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and
|
[ 5 ]
|
|
[ 6 ]
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and
|
[ 7 ]
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With respect to determining AV,
|
[ 8 ]
|
|
[ 9 ]
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and
|
[ 10 ]
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To shift the integral's starting point to the edge of the sun's
disk rather than the center (see Diagram D1), (X
R) is substituted for X. Thus
|
[ 11 ]
|
|
[ 12 ]
|
and
|
[ 13 ]
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Returning
to Eq. 1, the
luminance profile across a penumbra is calculated by solving
LP for all values of X (the distance across the surface on
which the shadow is cast; see Diagram D1). Note that the total area of
the sun's disk is given by
|
[ 14 ]
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|
[ 15 ]
|
and
|
[ 16 ]
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When the shape of the light source casting a shadow is rectilinear
instead of circular, the determination of XV and
AV differs accordingly.
With respect to determining XV,
|
[ 17 ]
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|
[ 18 ]
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With respect to determining AV,
|
[ 19 ]
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|
[ 20 ]
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and
|
[ 21 ]
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The modified meaning of the terms in these equations are
indicated in Diagram D2. Finally, note that the formula for the total
area of rectangular light source is given by
|
[ 22 ]
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[ 23 ]
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and
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[ 24 ]
|
 |
REFERENCES |
| 1.
|
Lotto, R. B., Williams, S. M. & Purves, D.
(1999)
Proc. Natl. Acad. Sci.
96,
5239-5244
[Abstract/Free Full Text].
|
| 2.
|
Williams, S. M., McCoy, A. N. & Purves, D.
(1998)
Proc. Natl. Acad. Sci.
95,
13296-13300
[Abstract/Free Full Text].
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| 3.
|
Williams, S. M., McCoy, A. N. & Purves, D.
(1998)
Proc. Natl. Acad. Sci.
95,
13301-13306
[Abstract/Free Full Text].
|
| 4.
|
Ratliff, F.
(1965)
Mach Bands: Quantitative Studies on Neural Networks in the Retina
(Holden-Day, San Francisco).
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| 5.
|
Cornsweet, T. N.
(1970)
Visual Perception
(Academic, New York).
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| 6.
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Yellott, J. I.
(1989)
J. Math. Psychol.
33,
1-35
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| 7.
|
Ross, J., Morrone, M. C. & Burr, D. C.
(1989)
Vision Res.
29,
699-715
[Medline]
.
|
Copyright © 1999 by The National Academy of Sciences 0027-8424/99/965245-6$2.00/0

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