Color consilience: color through the lens of art practice, history, philosophy, and neuroscience


Ann. N.Y. Acad. Sci. ISSN 0077-8923

A N N A L S O F T H E N E W Y O R K A C A D E M Y O F S C I E N C E S
Issue: The Year in Cognitive Neuroscience

Color consilience: color through the lens of art practice,
history, philosophy, and neuroscience

Bevil R. Conway
Neuroscience Program, Wellesley College, Wellesley, Massachusetts and Department of Neurobiology, Harvard Medical
School, Boston, Massachusetts

Address for correspondence: Dr. Bevil R. Conway, Wellesley College – Neuroscience, 106 Central St., Wellesley, MA 02481.
bconway@wellesley.edu

Paintings can be interpreted as the product of the complex neural machinery that translates physical light signals
into behavior, experience, and emotion. The brain mechanisms responsible for vision and perception have been
sculpted during evolution and further modified by cultural exposure and development. By closely examining artists’
paintings and practices, we can discover hints to how the brain works, and achieve insight into the discoveries and
inventions of artists and their impact on culture. Here, I focus on an integral aspect of color, color contrast, which
poses a challenge for artists: a mark situated on an otherwise blank canvas will appear a different color in the context
of the finished painting. How do artists account for this change in color during the production of a painting? In the
broader context of neural and philosophical considerations of color, I discuss the practices of three modern masters,
Henri Matisse, Paul Cézanne, and Claude Monet, and suggest that the strategies they developed not only capitalized
on the neural mechanisms of color, but also influenced the trajectory of western art history.

Keywords: cones; retina; V4; macaque monkey; Modernism; Matisse; Cézanne; Monet

It is only after years of preparation that the young
artist should touch color—not color used
descriptively, that is, but as a means of personal
expression.1

A great modern attainment is to have found the
secret of expression by color.2

Henri Matisse

Introduction

For Henri Matisse, painting was serious business.
Naturally, he wore a suit to work. Matisse, an icon
of modern art who “everyone agrees deserves the
title of the century’s greatest colorist,”3 lived in the
south of France and often painted with a smock to
protect his formal attire from sticky oil paint. Wear-
ing a smock was an easy decision. But what about the
decisions that followed? As Matisse so bluntly states,
“Anyone who paints has to make choices minute by
minute.”4 Faced with a blank canvas, how did Ma-
tisse decide what marks to apply where and with
what color? And how did these decisions go on to

shape the trajectory of art history? To some extent,
the kind of marks one makes is inevitably deter-
mined by body mechanics: our arms are attached at
a fixed point, the shoulder, and so any attempt at a
straight line invariably results in a gentle curve.5 The
physical structure of our bodies therefore influences
drawing practice—and these influences may extend
to cognitive development, shaping how we think.
Similarly, the way in which our nervous systems en-
code light signals necessarily determines what we
see and how artists paint. An emerging field of re-
search, vision and art, explores the interface between
the neural mechanisms of vision and art.6–10 An ex-
tension of this field, which I take up here, concerns
the interaction between visual processing and art
practice: how do the mechanisms of vision influ-
ence the decisions of the artist at work? And what
do the strategies that artists employ in making their
work tell us about brain function? While the work
and comments of artists are not scientific docu-
ments, with appropriate sensitivity to their limita-
tions, these materials may be useful in informing

doi: 10.1111/j.1749-6632.2012.06470.x
Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences. 1



Color consilience Conway

our understanding of how the brain works. In this
essay, I take up the relationship between painting
and color vision.

People have been experimenting with paints and
pigments for the entire history of human culture,
and have therefore generated a lot of data. But the
richest data has come relatively recently, following
on the heels of the industrial revolution, which fu-
eled the development of synthetic dyes and pigments
and resulted not only in the wide availability of in-
expensive pigments in the latter half of the 19th
century but also in an expansion of the color gamut
available to the artist11–14 (see also Ref. 15). With the
development of synthetic pigments, the use of par-
ticular colors was no longer restricted by the wealth
of the artist or sponsor, who previously could flaunt
their influence by commissioning pictures contain-
ing rare pigments like gold, or better, ultramarine
blue made from rare lapis lazuli rock. By 1830, syn-
thetic pigments were widely available. For example,
manufactured ultramarine was being churned out
by factories across Europe, following the invention
in 1826 of an inexpensive method of production by
Jean Baptiste Guimet in France and, independently,
by Christian Gottlob Gmelin in Germany.11 In the
same way that a technical development, photogra-
phy,a paved the way for one of the most creative
periods of painting in art history, the development
of synthetic pigments foreshadowed an explosion
of possibilities for the use of color. In some sense,
the only limitation on the use of color became our
neural machinery.

From this perspective, paintings can be inter-
preted as the product of our brains, specifically
as the product of all the complex neural circuits
that translate physical light signals into behavior,
experience, and emotion. The neural machinery of
our brains has been sculpted by many influences,
not only during a given individual’s development,
but also during the history of evolution. By closely

a Some argued that photography would herald the end of
painting, which shows how incompetent we can be at pre-
dicting the impact of technology on culture. “From today
painting is dead,” the French painter Paul Delaroche al-
legedly concluded in 1839 in response to the development
of the daguerreotype photographic technique. Although
there is no evidence that Delaroche actually said this, the
sentiment has been repeated periodically ever since the
middle of the 19th century.1

examining artists’ practices and the paintings they
make, scientists and art historians can collaborate to
uncover clues to how the brain works and thereby
gain insight into how the brain has been influenced
by cultural history and, in turn, has shaped that his-
tory. Here, I describe some of the clever strategies
that artists have used to paint in color, and examine
how these strategies exploit and reveal the neural ba-
sis for color. In this essay, I will consider three titans
of color, Paul Cézanne (1839–1906), Claude Monet
(1840–1926), and Henri Matisse (1869–1954). The
work of these artists certainly influenced the direc-
tion of art history. One theory, to which I return in
the last section of this essay, is that the art-historical
significance of these artists’ work derives from the
dynamic interaction between the artist and his work
during its production, an interaction that is con-
strained by neural mechanisms of vision and vi-
sual feedback. To fully understand the influence of
these artists on art history, one may therefore benefit
from knowledge of the neural mechanisms of color,
which may themselves be better understood in light
of art’s historical and philosophical considerations
of color. One might then argue that art practice, art
history, neuroscience, and philosophy have under-
gone a kind of consilience, and are dependent upon
each other for a complete account of color.b

Color in the world and in our heads

There are lively philosophical debates about color,
concerning whether color is determined by some
objective real-world criterion, or rather by the par-
ticularities of the viewer.18 These debates have often
boiled down to the uneasy question “do you see
red like I see red?” Curiously, we rarely ask whether
two people see an object as having the same shape.
One standard account for the specialness of color
rests on the argument that, unlike an object’s shape,
it cannot be determined objectively by a physical
measuring device like a ruler; the measurements of
a penny, for example, reveal it to be round, confirm-

b The term “consilience” was popularized by Wilson,17 and
I use it to point to the productive intersection between arts
and sciences. The various disciplines might not wholly
agree, but it is not necessary that they do. Rather, my
argument is that understanding will come through ap-
preciation of the many facets of color revealed by many
ways of knowing.

2 Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences.

Administrator
Highlight
delete



Conway Color consilience

ing our perception of it as round. But this account is
flawed on two counts: first, we actually can measure
the physical basis for color almost as easily as we can
for shape, by using a spectroradiometer to deter-
mine the relative fraction of different wavelengths
reflected or emitted from a colored object or source.
And second, although we may be able to measure the
diameter of a penny, rarely is the two-dimensional
retinal projection of the penny round; it is almost al-
ways an ellipse. Although the physical basis for both
can be measured just as accurately, the relationship
between these physical stimuli and the perceptions
elicited by them would therefore seem to be as com-
plicated in the case of shape as it is in the case of
color. The question, then, is why our perception of
the shape of the penny is considered universal (“it
is round”), yet its color is up for debate (“do you
see it as orange like I see it?”). I would argue that
the discrepancy between our account of shape and
color reveals something unique about color, but it
is not that shape is physically measurable and color
is not. The discrepancy suggests, instead, that color
carries a qualitatively different behavioral valence
than shape: we care more about the troubling re-
lationship between the physical basis for color and
our experience of it than we do about the relation-
ship between the physics of object shape and our
perception of shape. This special feature of color
may rest on the fact that we come to know color
only through our eyes and not through our mus-
cles and fingertips, which are also used to ascertain
shape. In any event, color’s specialness may account
for the passionate debates that constitute the history
of color vision research and continue to this day.

What is so special about color? Scientific studies
have shown that humans (with normal trichromatic
color) possess extraordinary color detection and
discrimination abilities;19 some claim that “color
is what the eye sees best.”20 So we can conclude
that color is an important part of our visual expe-
rience.21 But for what, exactly, is color important?
Answers often focus on the relevance of color for ob-
ject recognition (the “ripe fruit” argument19,22–24)
and occasionally on the use of color for intraspecific
communication (the “your face is red, you must be
angry” argument25,26). The seemingly unquantifi-
able, qualitative aspect of color that these hypothe-
ses miss is the fact that we like color.27 Color, unlike
other aspects of vision (with the possible exception
of pleasant faces), appears to have a direct impact

on the limbic system. Although emotional reactions
can be elicited from shapes (e.g., the outline of a
snake), these associations are learned and do not
have the same pop-out characteristic of color. Con-
sider a field of 2s in which one “5” is distributed. To
identify this unique character, people will typically
use a time-consuming search strategy, interrogat-
ing each letter (“is this a 5?”). But if the “5” is red
(and the distractor 2s are black), the 5 will pop out
instantly. For this reason, color is considered a “low-
level” or basic visual feature.

Color contributes directly to emotional state,28–31

which may account for why sports teams with red
uniforms win more often.32 Moreover, people who
lose color perception as a result of brain dam-
age become profoundly depressed33 (although it is
obviously unlikely that impaired color is the root
cause of most depression). Evidence in support of
the intimate relationship between color and emo-
tion/reward fell out of a study examining experi-
mental deep-brain stimulation (DBS) for the treat-
ment of intractable depression. Mayberg and her
colleagues found that DBS in humans of a brain
region implicated in depression, Area 25, resulted
in elevations in mood and enhancement of color
perception. Following DBS of Area 25, “all patients
spontaneously reported acute effects including . . .
sharpening of visual details and intensification of
colors in response to electrical stimulation.”34 The
special status of color may underlie our use of color
as a metaphor for emotion and a host of other in-
effable experiences, such as musical timbre (often
called “sound color”).

Although debates rage on in contemporary phi-
losophy, there are some facts concerning color about
which we have consensus. First, with the exception
of imaginary colors, color is dependent on the spec-
tral content (wavelength) of light reaching the eye
from the outside world. But, as we will see, the rela-
tionship between our experience of an object’s color
and this spectrum is not straightforward. While the
color of monochromatic light viewed as a disc sur-
rounded by black (“aperture color”) can be pre-
dicted,c it is difficult, if not impossible, to predict

c White light, when split by a prism, is divided into a series
of monochromatic wavelengths, each of which can be as-
signed a color term, from red, for the longest wavelengths,
to violet, for the shortest wavelengths (ROYGBIV).

Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences. 3



Color consilience Conway

a subject’s perception of a given stimulus given an
objective physical measurement of the stimulus un-
der natural viewing conditions. You might think that
the color of an object could be determined by simply
measuring the relative amount of each wavelength
reflected from the object, but it cannot. Rather, the
color we experience is contingent on the spatial and
temporal context in which a stimulus is viewed, and
these contextual relationships must be computed
by the brain. This leads to a second conclusion of
consensus: that our visual systems are implicated in
encoding color. The responsible neural mechanisms
not only transform light signals into electrical im-
pulses that are the currency of the nervous system,
but also generate spatial and temporal comparisons
of the light signals across the visual scene and in-
tegrate these data with the viewer’s expectations,
shaped by development, experience, and cultural
exposure. In coarse terms, these aspects of the neu-
ral machinery have been referred to as “bottom–
up” and “top–down”; the former term describes the
feed-forward, sequential processing of light signals
along the visual pathway from the retina, through
the thalamus, and up through various visual cortical
regions, and the latter term refers to the influences of
cognition and prior experience on the brain’s calcu-
lation of what color is assigned to the feed-forward
signals.35

The neat division of processing mechanisms into
bottom–up and top–down—a scheme that treats
neural signals like batons passed from one runner
to the next in a relay with a starting gun and a finish
line—is a gross simplification that may turn out to
be frankly wrong. Certainly, the spatial metaphor of
a “line” of discrete “relays” is incorrect. Increasing
evidence shows that brain regions are richly con-
nected by feed-forward and feed-back connections
that are engaged seemingly simultaneously,36–39 so
placing any brain region at a discrete “stage” in the
processing hierarchy is questionable. A more apt
analogy might be one of making soup: visual signals
contribute to the perceptual output of the brain just
as additional ingredients would shape the flavor of
a soup, but their contribution to perception and
behavior is influenced by the previous state of the
brain and how strong the visual signals are in that
context, just as the added flavor of any new ingredi-
ent is influenced by what else is in the soup. At the
risk of pushing the analogy too far, spices would be
the diffuse modulatory inputs, like those that regu-

late attention and wakefulness, which set the tenor
for the whole operation. How bottom–up relays and
top–down feedback, or cortical soup making are ac-
tually implemented in the brain in the service of
color is anything but resolved. But once again there
are areas of consensus, and new research using new
techniques is shedding light on some stubborn ques-
tions, as discussed in the next section.

Neural mechanisms for color

The retina contains three types of cone photorecep-
tor cells that are the first steps in the feed-forward
computation of color (Fig. 1A). These cells do not
encode primary colors, and the brain does not mix
the activity of the cones as a painter might mix pri-
mary paints. Instead, to encode color, our brains
have circuits that compute the relative amount of
each type of cone activity across the visual scene.
This spatial calculation enables the brain to achieve
something called color constancy, the phenomenon
that causes our experience of a given object’s color
to be stable despite changing illumination condi-
tions.27,40–43 Through color constancy, our brains
enable us to see color as part of objects, not con-
tingent on whether we are looking at them under a
blue sky or a cloudy sky. These two different view-
ing conditions would change the physical spectral
signals received by the eye, yet our experience of
the color of an object does not change that much—
fair weather or foul, we consider the apple to be
red. For the mathematically inclined, the problem
of color constancy can be summarized in straight-
forward terms:44 the spectral signals that the eye
receives from an object are the product of two vari-
ables, the spectral content of the illuminantd and the
absorptive property of the object. As organisms that
attained color vision for some selective advantage,
the only thing we really care about is the property
of the object—the ripe apple needs to be seen to be

d The spectral content of the illuminant describes the rela-
tive proportion of wavelengths across the visible spectrum
that comprises an illuminant. A spectroradiometer can be
used to measure the spectral content of the illuminant re-
flected off a standard “white” card. Natural daylight on a
cloudless day has relatively uniform levels of light across
the visible spectrum, and will contain a higher proportion
of short-wavelength light than tungsten light, which has
relatively low amounts of short-wavelength light and a
large proportion of long-wavelength light.

4 Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences.



Conway Color consilience

Figure 1. The first stages in the neural encoding of color. (A)
Cone-absorption spectra of the three classes of cones (L, M, and
S) in the retina. (B) Receptive-field of a double-opponent cell
in primary visual cortex. Top panels show the spatial receptive-
field map generated using sparse noise cone-isolating stimuli
and reverse correlation; difference maps show the “+” maps
subtracted from the “–” maps. The insets give an indication of
the color of each stimulus (although the actual stimuli were pre-
sented on a computer monitor and carefully color calibrated).
Scale of the grid is 0.75◦ of visual angle. The receptive-field center
was excited by an increase in L cone activity (L+) or a decrease
in M activity (M–), and suppressed by a decrease in L (L–) or
an increase in M (M+); the receptive-field surround gave the
opposite pattern of chromatic tuning. The surround but not the
center was modulated by S cones; the S response had the sign
as the response to M cones. The diagram to the right provides a
summary. Adapted from Refs. 50 and 51.

ripe under all viewing conditions for the experience
of color to be evolutionarily advantageous. Because
the spectrum of the various lighting conditions can
vary enormously; the spectrum coming from the
same object under different lighting conditions also
varies tremendously. That the brain extracts a more-
or-less constant color signal bound to objects despite
this changing illumination is a remarkable achieve-
ment, one that even the most advanced cameras can
only approximate.

The three cone types in the retina are called “L,”
“M,” and “S,” because they have peak sensitivities
in the long-, middle-, and short-wavelength regions

of the visible spectrum. Importantly, however, each
cone type has a very broad absorption curve. In the
case of the M and L cones, this means that light
of virtually every wavelength from the shortest (or
bluest) part of the spectrum all the way to the longest
(or reddest) part of the spectrum can be effective at
eliciting responses. The peak of both the M and L
cone types, which historically have been loosely re-
ferred to as the “green” and “red” cones, is actually in
the yellow part of the spectrum. It is sufficient to say
that the rich spectral information hitting the retina
is reduced to three numbers at any given retinal loca-
tion: the amount of activity in the L, M, and S cones.
These three signals are compared by retinal bipolar
cells just one synapse downstream of the cones, in
a process that is thought to involve two channels:
one comparing L and M signals and one compar-
ing S signals to the sum of L + M signals. These
two channels are still referred to as “red-green” and
“blue-yellow,” but these short-hand terms are inac-
curate because the chromatic tuning of the neurons
does not map onto the basic perceptual categories of
red, green, blue, and yellow. The optimal chromatic
stimulus for the “blue–yellow” channel, for exam-
ple, is actually lavender–lime. To date, the neural
basis for the basic perceptual categories is still un-
known,45,46 although there is some evidence that
implicates specialized brain regions downstream of
primary visual cortex in the visual processing hier-
archy, as I will describe at the end of this section.

The cone-comparison signals encoded by the
bipolar cells are converted into a digital signal of
action potentials by the retinal ganglion cells, whose
axons constitute the optic nerve that courses out the
back of the eye and terminates in the lateral genic-
ulate nucleus (LGN) of the thalamus, a structure
composed of layers of neural tissue folding, or “gen-
uflecting,” to form a peanut-sized structure located
deep in the brain—you can almost touch it through
the roof of the very back of your throat. Neurons
of the LGN send their axons to primary visual cor-
tex, the first cortical stage of visual processing, often
called V-1 for short, and paradoxically located at the
very back of your brain, as far away from the eyes
as any part of the brain can be. Curiously, the LGN
receives almost 10 times as many synapses from V-1
as it does from the retina.47 Each one of these feed-
back synapses is wimpy in comparison to the retinal
feed-forward synapses, but one can already begin
to see the limits of the “relay” analogy described

Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences. 5

Administrator
Highlight
,



Color consilience Conway

earlier: feedback begins before retinal signals even
enter the cerebral cortex. The cortex has already
started its soup.

Neurons in the LGN with color-coding properties
were first described over 50 years ago in the macaque
monkey, a creature who has virtually the same cone
types and visual system as humans and has be-
come the standard model of human color vision.
Although LGN cells carry chromatic information,
Hubel and Wiesel showed that the cells have a pecu-
liar response property: they respond well to full-field
colored light, but not to small spots of colored light
on contrasting backgrounds. For example, a “red-
on” cell would respond to full-field red but not to a
red spot on a green background.48 This is puzzling
because it is at odds with what we know about color
perception, namely that the color of full-field color, a
Ganzfeld, is not very salient, while a spot of color on
a contrasting background pops right off the page (or
screen). Evidence for a spatial transformation of the
color signals that could mediate color contrast is first
found in V-1, manifest by a specialized population of
neurons called double-opponent cells.49,50 Double-
opponent cells respond best to color boundaries,
say a red region next to a green region. Each V-1
neuron receives inputs from a restricted patch of
the retina which corresponds to a portion of the vi-
sual field. This small window on the world is called
the cell’s “receptive-field.” An example of a double-
opponent receptive-field is shown in Figure 1B. The
cell derives its name from the fact that it consists of
two kinds of opposition: chromatic and spatial. The
chromatic opponency is manifest by opponent re-
sponses, excitation or suppression, to L and M cones,
whereas the spatial opponency is manifest as oppo-
nent responses to the same cone type in spatially off-
set regions of the receptive-field. The cell shown in
Figure 1B was excited most strongly by a reddish
spot presented on a blue–green background. These
cells encode local cone ratios, and their importance
to color rests on the potential for them to mediate
color constancy: note that the response of the cell is
relatively unperturbed by a full field of light flooding
both the receptive-field center and the receptive-
field surround—any excitation caused by the
stimulus in one receptive-field subregion is coun-
teracted by suppression caused by the stimulus in
the adjacent subregion. One can consider the spec-
tral bias of an illuminant to be a full-field stimulus,
affecting all parts of a scene; double-opponent cells,

which do not react to full-field stimuli, are there-
fore capable of discounting the spectral bias of the
illuminant.

Double-opponent cells represent a small fraction
of the total population of neurons in V-1, which
initially led investigators to miss them and then to
overlook their significance.51 But importance is not
always reflected in numbers: as Richard Gregory
pointed out to me, a vivid chromatic signal was
carried by a small fraction of the total bandwidth
of the analog television signal (analog TV is now
obsolete). The rest of the bandwidth of the analog
signal was devoted to higher spatial resolution of
black-and-white shapes.

Neurons in V-1 besides double-opponent cells
can also carry chromatic information (reviewed in
Ref. 52), although it is less clear whether this in-
formation is used by the brain to encode hue per
se, or rather used in the service of object recog-
nition and motion perception. One can imagine
that there would be a selective advantage for an
ability to identify an object boundary formed by
colored regions without encoding the colors form-
ing the boundary—this ability is required to defeat
camouflage in which the hue of the various regions
comprising the object is actually distracting. Many
neurons in V-1 show responses to colored bound-
aries regardless of the colors forming the bound-
aries, providing a potential neural substrate for this
ability. But very few neurons in V-1 show sharp
color tuning; that is, V-1 cells do not tend to re-
spond exclusively to one color. Even a given double-
opponent cell is not narrowly color-tuned for small
spots presented in the center of the receptive-field.
Instead the response properties of these cells are de-
termined by the cone-contrast of the stimuli, which
does not correlate directly with color perception:
the cell shown in Figure 1B shows L versus M + S
opponency. A stimulus that increases the activity of
the L cones or decreases that of M cones appears red
(bright or dark), whereas a stimulus that decreases
the activity of S cones appears lime green and one
that increases activity of the S cones appears laven-
der. The crescent-shaped receptive-field subregions
of the cell shown in Figure 1B were excited by in-
creases in the activity of M cones and decreases in
that of L cones (both of which appear green), but
also excited by increases in the activity of S cones
(which appears lavender). The take-home message
is that while these cells may contribute to color con-

6 Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences.



Conway Color consilience

trast calculations, clearly they are not by themselves
encoding hue.

The functional properties and organization of the
relatively large region of cortex devoted to vision
outside of V-1 are still very dimly understood in
comparison to our knowledge of V-1.53–57 But broad
consensus among experts is that V-1 is not the only
cortical region involved in processing color: parts of
the second visual area (V-2, immediately adjacent
to V-1), large islands within the inferior temporal
cortex (IT, a large swath of brain buried under the
ears and on the bottom of the brain, which con-
tains classically defined areas V-4, PIT, and poste-
rior TEO), and regions of anterior TE (closer to
the front of the brain) all contain neurons that re-
spond preferentially to colored stimuli (Fig. 2A).
But the first region beyond V-1 in which neurons
with narrow hue tuning have been unequivocally de-
scribed with single-unit recording (the “gold stan-
dard”) is PIT (Figs. 2B and 2C), and these neurons
are densely clustered in millimeter-sized islands of
tissue, dubbed “globs.”53 Experimental estimates of
the fraction of color-tuned neurons within the globs

approach 90%, which represents a remarkable level
of specialization.

As a heuristic, one can consider each of the brain
regions described here—retina, LGN, V-1, V-2, IT,
and TE—to be involved in constructing a distinct
aspect of the color percept.27,52 The three cone types
are the basis for trichromacy; retinal ganglion cells
that respond in an opponent fashion to activation
of different cone classes are the basis for color oppo-
nency; double-opponent neurons in V-1 generate
local color contrast and are the building blocks for
color constancy; glob cells in IT elaborate the per-
ception of hue; and TE integrates color perception
in the context of behavior. Certainly, this sketch is
grossly simplified and likely inaccurate. We will need
to make many more measurements to understand
how the activity of neurons in the various stages
relate to perception, and there will be much work
unpacking how activity within the entire cortical
color circuit influences the processing of incoming
signals. But we are further ahead than we were 50
years ago when many scientists thought color could
be read out directly from the response properties of
LGN cells.

Figure 2. (A) Simple hierarchical, feed-forward model of color processing in the macaque cerebral cortex. Regions of cortex shown
in gray, which increase in spatial scale along the visual-processing hierarchy from primary visual cortex (V1) to TE, are implicated
in color processing. The first region beyond V-1 in which neurons with narrow hue tuning have been unequivocally described with
single-unit recording is PIT, where these neurons are densely clustered in millimeter-sized islands of tissue, dubbed “globs.” Panels
B and C show the color tuning of a typical glob cell. (B) Poststimulus time histograms to an optimally shaped bar of various colors.
Responses were determined to white and black (top two rows in histogram) and various colored versions of the bar that varied in
brightness. Stimulus onset aligned with 0 ms; stimulus duration (step at bottom). Gray scale bar is average number of spikes per
stimulus repeat per bin (1 ms). (C) The color tuning to each of the stimulus sets in polar coordinates. Adapted from Refs. 52 and 53.

Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences. 7



Color consilience Conway

Challenges in painting color

Color poses an enormous challenge for artists be-
cause the way a painted mark will ultimately appear
is unpredictable. It may be this feature of color that
led some artists, like Wassily Kandinsky, to ascribe
mystical power to color. It led me to study the neural
basis of visual perception in search of explanations.
The difficulty of painting in color is juxtaposed with
the relative ease with which novice students can ac-
quire representational drawing skills, as Edwards’
now classic text attests.58 The challenge posed by
painting in color is exacerbated by the fact that we of-
ten conceive of color in simple terms, as a superficial
glazing overlaid on an achromatic world. This mis-
conception is perpetuated by children’s coloring-in
books, which provide black outlines to relay the
“important” information, and give deceptively sim-
ple instructions to select the appropriate color but
to “stay within the lines”; some neuroscientists have
characterized the neural encryption of color in these
terms.59

Curricula at traditional art schools often mirror
this process: students are first taught to draw with
achromatic pencil lines and then, after mastering
black-and-white, to work with paint (as Matisse ad-
vised in the epigram quoted at the beginning of this
essay). Although this approach may make the prob-
lem of representation seemingly tractable, it fosters
a misunderstanding of the mechanics of color. The
apple in the still life may appear red, but the redness,
and our reaction to it, are not attributed solely to
the pigment in the skin of the apple, nor can that
redness be captured entirely (or even adequately) by
matching that pigment with paint. Rather the color
is attributed to an unconscious comparison that the
visual system makes between the color of the apple,
the color of the surrounding regions, and the con-
text in which we see the apple—the very same com-
parisons that form the basis for color constancy.e

e The challenge was articulated by Matisse: “If upon a white
canvas I set down some sensations of blue, of green, of
red, each new stroke diminishes the importance of the
preceding ones. Suppose I have to paint an interior: I have
before me a cupboard; it gives me a sensation of vivid
red, and I put down a red that satisfies me. A relation is
established between this red and the white of the canvas.
Let me put a green near the red, and make the floor yellow;
and again there will be relationships between the green or

For whatever reason, our visual system hides this
computation from our awareness and leaves us only
with an impression that the color is immutable and
attached to the object that is the focus of our at-
tention. The consequence is that when confronted
with a blank sheet of paper and asked to paint—in
color—the apple, we instinctively reach for the tube
of red paint, and pay little attention to the back-
ground and other viewing conditions. Art teachers
find themselves perennially repeating the mantra:
“Don’t forget about the background!” To which the
student retorts: “I’ll get to it when I’m done painting
the apple.” But the application of a background does
not have a neutral effect on the work-in-progress,
and the surprised and disappointed student is sud-
denly grossly displeased with the color of the apple, a
color that was perfectly satisfactory when floating on
the raw white canvas. The experience reinforces the
student’s resistance to painting backgrounds, and
keeps alive the art teacher’s mantra.

What accounts for the sudden decline of the
painting, coincident with work on the background?
The explanation must have something to do with
the fact that the student has an impression in his or
her mind’s eye, a color memory of the object pre-
sumably stored deep in brain area TE, which does
not match the painting in front of him or her. The
dissatisfaction that the student experiences during
this exercise underscores how important context is
to our experience of color,f and how little we ac-
knowledge context in anticipating our experience
of color. In the case of color, the spectral bias of
the illuminant plays a large role in establishing the

yellow and the white of the canvas which satisfy me. But
these different tones mutually weaken one another. It is
necessary that the diverse marks [signes] I use be balanced
so that they do not destroy each other.” (see Ref. 2, p. 40).
f Color is determined by the context in which it appears,
its relationship to the whole, and by the quantity of it
within the picture (although this relationship does not
bear in a straightforward way on the color). These con-
siderations contribute to the “quantity–quality” calcula-
tions described by Bois (1993), and as Bois argues quite
compellingly, “The founding principles of Matisse’s art
proceed from the fact that color relations, which deter-
mine expression, are above all relations between surface
quantities” (see Ref. 3, p. 23). Thus, Bois argues, Matisse’s
drawing is determined by the same principles as his color,
in service of the same goal of personal expression.

8 Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences.



Conway Color consilience

Figure 3. Color interaction depends on immediately adjacent colors. The “X” target in panel A has the same spectral reflectance
in both panels, yet appears a different color because it is placed on a colored background (adapted from Ref. 75). This effect is
demonstrated again in panel C (courtesy of Beau Lotto). Panels B and D show that the color induction effect is obliterated by
insulating the target with an achromatic margin.

context for color judgments, and as described ear-
lier, we are virtually blind to the spectral content
of the illuminant; this blindness is in very effective
service of color constancy. The artist’s frustration is
therefore a direct consequence of the fact that we
evolved to see color, not to paint it. Matisse and
other artists indicate cultural progress in this re-
gard, as Matisse clearly acknowledged, “Each color
in the painting was determined by and dependent
on the others,”60 and as Bois goes on to reinforce,
“Matisse was constantly forced to start from scratch
because each color stroke implied a further disso-
nance, ricochet-like, and necessitated an unsettling
of the picture’s global color harmony.”61

The neglect of context is not unique to percep-
tions of color: the anticipated emotional reaction
we have to a given event is radically impacted by
the context in which the event is experienced, al-
though we rarely pay much attention to these ef-
fects.62 Color, like a mental preview of a future event,
is essentialized, defined by salient aspects and largely
agnostic of context. We define color by its category
(red, orange, yellow, green, and blue), one that may
have behavioral or linguistic relevance. But the con-
text, as the art student’s experience shows, is ignored
despite the fact that context significantly shapes not

only our color experience, but also our emotional
reaction. This complexity makes the task of artists
particularly difficult, for they must uncover the un-
conscious mechanisms that underlie color in order
to be able to paint in color.63

The context dependence of color means that the
colored elements comprising the scene interact; and
the neural basis for these interactions almost cer-
tainly depends to some extent on the calculations
made by double-opponent cells. The interaction of
color constituted the primary focus of the artist and
teacher Josef Albers (1888–1976), whose powerful
images underscored the disjunction between what
we think underlies a color and the role of context.
Figure 3A shows one of Albers’ famous color induc-
tion demonstrations. In this image, Albers is em-
ploying a simple color contrast effect to alter the
appearance of a line by placing the line against dif-
ferent colored backgrounds. The image remains sur-
prising even though we fully understand the power
of color context to shape our color experience. And
all the information in the world is still insufficient to
stave off the question, “But what color is the line in
reality?”—as if our eyes have deceived us on this rare
occasion. Rather than deception, these demonstra-
tions showcase what the visual system is constantly

Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences. 9



Color consilience Conway

doing—and usually to great adaptive effect—by tak-
ing context into account, and then discounting that
very information. Such contrast effects continue to
inspire the development of powerful demonstra-
tions, like Beau Lotto’s cube shown in the Figure 3C.
These contextual interactions continue to be mined
for clues to the operation of the visual system.64–66

Why is it so difficult to learn how to render per-
ceptually accurate color? There are probably several
reasons, but I think the main one has to do with
the fact that the color computation is effortless. The
automatic nature of color leads us to believe that
there is a straightforward relationship between the
physical stimulus (photons off the apple, and paint
in the artist’s case) and the color experience. This is
reflected in the instructions often given to art stu-
dents. Indeed, when I took art courses at university,
this was the instruction I received: identify a patch
of color in the scene, mix it on your palette, and ap-
ply it at the appropriate location on the canvas. The
instruction sounds logical but it is deeply flawed.
One mixes the color on a gray or white palette and
applies the paint to a canvas that is white or gray (at
least to start) yet the color is ultimately viewed in a
colored context. If one were asked to paint Lotto’s
cube, one might logically begin by painting the yel-
low squares with paint that appears yellow on the
raw white canvas, instead of using paint that appears
gray. This false start would influence all subsequent
color decisions, and the outcome would consist of
profoundly distorted color relationships.

Painting color accurately requires access to infor-
mation that is simply not available to our perceptual
apparatus, which may be why paint-by-number kits
are so compelling (Fig. 4). Putting a milky greenish-
brown patch in the sky does not seem like the right
thing to do at the outset of the project, yet some-
how the color is appropriate in the context of the
completed image. Working through the painting
becomes a kind of joke, in which the punch line
(what color the marks appear to have in the finished
picture) is surprising.

Color-master strategies

So how do the painters we think of as masterful col-
orists capture perceptually accurate color relation-
ships, and what do their strategies tell us about how
the nervous system functions? The very category of
“colorist” was generated within modern art tend-
ing toward abstraction. As painters turned from the

Figure 4. Paint-by-number image, partially completed (top
panel), and finished (bottom panel).

strictures of representation that photography had
mastered, they were liberated to focus on color, a
more recondite aspect of perception. Perhaps we can
get some insight into this conjoined project involv-
ing both culture and the nervous system from the
artists’ unfinished works. The left panel of Figure 5
shows a painting that Paul Cézanne was working
on at the time of his death. What is striking about
it is the lack of a defined subject. Unlike the aca-
demic painters of his day, Cézanne does not begin
with a well-resolved preparatory line drawing; in-
stead, he begins the work almost immediately with
intensely colored paint, and continues to develop
the image with patches of color distributed over
the surface of the painting. We can begin to make
out the suggestion of tree trunks, foliage, sky, and
earth—many of the cues to such suggestions are
purely coloristic. Using this approach, Cézanne re-
cruits his visual system as a meter of accurate color.
Importantly, he has given up the natural conviction
that the color of the patch is stable throughout the

10 Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences.



Conway Color consilience

Figure 5. The visual system as feedback device used to paint color: Paul Cézanne (1839–1906; French) Study of trees 1904 Oil on
Canvas; Mont Ste.-Victoire seen from les Lauves [V.798; R.912] 1902–1906.

development of the image. He is able to alter the
color through adjacency, by adapting and modify-
ing the painted context in which a colored patch ap-
pears. Specifically, he alters the colors of his marks by
adding surrounding colors, changing their appear-
ance through changes in context. The approach al-
lows a form of evolution: Cézanne creates a diversity
of marks, and then progressively emphasizes those
that are the most effective—that most accurately
capture his perceptual color experience—and de-
emphasizes those that are least effective, by chang-
ing their context or occasionally covering a patch
with a different color. As the marks on the canvas
suggest, this is a dynamic and unpredictable process
in which the decision of what colored patch to apply
next is largely prescribed by local circumstances—
what mark he makes is determined by what is needed
to compensate for the change in color appearance of
all the marks on the canvas caused by the mark just
made. Although the trajectory of the painting may
be set (a painting of trees), Cézanne does not seem
to be attempting to reproduce a completed picture
he has in his mind’s eye at the outset of the paint-
ing. Rather, the precise combination of colors and
marks he uses is made up on the spot and guided
continually by visual feedback.

Many colorists have worked in a similarly empir-
ical fashion, developing paintings through trial and
error. Perhaps the most famous is Claude Monet, an
exemplar well known to Cézanne, who made paint-
ing au plein air enormously popular in the 19th cen-
tury. This approach to painting supposedly involves
making pictures of scenery outside under natural
light, directly looking at the subject being painted.

On first blush, this appears to be a similar approach
to that used by Cézanne for it would seem to en-
courage direct visual feedback. So I was surprised to
learn that most of Monet’s early finished paintings
were completed in his studio. (This is, incidentally,
a delightful historical example of how the rhetoric
produced around art often precedes the art actually
made that way.) The painting shown in Figure 6,
for example, was begun au plein air, but completed
some months later in his studio, in winter. With-
out a real-life scene immediately before him, Monet
completed the image through many local decisions,
errors, and corrections reflected in the thick layers
of paint of the finished picture. Beginning the image
au plein air honed Monet’s observational skills and
presumably refined his color memory, and it was
this memory that provided stable feedback during
the development of the painting in studio. Paradox-
ically, this feedback might have been more stable
than if the scene lay before him in life because real-
world scenes are constantly changing, the light shift-
ing throughout the day with a time course shorter
than the time required to paint. In his later career,
Monet would shift from canvas to canvas through-
out the day actually painting au plein air before the
same motif, making numerous sets of paintings of
haystacks and cathedrals that document the passage
of time and the changing play of light throughout
the day. As a result of his careful observation, and
the time spent in studio critically assessing the suc-
cess of his attempts, Monet was able to reproduce
color boundaries as they move through shadow in
a way that reflects the cone ratios generated by real
color boundaries moving in and out of shadow. It

Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences. 11



Color consilience Conway

Figure 6. The visual system as feedback device used to paint color: Claude Monet (1840–1926). Femmes au jardin (Women in the
Garden), started spring/summer 1866 open air in Ville-d’Avray, finished the following winter in studio Honfleur. Collection Musée
D’Orsay, Paris (RF2773) Oil on canvas.

is these local cone ratios that are encoded by the
visual system and form the neural building blocks
for color. It remains a testable hypothesis whether
the cone ratios elicited by the color boundaries in
Monet’s paintings are similar to those encoded by
the nervous system, perhaps by double-opponent
cells.

I do not want to suggest that all masters of color
work in the same way. Indeed, Monet’s early prac-
tice is manifestly different than the later methods
of Cézanne, although they lived at more or less the
same time and painted some of the same motifs in
France. In fact, it is the inventiveness of the artist’s

solution to the problem of color that contributes to
the visual interest of their work, and their lessons
for neuroscience. Consider the artist with which we
began, also recognized for his stunning use of color:
Henri Matisse. A striking feature in many of Ma-
tisse’s mature canvases, beginning in early 1904, is
that he leaves portions of the raw canvas untouched.
These white regions typically fall at the interface
between two differently colored marks. Figure 7
shows three examples dating from 1905 to 1948;
the spare use of paint, in contrast to the slathered
thick overlapping marks deployed by Monet, was
a consistent feature of Matisse’s process, one also

12 Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences.

Administrator
Highlight
two

Administrator
Highlight
1912



Conway Color consilience

Figure 7. The use of achromatic borders to separate colored regions in paintings of Henri Matisse. Henri Matisse (1869–1954;
French): Intérieur à Collioure/La sieste (Interior at Collioure/The Siesta), Oil on canvas, 23 1/4;′′ × 28 3/8′′ Private collection, 1905
(left panel). Poissons rouges et sculpture (Goldfish and Sculpture) spring–summer 1912, oil on canvas 45 3/4′′ x 39 1/2′′ Museum
of Modern Art, NY (right panel).

exploited by Cézanne.g Moreover, most of Matisse’s
canvases were signed, confirming for the art market
that Matisse considered them finished works; the
white omissions were clearly intended.

What lay behind Matisse’s intention? A clue is
provided by some classic psychophysical work re-
viewed by Brenner and his colleagues:67 “It is known
that chromatic induction is primarily determined
by the color of directly adjacent surfaces. . .This is
consistent with the idea that information at the bor-
ders is critical in determining the perceived color.”
Chromatic induction is the Yin of the chromatic
contrast Yang: it is the phenomenon whereby a tar-
get that appears an achromatic gray when placed

g The importance of the white unfinished spaces to the
color relationships was quite obvious to Cézanne, as
demonstrated with his exchange with the art dealer and
critic Vollard, as Bois recounts, “What Cézanne said to
Vollard concerning the two small spots on the hands in
his portrait that weren’t yet covered with pigment: ‘Maybe
tomorrow I will be able to find the exact tone to cover up
those spots. Don’t you see, Monsieur Vollard, that if I put
something there by guesswork, I might have to paint the
whole canvas over starting from that point?’ ” Bois goes
on to emphasize that “Matisse was well aware that the ap-
parently ‘unfinished’ quality of Cézanne’s canvasses had
an essential function in their construction.”61

Figure 8. Color induction is eliminated when achromatic
boundaries separate an otherwise achromatic target from the
colored surround. The panel shows induction in the x direc-
tion (red–green) of the cone space of MacLeod and Boynton as
a function of the distance between the border of a target and
the colored surround; similar effects are seen in the y direction
(blue–yellow). Adapted from Ref. 68.

Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences. 13

Administrator
Highlight
A. Color induction demonstration: see text for details
B. Color induction is eliminated when ...



Color consilience Conway

Figure 9. The development of color in the later paintings of Henri Matisse accentuates their inherent flatness. Henri Matisse
(1869–1954; French).

on a white (or black) background will appear col-
ored when surrounded by a color field; the induced
color is the complementary color of the background.
Figure 8A gives an example in which the “gray” cen-
tral disc appears greenish; curiously, the induced
color is often stronger as an afterimage: maintain
your gaze on the black dot in the center of the
disc, then after 10 seconds transfer your gaze to
the black dot to the right. Most observers report
the appearance of a striking red spot that is the af-
terimage to the induced green. Figure 8B, adapted
from an original paper by Ref. 68, shows that the
degree of color induction (indicated along the y-
axis) falls off precipitously if the target is separated
from the surrounding colored field by an achro-
matic margin. I have illustrated this observation us-
ing the powerful Albers and Lotto demonstrations
shown in Figures 3B and D. Given the importance of
these local interactions, it is perhaps not surprising
that Albers always painted his color fields immedi-
ately adjacent to each other. The prediction from
Albers is that color is dependent on neural calcula-
tions that take place over small local spatial scales,
comparable to the spatial scale of double-opponent
receptive-fields, which compare the relative cone
ratio in one part of visual space with the cone
ratio in an immediately adjacent region of visual
space.

Let’s return to Matisse. Whether he was conscious
of it or not, the small achromatic, white gaps left by
Matisse would have insulated the appearance of the

colors against color induction during the develop-
ment of the image. As a result, the marks Matisse
made remain largely the color he chose them to be
at the time he made them. In this way, Matisse was
liberated to use vibrant saturated colors, often right
out of the tube, without the fear that his colors would
become garish from chromatic contrast. The desire
to use saturated colors is pervasive, suggesting deep
roots in our neural hardware. And the consequence
of Matisse’s strategy for protecting against induc-
tion was, I wager in the next section, an important
driving force in the trajectory of art history and the
development of Modernism.

Painting practice, new materials,
and Modernism

Beginning with his fauvist work in the early 1900s
and extending for the rest of his career, Matisse’s
output represents a pinnacle of Modernism and
owes its success in large part to his innovative use
of color.2,69,70 One consequence of Matisse’s ded-
ication to color, in the reading of historians and
theorists of modern art, is the accentuation of the
inherent flatness of a painted surface. Compare
two paintings that bookend Matisse’s long career
(Fig. 9). In the early painting, Matisse seems to
struggle to achieve a representation of perspective
and depth; the colors he uses are subsidiary. In
the later painting, the color is fundamental and
more playful, but the image lacks depth, appear-
ing instead as a decorative wall panel not unlike

14 Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences.

Administrator
Highlight
Left: Small Door of the Old Mill (Petiteporte du viewx moulin), spring-summer 1898, Oil on canvas 18 7/8" x 14 1/8". Private collection.

Right: Plum Blossoms, Green Background (La branche de prunier, fond vert), Vence, villa Le Reve [winter-spring], 1948. Oil on canvas 45 5/8"x 35". Private collection.



Conway Color consilience

Figure 10. The use of achromatic borders to separate colored regions in paintings of Max Beckmann. Max Beckmann (1884–1950;
German): Self portrait in blue jacket 1950, 54 3/4′′ x 36′′ The Saint Lous Art Museum (right panel). Bequest of Morton D. May. Oil
on Canvas Self Portrait in Florence, 1907 (left panel).

a carpet with broad areas of uniform color en-
livened by small graphical marks. Without address-
ing the cultural considerations as to why Matisse
might have sought this flatness, the consensus is
that he achieved it. The development of color in
this later work, as already described for the im-
ages shown in Figure 7, involves a sparing use of
paint that leaves bare portions of the underlying
canvas, particularly at boundaries between colored
regions. As described earlier, this strategy insulates
Matisse’s color choices against color induction dur-
ing the process of painting, so the colors we see in
the final painting are presumably very close to the
colors Matisse decided upon when the picture was
being created. Matisse’s simple strategy of limiting
color induction by leaving white margins around
the colored marks was adopted by many other Mod-
ernists, including Wassily Kandinsky, Milton Avery,
Mark Rothko, and later Frank Stella, whose “pin-
stripe” paintings launched his career in 1959 with
their pulsating whispery white “breathing lines,” the
remnant unpainted white buffers between broadly
painted black stripes (Ref. 71 discussed in Ref. 72).
Others, like Max Beckmann, employed a variant:
the use of heavy black lines (Fig. 10), which serve
the same purpose. Like Matisse, Beckmann began
his career attempting to capture space and depth,

but concluded by painting images whose color and
flatness are central. In these cases, the vivid flat-
ness of the work would seem to be attributed to
an emphasis on color because color is for the most
part a surface property: the surface of the painting
is flat, a fact we come to be aware of through its
color.h Indeed, the neural mechanisms of color are
tied up with the neural mechanisms responsible for
encoding surfaces and textures.73 This attribute of
color may, incidentally, account for the philosophi-
cal claim that color is tied to objects.

Modernism characterizes a broad movement in
thought and culture in Western society that culmi-
nated sometime between the end of the 19th cen-
tury and the middle of the 20th century. It is during
this time that the role of subjective experience in art
making and interpretation becomes significant. The
grand subjects that were often the basis for pictures
made during the Renaissance until the French Rev-
olution, such as history, kings, queens, discoveries,

h Some have argued for a different spatial register to ac-
count for the visual experience of colors deployed in in-
tangible screens, like the sky, a smoky sunset, or a cave
wall indirectly illuminated by a fire; whether these colors
are experienced as surfaces is perhaps debatable.

Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences. 15



Color consilience Conway

and conquests, are rarely the focus of Modernist pic-
tures. (Modernists tended to break with the academy
that persisted with those themes.) Instead, we find
depictions of domestic life, intimate scenes that un-
derscore the interaction of the artist and his subject.
The work showcases the involvement of people with
their new-found self-consciousness. These trends
have been exhaustively described in the extensive
literature on Modernism. Here, I shift focus to ques-
tion the relationships between the artist, her ma-
terials, and her artistic process—which I construe
broadly to include the dynamic interaction between
the artist and her work during its development, an
interaction that is inextricably characterized by the
neural mechanisms of vision and visual feedback.
These relationships evolved during Modernism and
have continued to be a central force in art making
today.

The flatness of Matisse’s work advanced the Mod-
ernist agenda by drawing attention to the material
properties of the work: Matisse’s work proclaims it-
self to be objects made of paint and canvas, rather
than mere depictions of scenes. As Wright sug-
gests, Matisse “is becoming more interested in paint
than in sight.”70 Matisse’s focus on color, and on
the material properties of paintings, set the stage
for high Modernist masters like Mark Rothko and
Barnett Newman, whose mature canvases are en-
tirely abstract, consisting simply of large swaths of
bold uniform color. Matisse’s work is a bridge be-
tween one side “the eye of Impressionism or Neo-
Impressionism, all eager regard, scanning the shift-
ing surfaces of the world, and on the other, the eye of
modernist visuality, absorbed in the formal qualities
of a the painting’s own surface.”70 I argue here, Ma-
tisse’s accomplishment was brought about in part
because of the particularities of his practice, one
aspect of which sought to insulate color from in-
duction. The result of this particular strategy, those
vacant bits of canvas, revealed what the paintings
were made of; and as a consequence, the making
of paintings, rather than their content, took cen-
ter stage. As Elderfield describes it, the “substance
of painting itself came to fulfill the functions that
form and structure had fulfilled earlier”;69 see also
Ref. 74.

Matisse’s paintings are not appreciated as illu-
sions of real space, but rather as objects whose power
to move us, much like the power of color itself, is
difficult to pin down. The power of Matisse’s pic-

tures surely rests on a successful use of color; and
this use of color derives its success in part from the
process Matisse adopted in making the pictures, a
process that was contingent on the particularities of
his practices, and their probing relation to the neu-
ral mechanisms of color. In the case of the example
described here, the decision to leave portions of the
canvas unpainted may be attributed to a practical
desire to mitigate color induction; but the conse-
quence of this decision pulled back the curtain on
the process of art making itself and emphasized the
materials of art, thereby underscoring the subjec-
tive experience of the artist as art maker, actively
engaged in the making of an object.

Matisse’s interest in color propelled his rejection
of tradition, a tradition that aimed not only to rep-
resent objects in space and depth but also to sub-
jugate the materials of painting—brush, paint, and
canvas—to the requirements of mimetic represen-
tation. Matisse’s approach freed painting from this
traditional requirement, and is justly celebrated for
that liberation. The artist makes the painting self-
conscious by underscoring its own making. The
viewer cannot escape appreciating that the paint-
ing is made of paint and canvas: we have direct evi-
dence of these facts, revealed in many of his paintings
by vacant white lines across their surfaces. Thus, it
seems that Matisse’s sensitivity to color and the in-
novative process he developed to make his pictures,
helped to advance one important aspect of the Mod-
ernist agenda: the desire to achieve an accurate rep-
resentation of the artist’s subjective experience of
color.

Acknowledgments

This work was supported by the Radcliffe Insti-
tute for Advanced Study (Harvard University) and
the National Science Foundation. I am grateful to
Caroline Jones, Ann Jones, David Hilbert, Dale
Purves, Alexander Rehding, and an anonymous re-
viewer for helpful discussions and comments on the
manuscript. I thank Rosa Lafer-Sousa for help in
preparing the manuscript.

Conflicts of interest

The author declares no conflicts of interest.

References

1. Wolff, T.F. Drawings of Matisse. N.Y. Christian Science Mon-
itor, 25 March 1985, p. 27.

16 Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences.



Conway Color consilience

2. Flam, J. 1995. Matisse on Art (Revised Edition). Univer-
sity of California Press. Berkeley and Los Angeles, CA:
p. 121.

3. Bois, Y.-A. 1993. Matisse and “Arche Drawing.” In Painting
as Model. MIT Press. Cambridge, MA: p. 61.

4. Flam, J. 1995. Matisse on Art (Revised Edition). University
of California Press. Berkeley and Los Angeles, CA: p. 101.

5. Van Sommers, P. 1984. Drawing and Cognition: Descriptive
and Experimental Studies of Graphic Production Processes.
Cambridge University Press. New York.

6. Cavanagh, P. 2005. The artist as neuroscientist. Nature 434:
301–307.

7. Conway, B.R. & M.S. Livingstone. 2007. Perspectives on
science and art. Curr. Opin. Neurobiol. 17: 476–482.

8. Livingstone, M.S. 2002. Vision and Art: The Biology of Seeing .
Abrams Press. New York.

9. Zeki, S. 1999. Inner Vision: An Exploration of Art and the
Brain. Oxford University Press. New York.

10. Marmor, M.F. & J.G. Ravin. 2009. The Artist’s Eyes: Vision
and the History of Art . Abrams Books. New York.

11. Roy, A., Ed. 1993. Artist’s Pigments: A Handbook of Their
History and Characteristics, Volume 2. National Gallery of
Art. Washington, DC.

12. Feller, R.L., Ed. 1986. Artist’s Pigments: A Handbook of Their
History and Characteristics, Volume 1. National Gallery of
Art. Washington, DC.

13. Fitzhugh, E.W., Ed. 1997. Artists Pigments: A Handbook of
Their History and Characteristics, Volume 3. National Gallery
of Art. Washington, DC.

14. Berrie, B.H., Ed. 2007. Artists’ Pigments: A Handbook of
Their History and Characteristics, Volume 4. National Gallery
of Art Washington, DC.

15. Douma, M. 2011. Pigments through the ages. URL
http://www.webexhibits.org/pigments [accessed on 15 Au-
gust 2011].

16. Crimp, D. 1981. The end of painting. October 16: 69–86.
17. Wilson, E.O. 1998. Consilience: The Unity of Knowledge.

Knopf. New York.
18. Byrne, A. & D.R. Hilbert. 1997. Colors and Reflectances. In

Readings on Color Volume 1: The Philosophy of Color. MIT
Press. Cambridge, MA: pp. 263–288.

19. Gegenfurtner, K.R. & J. Rieger. 2000. Sensory and cognitive
contributions of color to the recognition of natural scenes.
Curr. Biol. 10: 805–808.

20. Chaparro, A., et al. 1993. Colour is what the eye sees best.
Nature 361: 348–350.

21. Hurlbert, A. 1997. Colour vision. Curr. Biol. 7: R400–
402.

22. Dominy, N.J. & P.W. Lucas. 2001. Ecological importance of
trichromatic vision to primates. Nature 410: 363–366.

23. Smith, A.C., et al. 2003. The effect of colour vision status on
the detection and selection of fruits by tamarins (Saguinus
spp.). J. Exp. Biol. 206: 3159–3165.

24. Caine, N.G. & N.I. Mundy. 2000. Demonstration of a forag-
ing advantage for trichromatic marmosets (Callithrix geof-
froyi) dependent on food colour. Proc. R. Soc. Lond. B 267:
439–444.

25. Changizi, M.A., Q. Zhang & S. Shimojo. 2006. Bare skin,
blood and the evolution of primate colour vision. Biol. Lett .
2: 217–221.

26. Fernandez, A.A. & M.R. Morris. 2007. Sexual selection
and trichromatic color vision in primates: statistical sup-
port for the preexisting-bias hypothesis. Am. Nat . 170:
10–20.

27. Conway, B.R. 2009. Color vision, cones, and color-coding
in the cortex. Neuroscientist 15: 274–290.

28. Valdez, P. & A. Mehrabian. 1994. Effects of color on emo-
tions. J. Exp. Psychol. Gen. 123: 394–409.

29. Adams, F. & C. Osgood. 1973. Cross-cultural study of
affective meanings of color. J. Cross. Cult. Psychol. 4:
135–156.

30. Ou, L. et al. 2004. A study of colour emotion and colour
preference. Part I: Colour emotions for single colours. Color
Res. Appl. 29: 232–240.

31. Gao, X., et al. 2007. Analysis of cross-cultural color emotion.
Color Res. Appl. 32: 223–229.

32. Attrill, M.J., et al. 2008. Red shirt colour is associated with
long-term team success in English football. J. Sports Sci. 26:
577–582.

33. Sacks, O. & R. Wasserman. 1987. The case of the colorblind
painter. N.Y. Rev. Books 34: 25–34.

34. Mayberg, H.S., et al. 2005. Deep brain stimulation for
treatment-resistant depression. Neuron 45: 651–660.

35. Gregory, R.L. 1998. Eye and Brain: The Psychology of Seeing .
Oxford University Press. Oxford.

36. Lamme, V.A., H. Super & H. Spekreijse. 1998. Feedforward,
horizontal, and feedback processing in the visual cortex.
Curr. Opin. Neurobiol. 8: 529–535.

37. Hupe, J.M., et al. 1998. Cortical feedback improves discrim-
ination between figure and background by V1, V2 and V3
neurons. Nature 394: 784–787.

38. Angelucci, A., et al. 2002. Circuits for local and global signal
integration in primary visual cortex. J. Neurosci. 22: 8633–
8646.

39. Bullier, J., et al. 2001. The role of feedback connections in
shaping the responses of visual cortical neurons. Prog. Brain
Res. 134: 193–204.

40. Land, E.H. 1977. The retinex theory of color vision. Sci. Am.
237: 108–128.

41. Brainard, D.H. & B.A. Wandell. 1986. Analysis of the retinex
theory of color vision. J. Opt. Soc. Am. A 3: 1651–1661.

42. Kraft, J.M. & D.H. Brainard. 1999. Mechanisms of color
constancy under nearly natural viewing. Proc. Natl. Acad.
Sci. USA 96: 307–312.

43. Hansen, T., S. Walter & K.R. Gegenfurtner. 2007. Effects of
spatial and temporal context on color categories and color
constancy. J. Vis. 7: 1–15.

44. Stockman, A. & D.H. Brainard. 2010. Color vision mech-
anisms. In OSA Handbook of Optics. 3rd ed. M. Bass, Ed.
McGraw-Hill. New York.

45. Valberg, A. 2001. Unique hues: an old problem for a new
generation. Vision Res. 41: 1645–1657.

46. Webster, M.A., et al. 2000. Variations in normal color vision.
II: Unique hues. J. Opt. Soc. Am. A. Opt. Image Sci. Vis. 17:
1545–1555.

47. Briggs, F. & W.M. Usrey. 2010. Corticogeniculate feedback
and visual processing in the primate. J. Physiol. 589: 33–40.

48. Wiesel, T.N. & D.H. Hubel. 1966. Spatial and chromatic
interactions in the lateral geniculate body of the rhesus
monkey. J. Neurophysiol. 29: 1115–1156.

Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences. 17



Color consilience Conway

49. Michael, C.R. 1978. Color vision mechanisms in monkey
striate cortex: dual-opponent cells with concentric receptive
fields. J. Neurophysiol. 41: 572–588.

50. Conway, B.R. 2001. Spatial structure of cone inputs to color
cells in alert macaque primary visual cortex (V-1). J. Neu-
rosci. 21: 2768–2783.

51. Conway, B.R. & M.S. Livingstone. 2006. Spatial and tem-
poral properties of cone signals in alert macaque primary
visual cortex. J. Neurosci. 26: 10826–10846.

52. Conway, B.R., et al. 2010. Advances in color science: from
retina to behavior. J. Neurosci. 30: 14955–14963.

53. Conway, B.R., S. Moeller & D.Y. Tsao. 2007. Specialized
color modules in macaque extrastriate cortex. Neuron 56:
560–573.

54. Conway, B.R. & D.Y. Tsao. 2006. Color architecture in alert
macaque cortex revealed by FMRI. Cereb. Cortex 16: 1604–
1613.

55. Harada, T., et al. 2009. Distribution of colour-selective ac-
tivity in the monkey inferior temporal cortex revealed by
functional magnetic resonance imaging. Eur. J. Neurosci.
30: 1960–1970.

56. Yasuda, M., T. Banno & H. Komatsu. 2010. Color selectivity
of neurons in the posterior inferior temporal cortex of the
macaque monkey. Cereb. Cortex 20: 1630–1646.

57. Tanigawa, H., H.D. Lu & A.W. Roe. 2010. Functional or-
ganization for color and orientation in macaque V4. Nat.
Neurosci. 13: 1542–1548.

58. Edwards, B. 1979. Drawing on the Right Side of the Brain.
Penguin Putnam. New York.

59. Gegenfurtner, K.R. & D.C. Kiper. 2003. Color vision. Annu.
Rev. Neurosci. 26: 181–206.

60. Flam, J. 1995. Matisse on Art (Revised Edition). Univer-
sity of California Press. Berkeley and Los Angeles, CA:
p. 62.

61. Bois, Y.-A. 1993. Matisse and “Arche Drawing.” In Painting
as Model. MIT Press. Cambridge, MA: p. 48.

62. Gilbert, D.T. & T.D. Wilson. 2009. Why the brain talks to
itself: sources of error in emotional prediction. Philos. Trans.
R. Soc. Lond. B Biol. Sci. 364: 1335–1341.

63. Hurlbert, A. 2007. Colour constancy. Curr. Biol. 17: R906–
907.

64. Lotto, R.B. & D. Purves. 2000. An empirical explanation
of color contrast. Proc. Natl. Acad. Sci. USA 97: 12834–
12839.

65. Shevell, S.K. & F.A. Kingdom. 2008. Color in complex
scenes. Annu. Rev. Psychol. 59: 143–166.

66. Purves, D., W.T. Wojtach & R.B. Lotto. 2011. Understanding
vision in wholly empirical terms. Proc. Natl. Acad. Sci. USA
108(Suppl 3): 15588–15595.

67. Brenner, E., et al. 2003. Chromatic induction and the layout
of colours within a complex scene. Vision Res. 43: 1413–
1421.

68. Brenner, E. & F.W. Cornelissen. 1991. Spatial interactions
in color vision depend on distances between boundaries.
Naturwissenschaften 78: 70–73.

69. Elderfield, J. 1979. Describing Matisse. In Henri Matisse: A
Retrospective. J. Elderfield, Ed.: 14. Museum of Modern Art.
New York.

70. Wright, A. 2004. Matisse and the Subject of Modernism.
Princeton University Press. Princeton and Oxford.

71. Genauer, E. 16-artist show is on today at Museum of Mod-
ern Art. New York Herald Tribune, 20 December 1959.

72. Jones, C.A. 1998. Machine in the Studio: Constructing
the Postwar American Artist . University of Chicago Press.
Chicago: pp. 407–408.

73. Lu, H.D. & A.W. Roe. 2008. Functional organization of
color domains in V1 and V2 of macaque monkey revealed
by optical imaging. Cereb. Cortex 18: 516–533.

74. Gowing, L. 1979. Matisse. Oxford University Press. New
York: p. 59.

75. Albers, J. 1975. Interaction of Color Unabridged Text & Se-
lected Plates. Yale University Press. New Haven.

18 Ann. N.Y. Acad. Sci. xxxx (2012) 1–18 c© 2012 New York Academy of Sciences.