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Haptics is now commonly viewed as a perceptual sys-
tem, mediated by two afferent subsystems, cutaneous and
kinesthetic, that most typically involves active manual
exploration (Lederman & Klatzky, 2009). Whereas vi-
sion and audition are recognized for providing highly
precise spatial and temporal information, respectively,
the haptic system is especially effective at processing the
material characteristics of surfaces and objects. Here we
concentrate on the behavioral research that has addressed
the phenomenology and functionality of haptic percep-
tion. This excellent behavioral work stands on its own,
although where directly appropriate we relate it to work in
neuroscience (for more general references, consult, e.g.,
Kandel, Schwartz, & Jessell, 2000; Squire, 2009).
Because this tutorial is necessarily brief, for certain top-
ics we have also chosen to direct the reader to one or more
review chapters or books that offer further detailed discus-
sion and extensive bibliographies containing important
original sources. The tutorial provides a comprehensive
bibliography followed by a list of other suggested review
articles, encyclopedia entries, and books about haptics and
the sense of touch that the reader may wish to consult.
PERIPHERAL SENSORY MECHANISMS
The haptic system uses sensory information derived
from mechanoreceptors and thermoreceptors embedded
in the skin (“cutaneous” inputs) together with mechano-
receptors embedded in muscles, tendons, and joints (“kin-
esthetic” inputs).
Most studies that focus on human sensations involve the
application of various stimuli (hairs, sharp probes, warm
and cool metal tips, etc.) to the skin of a passive observer,
thereby limiting inputs to those of the cutaneous recep-
tors. In his seminal 1962 paper on active touch, J. J. Gib-
son emphasized the polarity of one’s tactual experiences:
Being passively touched tends to focus the observer’s at-
tention on his or her subjective bodily sensations, whereas
contact resulting from active exploration tends to guide
the observer’s attention to properties of the external envi-
ronment. Whereas the results of the passive-touch studies
clearly confirm that cutaneous inputs alone are sufficient
to induce subjective sensations, they fail to recognize the
important role of cutaneous sensing when active explora-
tion is permitted.
Cutaneous receptors are found across the body surface,
beneath both hairy and hairless skin. To date, the majority
of human studies have focused on mechanoreceptors and
thermoreceptors located within the hairless (“glabrous”)
skin of the human hand (Jones & Lederman, 2006). Fig-
ure 1 shows the structure of palmar skin, together with
the specialized nerve endings of the four mechanorecep-
tor populations that human neuroscience has shown are
distributed within this region (see Johansson & Vallbo,
1983). The response characteristics of each population
are differentiated by both the relative size of its receptive
field (small vs. large) and its relative adaptation rate (i.e.,
response to onset/offset of skin deformation vs. continued
response during sustained skin deformation), as outlined
in Table 1A. Table 1B shows the relatively optimal fea-
1439 © 2009 The Psychonomic Society, Inc.
Tu T o r i a l re v i e w
Haptic perception: A tutorial
S. J. le d e r m a n
Queen’s University, Kingston, Ontario, Canada
a n d
r. l. Kl a T z K y
Carnegie Mellon University, Pittsburgh, Pennsylvania
This tutorial focuses on the sense of touch within the context of a fully active human observer. It is intended for
graduate students and researchers outside the discipline who seek an introduction to the rapidly evolving field of
human haptics. The tutorial begins with a review of peripheral sensory receptors in skin, muscles, tendons, and
joints. We then describe an extensive body of research on “what” and “where” channels, the former dealing with
haptic perception of objects, surfaces, and their properties, and the latter with perception of spatial layout on the
skin and in external space relative to the perceiver. We conclude with a brief discussion of other significant issues
in the field, including vision–touch interactions, affective touch, neural plasticity, and applications.
Attention, Perception, & Psychophysics
2009, 71 (7), 1439-1459
doi:10.3758/APP.71.7.1439
S. J. Lederman, susan.lederman@queensu.ca
1440 Le d e r m a n a n d KL a t z K y
topic of debate), the somatosensory system is served by
two subsystems, a “what” system that deals with percep-
tual (and memory) functions, and a “where” system that
deals with the perceptual guidance of action. Evidence that
supports a “what/where” distinction for the somatosensory
system include, for example, f MRI and behavioral studies
by Reed, Klatzky, and Halgren (2005) and by Chan and
Newell (2008), respectively. Reed et al. (2005) showed
that haptic object recognition and object localization ac-
tivated inferior and superior parietal areas, respectively,
suggesting a correlation with the distinction between dor-
sal and ventral visual streams made earlier by Ungerleider
and Mishkin (1982). Chan and Newell showed behavioral
evidence for a task- dependent what/ where distinction that
transcends modalities by using a dual-task paradigm. Si-
multaneous “what” or “where” tasks were found to mutu-
ally interfere more than crossfunction tasks in both in-
tramodal and crossmodal conditions, indicating resource
pools that depended on the task demands but not on the
modality (vision, haptics) used to execute the task. Dijker-
man and De Haan (2007) have comprehensively evaluated
the neural and behavioral literatures for evidence of sepa-
rate processing streams used for somatosensory percep-
tion versus action (“what” vs. “how” systems), as well as
for distinguishing between haptic processing of external
targets and sites on the body. An important issue that arises
from this body of research is whether haptic processing of
shape taps into a visual “what” pathway by invoking vi-
sual imagery, a topic we consider further below.
For purposes of the present tutorial, we will organize
the following discussions of haptic perception in terms of
this functional distinction between “what” and “where”
systems.
The “What” System
The “what” system in touch processes surfaces, objects,
and their many different properties. The efficacy of this
processing pathway is demonstrated by the finding that
familiar objects are recognized quickly and with very high
accuracy by touch alone (Klatzky, Lederman, & Metzger,
1985). The foundation for this ability lies in the sensory
primitives signaled by the peripheral receptors. A broad
spectrum of properties results from further neural pro-
cessing of the receptor signals, with research providing
considerable insight into the computational nature of that
processing.
To begin with, it is useful to divide haptically acces-
sible object properties into two broad classes: material and
geometric. Material properties are defined as those inde-
pendent of the particular object sample being considered;
conversely, geometric properties describe the structure of
that object sample.
Spatial and Temporal Resolving Capacity
of the Skin
Before considering in the next section the haptic per-
ception of object properties, it is important to be aware of
the extent to which the cutaneous system is limited by its
ability to resolve spatial and temporal details presented
ture sensitivity, together with the primary functions with
which each mechanoreceptor population is associated.
The two additional peripheral receptor populations known
as thermoreceptors (Stevens, 1991) respond to increases
or decreases in skin temperature, and mediate the human
experiences of warmth and cold, respectively.
The kinesthetic inputs from mechanoreceptors in mus-
cles, tendons, and joints contribute to the human percep-
tion of limb position and limb movement in space (see re-
views by Gandevia, 1996; J. L. Taylor, 2009). Research in
the motor-control field tends to treat kinesthetic feedback
as sensory signals to be included in models (feedback,
feedforward) of limb movement and grasping. Hence, we
will consider the contributions of kinesthesis and kines-
thetic inputs only where they are inextricably bound up
with human haptic processing and representation—that
is, for purposes of sensing, perceiving, and thinking about
objects, their properties, and the space within which they
reside.
Cutaneous and kinesthetic inputs are combined and
weighted in different ways to serve various haptic func-
tions. In the discussion that follows, we treat complex
human haptic experience as being influenced by a variety
of factors at multiple levels of processing. Accordingly,
it is neither possible nor particularly fruitful to separate
human haptic function into modular compartments as was
once done (e.g., sensations, percepts, and cognitions).
“WHAT” AND “WHERE” TOUCH SYSTEMS
Touch scientists have been recently and vigorously de-
bating whether, like vision (and audition, a more recent
Figure 1. Vertical section through the glabrous skin of the
human hand. Schematic depiction of the two major layers of
the skin (epidermis and dermis), and the underlying subcuta-
neous tissue. The locations of the organized nerve terminals are
also shown. Mr, Meissner corpuscle; Ml, Merkel cell complex;
R, Ruffini ending; P, Pacinian corpuscle. From “Tactile Sensory
Coding in the Glabrous Skin of the Human Hand,” by R. S. Jo-
hansson and A. B. Vallbo, 1983, Trends in Neurosciences, 6, p. 28.
Copyright 1983 by Elsevier. Reprinted with permission.
Ha p t i c pe r c e p t i o n 1441
server to decide whether a linear grating pattern has been
applied “horizontally” or “vertically.” Thresholds obtained
with this more objective measure are typically lower than
the two-point touch threshold (e.g., 1 mm on the finger-
tip, as opposed to 2–4 mm).
When evaluating the point-localization threshold, a
stimulus is presented to the skin, followed in time by a
second stimulus that may or may not be applied to the
same site. Observers are required to say whether the two
stimuli occur at the same or different locations. The point-
localization threshold is consistently lower (i.e., ~1–2 mm
on the fingertip) than the two-point touch threshold. How-
ever, the two measures are highly correlated (Weinstein,
1968), as is evident in Figure 2, which presents both two-
point touch and point-localization thresholds as a function
of body locus for women. Corresponding male thresholds
show similar patterns. Note that tactile spatial acuity var-
ies significantly across the body surface, being highest on
the fingertips and lowest on the back.
to the skin. Under some circumstances, these factors may
potentially constrain haptic perception.
Over the years, a number of psychophysical methods
have been proposed to evaluate the spatial acuity of the
skin. Two classical methods are known as the “two-point
touch threshold” and “point-localization threshold” (see,
e.g., Weinstein, 1968). The two-point touch threshold rep-
resents the smallest spatial separation between two stimuli
applied to the skin that can be detected some arbitrary
percentage of the time (e.g., 75%). Observers are asked
to decide whether they subjectively feel “one” or “two”
points. Although relatively simple to administer, the two-
point touch measure is somewhat limited, in that it not
only requires a subjective response but is also vulnerable
to a number of possible confounds (see, e.g., Johnson &
Phillips, 1981). An extensive research literature on this
topic exists (see, e.g., Jones & Lederman, 2006). A more
objective variant of the classic psychophysical procedure
(Craig, 1999; Johnson & Phillips, 1981) requires the ob-
Table 1A
Response Characteristics of the Four Mechanoreceptor Populations
Size of Receptive Field
Adaptation Rate Small Large
Slow Slow-adapting type I (SA I)
(Merkel)
Slow-adapting type II (SA II)
a
(Ruffini)
Fast Fast-adapting type I (FA I)
(Meissner)
Fast-adapting type II (FA II)
(Pacinian)
Note—The terminal ending associated with each type of tactile nerve fiber is shown
in parentheses.
a
Note that primate research has failed to find evidence for the exis-
tence of SA II units (see, e.g., Johnson, 2001). From Sensation and Perception (2nd
ed., p. 302), by J. M. Wolfe et al., 2008, Sunderland, MA: Sinauer. Copyright 2008 by
Sinauer Associates, Inc. Adapted with permission.
Table 1B
Mechanoreceptors: Feature Sensitivity and Associated Function
Mechanoreceptor
Population
Maximum Feature Sensitivity
Primary Functions
SA I Sustained pressure; maximally sensitive to very low frequencies
(5 Hz) (Johansson, Landström, & Lundström, 1982); spatial de-
formation (Johnson & Lamb, 1981)
Very-low-frequency vibration detection (Löfvenberg
& Johansson, 1984)
Coarse texture perception (D. T. Blake, Hsiao,
& Johnson, 1997)
Pattern/form detection (Johnson & Phillips, 1981)
Stable precision grasp and manipulation (Westling
& Johansson, 1987)
FA I Temporal changes in skin deformation (5 to 40 Hz) (Johansson
et al., 1982); spatial deformation (Johnson & Lamb, 1981)
Low-frequency vibration detection (Löfvenberg &
Johansson, 1984)
Stable precision grasp and manipulation (Westling
& Johansson, 1987)
FA II Temporal changes in skin deformation (40 to 400 Hz)
(Johansson et al., 1982)
High-frequency vibration detection (Löfvenberg &
Johansson, 1984)
Fine texture perception (Bensmaïa & Hollins, 2005)
Stable precision grasp and manipulation (Westling
& Johansson, 1987)
SA II Sustained downward pressure, lateral skin stretch (Knibestöl &
Vallbo, 1970); low dynamic sensitivity
(Johansson et al., 1982)
Direction of object motion and force due to skin
stretch (Olausson, Wessberg, & Kakuda, 2000)
Stable precision grasp and manipulation (Westling
& Johansson, 1987)
Finger position (Edin & Johansson, 1995)
From Sensation and Perception (2nd ed., p. 302), by J. M. Wolfe et al., 2008, Sunderland, MA: Sinauer. Copyright 2008 by Sinauer Associates, Inc.
Adapted with permission.
1442 Le d e r m a n a n d KL a t z K y
the eye’s but better than the ear’s (Sherrick & Cholewiak,
1986).
The temporal resolving capacity of the skin has been
measured in a number of different ways. One common
measure indicates that people can resolve a temporal
gap of 5 msec between successive taps on the skin (Ge-
scheider, 1974). Overall, the temporal resolving power of
the skin is better than that of vision, but worse than that
of audition.
Haptic Perception of Object
and Surface Properties
Principal material properties pertain to surface texture,
compliance, and thermal quality. Geometric properties
generally comprise shape and size. Weight is a hybrid
property reflecting an object’s material (i.e., density)
and its structure (i.e., volume). To be sure, this list of
properties provides a coarse cut across the material and
geometric domains. Perceived surface texture might be
characterized, for example, in terms of its roughness,
stickiness, slipperiness, or friction. Size can be measured
using a number of metrics: total area, volume, perimeter,
bounding- box volume, and so on. Shape is particularly
hard to characterize. As was noted above, psychophysical
and neuroscientific research have deepened our under-
standing of how the perceptual system achieves a repre-
sentation of these properties, given the sensory inputs. We
next describe some of the work in these areas.
Surface texture
. Among the various perceptual prop-
erties that characterize object surfaces, roughness has
undoubtedly received the most attention from haptics re-
searchers. The roughness percept reflects the properties of
the surface touched in interaction with the manner in which
Studies have typically shown a decline in spatial acuity
on the fingertip with increasing age for both sighted and
blind individuals (e.g., Goldreich & Kanics, 2003; Vega-
Bermudez & Johnson, 2004); for a more detailed sum-
mary, see Table 1 in Legge, Madison, Vaughn, Cheong,
and Miller (2008). Studies that have used more recent
psychophysical procedures further reveal that tactile
spatial acuity in blind subjects is typically better than in
sighted subjects who have been matched for age (but see
Grant, Thiagarajah, & Sathian, 2000).
Most recently, however, Legge et al. (2008) used two
newly designed spatial-acuity charts that require active
exploration of Braille-like dot patterns and raised Landolt
rings (Figure 3A). Their results confirmed earlier find-
ings with sighted subjects—namely, a decline in tactile
spatial acuity of almost 1% per year from 12 to 85 years
(e.g., Stevens & Patterson, 1995); in contrast, the blind
showed high tactile spatial acuity that did not decline with
age and that was not limited to the finger used for reading
Braille (Figure 3B). Having discredited peripheral factors,
they attributed this intriguing finding to central changes
arising from the regular use of active touch in daily life.
The broader influences of development, maturation, and
aging on tactile sensing and haptic perception constitute
a fascinating topic for touch scientists (see, e.g., Jones &
Lederman, 2006, chap. 9).
The spatial resolving power of the skin and the influ-
ence of such factors as body locus, age, and visual experi-
ence are relevant to our next topic, the haptic perception
of object and surface properties. As will become evident,
they are also critical to how well people can spatially lo-
calize contacts on the body. Relative to vision and audi-
tion, the spatial resolving power of the skin is poorer than
Mean Threshold (mm)
20
25
30
35
0
5
10
15
40
45
2-point threshold
Point localization
Figure 2. Two-point touch and point localization thresholds are shown for various body sites. Although only the
data for women are presented, the corresponding data for males show close parallels in their general patterns. The
data represent mean threshold values for left and right sides of the body because, with few exceptions, there was no
effect of laterality. Although the point localization thresholds are usually lower than the corresponding two-point
values, the measures are highly correlated. The results indicate that the more distal parts of the body are more
spatially acute. From “Skin and Touch,” by S. J. Lederman, 1991, Encyclopedia of Human Biology, Vol. 7, p. 55.
Copyright 1991 by Academic Press. (Figure adapted from S. Weinstein, 1968.) Reprinted with permission.
Ha p t i c pe r c e p t i o n 1443
ception that predicted perceived roughness of linear grat-
ings from the total area of skin instantaneously deformed
from a resting position while in contact with a surface.
This model used several experimental paradigms to show
that the spatial distribution of the textural elements, rather
than temporal factors, most strongly determined rough-
ness perception. Neither changing hand speed (see also
Meftah, Belingard, & Chapman, 2000) nor preadapting
the surface/object is manually explored. Surface proper-
ties have been extensively studied, and one of the most im-
portant factors found to affect perceived roughness is the
gap between the elements that constitute the surface; the
width of the elements has a smaller effect (M. M. Taylor
& Lederman, 1975). Lederman and Taylor (1972; M. M.
Taylor & Lederman, 1975; see also Lederman, 1974,
1983) developed a mechanical model of roughness per-
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Figure 3. Newly designed dot (A) and ring (B) charts for testing tactile spatial acuity using active touch. Median tactile acuities and
associated error bars indicating the interquartile range for four groups for measurements with dot chart (C) and ring chart (D) in older
and younger blind and sighted subjects. From Legge, Madison, Vaughn, Cheong, and Miller (2008). Copyright 2008 by Psychonomic
Society, Inc.
1444 Le d e r m a n a n d KL a t z K y
Bensmaïa, & Risner, 1998). For the relatively coarse tex-
tures above this point, a spatial model appears to hold.
Johnson and associates modeled roughness perception as
a multistage computation, beginning with a pressure map
on the skin transduced by the SA I slowly adapting mecha-
noreceptors (see, e.g., Johnson & Hsiao, 1994), and pro-
ceeding to sites in somatosensory cortex where inputs are
combined into a measure of spatial variation. In contrast,
the perception of roughness for fine surfaces with spatial
periods of less than ~200 microns appears to be based
on vibratory signals from the Pacinian Corpuscles (PCs).
The importance of vibration at this level is indicated, for
example, by vibrotactile effects of selective adaptation
(Bensmaïa & Hollins, 2003; Hollins, Bensmaïa, & Wash-
burn, 2001), as shown in Figure 4. Bensmaïa and Hollins
(2005) found that direct measures of vibrations in the skin,
as filtered by a PC model, predicted psychophysical dif-
ferentiation of fine textures.
Thermal quality
. The principal thermal property is
the apparent warmth or coolness of a surface under con-
tact, as mediated by the thermal receptors, which respond
within a temperature range of 5º–45ºC. The perceptions
the fingertip to either low- or high-frequency vibrations
of high intensity (Lederman, Loomis, & Williams, 1982)
altered the perceived roughness magnitude. An additional
psychophysical experiment (Lederman, 1974) confirmed
that perceived roughness magnitude was determined
largely by changes in groove width and less by changes
in ridge width, whether or not the corresponding spatial
period was varied. Because isospatial-period gratings pro-
duce the same fundamental temporal periodicity during
contact, provided hand speed is constant, the results of
this study suggest that temporal determinants of perceived
roughness are not involved. A subsequent study by Cascio
and Sathian (2001) qualified these earlier conclusions by
showing that although perceived roughness of gratings is
most strongly determined by the spatial variable, groove
width, the smaller effect of ridge width is indirectly af-
fected by associated changes in temporal frequency.
Subsequent to early work, a “duplex” model of rough-
ness perception was developed, which differentiates be-
tween surfaces at two different scales with spatial periods
above and below ~200 microns (Bensmaïa & Hollins,
2003, 2005; Bensmaïa, Hollins, & Yau, 2005; Hollins,
Proportion Comparison Judged Smoother
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Figure 4. Effect of adapting the index finger to 100-Hz vibration on discriminating fine (A) and coarse (B) surfaces. Proportion of tri-
als on which the comparison surface was judged smoother than the standard surface (40 microns) as a function of log spatial period of
the comparison surface. Note that discrimination in the unadapted state was eliminated for fine surfaces, but was unaffected for coarse
surfaces. From “Vibrotactile Adaptation Impairs Discrimination of Fine, but Not Coarse, Textures,” by M. Hollins, S. J. Bensmaïa, and
S. Washburn, 2001, Somatosensory & Motor Research, 18, p. 259. Copyright 2001 by Informa Healthcare. Reprinted with permission.
Ha p t i c pe r c e p t i o n 1445
difference required to tell materials apart was found to be
43%. A difference less than that value is what makes it
difficult to tell copper from aluminum, whereas a greater
difference makes it easy to tell glass from steel.
Compliance
. The compliance of a touched object refers
to its deformability under force. In a simple 1-D system,
compliance can be expressed by Hooke’s Law, as the rela-
tion of position to force. Srinivasan and LaMotte (1995)
distinguished between objects with compliant versus rigid
surfaces. The former show continuous indentation under
pressure, whereas the latter deform the finger pad up to
some critical point, then compress it. Detailed studies with
robot-controlled force application versus active explora-
tion and use of anesthetized versus normal fingertips have
revealed distinct neural peripheral mechanisms for the two
types of surface. Compliance of continuously deformable
rubber specimens could be discriminated by the spatial
pressure distribution over the contact region, as sensed
by the cutaneous mechanoreceptors. Spring-loaded cells
with rigid surfaces required kinesthetic as well as tactile
cues for the spring constant to be discriminated. Figure 5
presents a schematic representation of the experimental
apparatus.
Weight
. The perceived weight of an object reflects its
density and structure. To some extent, weight can be per-
ceived when an object simply rests on a stationary hand;
however, active exploration—particularly lifting and
wielding the object—substantially enhances the ability to
judge weight (Brodie & Ross, 1984). Amazeen and Tur-
vey (1996) proposed that the perceived weight of an ob-
of warmth and coolness arise from physical interactions
between the skin and touched surface. Ordinarily, the tem-
perature of the skin on the hand is within 25º–36ºC (Ver-
rillo, Bolanowski, Checkosky, & McGlone, 1998). Am-
bient temperatures are generally cooler than this range,
which means that objects in the environment tend to con-
duct heat out of the skin at contact. Ho and Jones (2004,
2006) modeled the process of heat transfer by assuming
that the finger pad and the surface were “semi-infinite”
bodies. Under this model, the skin temperature changes
at contact to an interface temperature determined by the
initial skin and material temperatures and by the material
itself—particularly its thermal conductivity, density, and
specific heat. The difference between the initial skin tem-
perature and the interface temperature—that is, how much
the skin temperature changes at contact—is the essential
signal for apparent temperature. This signal is transmitted
by the thermoreceptor response to higher levels of pro-
cessing that produce the percept of surface coolness (see
also Jones & Ho, 2008).
The importance of thermal quality as an object property
is underscored by the finding that heating various materi-
als so that they are all close to skin temperature, which
eliminates thermal cues, impairs discrimination (Katz,
1925/1989). Materials can be differentiated to some ex-
tent solely by differences in their thermal properties. Berg-
mann Tiest and Kappers (2009) found that differences in
thermal diffusivity—that is, the rate at which a material
conducts heat away upon touch—predicted the ability to
make material discriminations. The minimum diffusivity
AB
Video
Camera
Microscope
Force transducer
Spring-loaded plate
Figure 5. (A) Schematic of the experimental apparatus depicted with one of the transparent rubber stimuli that
varied in compliance. The compliant stimulus was mounted on the spring-loaded plate, which protruded from
a computer-controlled tactile stimulator. The plate contacted a force transducer used to measure contact forces
between finger pad and stimulus under active- or passive-touch modes of stimulation. The contact regions were
videotaped with a dissection microscope that was fitted with a video camera. (B) Schematic of the apparatus used
to present deformable objects with planar rigid surfaces. A spring-loaded cell is shown mounted on the same
spring-loaded plate (left) and in longitudinal section (right). Each stimulus consisted of two telescoping hollow
cylinders with the internal cylinder able to move easily within the external cylinder. Four springs attached to the
base plate of the external cylinder and linked to the internal cylinder determined the compliance of the stimulus.
From “Tactual Discrimination of Softness,” by M. A. Srinivasan and R. H. LaMotte, 1995, Journal of Neurophysi-
ology, 73, p. 90. Copyright 1995 by the American Physiological Society. Reprinted with permission.
1446 Le d e r m a n a n d KL a t z K y
occur with both 2-D and 3-D stimuli and from at least
6 years of age through adulthood, without regard to vi-
sual status (sighted or blind). Gentaz and colleagues have
argued (e.g., Gentaz & Hatwell, 1995) that the haptic
oblique effect is intrinsically dependent on the availability
of kinesthetic gravitational cues produced during manual
exploration by the hand–shoulder system, as well as on
the additional memory constraints that sequential explora-
tion commonly imposes on haptic processing. They sug-
gest that the haptic oblique effect occurs at a relatively
late stage of orientation processing, with the sensorimo-
tor traces converted into a more abstract representation
of spatial orientation. To this end, they suggest that the
observer uses a frame of reference defined by the vertical
and horizontal orientations. Whereas vertical and horizon-
tal orientations can be encoded relative to one of these two
axes, oblique lines must be encoded relative to both, thus
requiring more calculations and possibly explaining, at
least in part, the haptic orientation anisotropy (for further
details, see Gentaz, Baud-Bovy, & Luyat, 2008).
Manual Exploration for Haptic Perception
From the foregoing, it should be clear that haptic per-
ception of surface and object properties is tightly bound
ject wielded in the hand is determined by its resistance to
the rotational forces of the limbs. Their model provides a
physical measure of this property by means of the inertia
tensor, a matrix of the moments and products of inertia.
Because rotational forces are encountered as people lift and
heft objects, these movements provide essential informa-
tion for the judgment of weight. The model predicts that
the distribution of an object’s mass, as well as mass per se,
will be critical to its weight when judged by wielding, in a
manner specified by the changes in the inertia tensor.
A number of illusions related to weight perception
have been demonstrated—for example, thermal/weight
(Stevens, 1979), size/weight (Charpentier, 1891), and
material/ weight (Ellis & Lederman, 1999) illusions, as
well as the “golf-ball” illusion (Ellis & Lederman, 1998),
in which expert but not novice golfers perceive real golf
balls to weigh less than practice golf balls engineered to
be of the same mass. Undoubtedly, these variations in
weight perception reflect a wide variety of mechanisms,
ranging from low-level receptor responses all the way to
high-level cognitive expectations.
Geometric properties
. The size and shape of objects
can be considered on two scales: objects that fit within
the fingertip and thus reveal shape by skin indentation,
and objects with contours that extend beyond fingertip
scale, for which shape perception reflects the contribu-
tion of kinesthetic inputs. Of the various geometric prop-
erties, curvature has received particular attention. When
the finger presses against a curved surface, responses of
slowly adapting mechanoreceptors are directly mapped to
the pressure gradient on the skin (Goodwin, Macefield, &
Bisley, 1997; LaMotte & Srinivasan, 1993; Vierck, 1979).
People can scale local curvature over a large range, from
flat to 107 m
21
; note that the curvature is inversely related
to the radius of curvature (Louw, Kappers, & Koenderink,
2000; Wheat & Goodwin, 2001). Larger curves explored
by touching multiple points, whether statically or dynami-
cally, appear to be judged by the difference in local slope
at different points of contact (Pont, 1997; Pont, Kappers,
& Koenderink, 1999).
The perception of geometric properties beyond fin-
gertip scale is subject to a number of influences that un-
dermine veridicality in systematic ways. For example,
curvature perception depends on whether the curvature is
convex or concave (van der Horst & Kappers, 2008), the
direction of movement over the surface (Davidson, 1972;
Hunter, 1954), the position of the stimulus on the hand
(Pont, Kappers, & Koenderink, 1997, 1998), and on shape
features other than the judged curvature (Vogels, Kap-
pers, & Koenderink, 1999). Haptic perception of linear
extent is affected by the path length, curvature (Sanders
& Kappers, 2008), rate of exploration between endpoints
(Armstrong & Marks, 1999; Lederman, Klatzky, & Bar-
ber, 1985), and other linear elements in the field (Heller
& Joyner, 1993).
Orientation
. In keeping with vision, both vertical
and horizontal lines are haptically perceived better than
oblique lines (Lechelt, Eliuk, & Tanne, 1976; Lechelt &
Verenka, 1980). Known as the oblique effect, the haptic
version of this spatial anisotropy has been observed to
Lateral Motion
(Texture)
Unsupported Holding
(Weight)
Pressure
(Hardness)
Enclosure
(Global Shape)
(Volume)
Static Contact
(Temperature)
Contour Following
(Global Shape)
(Exact Shape)
Figure 6. Depictions of six manual “exploratory procedures”
and their associated object properties (in parentheses). From
“Hand Movements: A Window Into Haptic Object Recogni-
tion,” by S. J. Lederman and R. L. Klatzky, 1987, Cognitive Psy-
chology, 19, p. 346. Copyright 1987 by Elsevier. Reprinted with
permission.
Ha p t i c pe r c e p t i o n 1447
asked to verify whether a property described an object,
their initial response tendency was to grasp and lift. Only
subsequently did they use other EPs directed at the inter-
rogated property.
Haptic Perception of Multiattribute Objects
We turn now to everyday objects, which tend to have
multiple attributes such as weight, compliance, and shape.
Klatzky and Lederman (2007) have argued that traditional
models of visual object recognition (e.g., Biederman,
1987; Marr, 1982) are inappropriate for haptics because
they generally emphasize the importance of spatially
aligned edges, which the haptic system extracts poorly
because of its relatively low spatial acuity (Weinstein,
1968). To establish fundamental principles of haptic ob-
ject processing, it is instructive to consider the voluntary
execution of haptic exploratory procedures, each associ-
ated with specific costs and benefits. As outlined next,
two fundamental principles with respect to haptic process-
ing and representation become evident.
When manual exploration of unfamiliar objects is
temporally unconstrained, material properties are
more perceptually salient than geometric properties
.
When the properties of objects are matched for percep-
tual discriminability, observers judging interobject simi-
larity attend to material properties (texture, compliance,
thermal, and weight) more when objects are encoded
by touch alone than when objects are seen while being
touched. Conversely, they weight geometric properties
(2-D and 3-D shape and size) more when examining the
same objects with vision present than by touch alone (e.g.,
Klatzky, Lederman, & Reed, 1987; Lederman, Summers,
& Klatzky, 1996). The greater salience of material prop-
erties under haptic exploration presumably reflects the
findings that a greater number of EPs convey information
about material than geometry, and that EPs optimized for
encoding material (cf. geometry) tend to be relatively pre-
cise and quick to execute.
Simultaneous execution of two or more explor-
atory procedures allows perceivers to integrate re-
dundant properties about the identity of multiattri-
bute objects
. For example, Klatzky et al. (1987; see also
Lederman et al., 1996) showed that object classification
was faster when each object class was defined by redun-
dant information along two object dimensions. The “re-
dundancy gain” was shown to be governed by two factors:
the extent to which single EPs deliver information about
multiple object properties, and the potential of EPs to be
coexecuted.
Relative contributions of spatial and temporal in-
formation in haptic object processing
. The informa-
tion used to recognize objects arises at different points
during the time course of manual exploration and has
multiple spatial components. It is possible to assess the
relative contribution of different spatial and temporal cues
by constraining haptic exploration, thereby eliminating
certain information sources. The resulting decrement in
performance signals the contribution of the missing infor-
mation. In this section, we consider three examples of this
restricted-exploration approach.
to the nature of contact (i.e., whether an object is pressed
against the finger or explored over time, and how it is ex-
plored). Lederman and Klatzky (1987) have described a
systematic relationship between exploration and object
properties in the form of a set of exploratory procedures
(EPs), of which the most intensively investigated are
depicted in Figure 6. An EP is a stereotyped pattern of
manual exploration observed when people are asked to
learn about a particular object property during voluntary
manual exploration without vision—and sometimes when
vision is present.
For example, the EP associated with queries about ap-
parent warmth or coolness is “static contact,” which in-
volves placing a large skin surface against an object with-
out motion. Other EPs that have received most attention in
the haptic research literature include “pressure” (associ-
ated with compliance), “unsupported holding” (weight),
“enclosure” (volume; coarse shape), “lateral motion”
(texture), and “contour following” (precise shape). The
EP associated with a property during free exploration is
also found to be optimal, in that it provides the most pre-
cise discrimination along the given dimension.
Exploratory procedures can be characterized not only
by their stereotyped motor actions, but also by what those
actions accomplish at neural and computational levels. In
general, the EP associated with a property tends to op-
timize the activation of a set of associated neural recep-
tors, thereby facilitating the computational mechanisms
invoked by those receptors. For an example of this mar-
riage among EP, neural output, and computation, consider
roughness perception. The lateral motion EP, which moves
the skin tangentially across a surface, enhances the re-
sponses of SA I mechanoreceptors (Johnson & Lamb,
1981) and creates deep vibrations that activate the PCs
(Bensmaïa & Hollins, 2003). These two neural systems
are thought to provide the input into the computation of
perceived roughness at the macro- and microscale, respec-
tively (Bensmaïa & Hollins, 2005; D. T. Blake, Hsaio, &
Johnson, 1997).
Costs and Benefits of Exploratory Procedures
The various EPs have different costs and benefits
(Klatzky & Lederman, 1993; Lederman & Klatzky, 1987).
An EP has costs in terms of its execution time and its in-
terference with other patterns of exploration that might
occur at the same time; it has benefits if it provides inci-
dental pickup of object properties for which it is not op-
timal. For example, the benefits of static contact are that
it is quick to execute; it provides incidental information
about texture, volume, and shape, as well as temperature;
and it co-occurs with unsupported holding and enclosure.
On the cost side, static contact cannot be coexecuted with
dynamic EPs such as lateral motion or contour following.
An overall analysis of EP costs and benefits led Leder-
man and Klatzky (1990) to predict that the most efficient
way to process an object’s properties was to grasp and
lift it, thus instantiating the EPs of static contact, unsup-
ported holding, and enclosure. This action would suffice
to provide at least coarse information about material and
structural properties. As predicted, when subjects were
1448 Le d e r m a n a n d KL a t z K y
Moreover, as shown in Figure 7, the greater the number of
end-effector constraints, the more performance declined.
Contribution of extended exploration assessed by
restricting contact duration
. We have just described
some of the significant ways in which restricting the
nature and amount of spatial information, both cutane-
ous and kinesthetic, can impair haptic object processing.
Limiting the duration of manual exploration has its own
important consequences, particularly because material
properties are available for haptic processing earlier than
geometric ones are. In a series of experiments that em-
ployed a tactual version of the visual search paradigm
used by Treisman and colleagues (e.g., Treisman & Ge-
lade, 1980), Lederman and Klatzky (1997) showed that
when delivered to the static fingers of both hands, material
features (rough vs. smooth, soft vs. hard, cool vs. warm)
and edges (present vs. absent) are all available for further
processing relatively earlier than geometric information
(e.g., bar orientation, curvature, 3-D slant, relative posi-
tion), as indicated by the essentially flat search functions
(response time as a function of number of items in the
display). Similar “pop-out” effects for texture have since
been confirmed using active touch (Plaisier, Bergmann
Tiest, & Kappers, 2008). In addition, Overvliet, Smeets,
and Brenner (2007) have presented an elegant model of
haptic search that successfully predicts serial search for
geometric features (shape, i.e., cross target vs. circle dis-
tractors; orientation, i.e., vertical target vs. horizontal dis-
tractors) and parallel processing for the simple detection
of a line target versus blank distractors.
Other research (Klatzky & Lederman, 1995) suggests
that a brief “haptic glance” lasting about 200 msec is
sometimes sufficient for haptic identification of familiar
objects with highly diagnostic features, whether they are
geometric (local shape) or material. Finally, the duration
of manual exploration has been shown to influence hap-
tic processing in terms of the distinction between featural
and global processing of object structure. When haptically
evaluating the relative similarity of pairs of geometric ob-
jects fairly alike in their global shape, observers initially
focus more on local shape features than on global struc-
ture; with continued manual exploration, however, observ-
ers focus more on the global shape at the expense of the
local features. No such switch in focus occurs for objects
dissimilar in their global shapes and without notable local
features (Lakatos & Marks, 1999, as depicted in Figure 8;
see also Berger & Hatwell, 1993).
The “Where” System and
Haptic Space Perception
Like its counterpart in vision, the “where” system for
touch provides a description of the layout of points, sur-
faces, and objects in the world. Touch differs from vision,
however, in that localization can be referred to the sen-
sory organ itself—the skin—as well as to the environ-
ment. Therefore, we consider two types of haptic spatial
localization—determining where on the body a stimulus
is being applied, and determining where in the space ex-
ternal to the body a stimulus is being touched.
Contributions of cutaneous array sensing assessed
by eliminating spatially distributed force feedback
.
What happens when the spatially distributed deformation
patterns normally available to fingertip receptors are elim-
inated? This commonly occurs, for example, when people
use an intermediate tool (e.g., a pencil) to explore an ob-
ject. In this case, haptic perception is considered remote
or indirect, and the skin receives most of its information in
the form of vibrations. In one study that modeled this situ-
ation (Lederman & Klatzky, 1999), observers performed
a battery of simple sensory tests and more complex per-
ceptual tests with and without a rigid finger sheath that
covered the palmar surface of the index finger from the
extreme tip to the most distal finger joint. Not surpris-
ingly, while using the rigid sheath participants showed no
deficit when detecting vibrations. They were moderately
successful at perceptually differentiating roughness. In
marked contrast, they could not resolve the orientation of
raised bars delivered to the fingertip, and were less suc-
cessful locating the presence of a 3-D artificial “lump”
embedded in artificial “tissue.”
Contributions of kinesthetic feedback assessed by
spatial constraints
. Researchers have also investigated
the consequences of depriving observers of normally
available kinesthetic spatial cues that extend beyond the
size of the fingertip (Klatzky, Loomis, Lederman, Wake,
& Fujita, 1993; Lederman & Klatzky, 2004). Observers
were confined to using one finger rather than five, rigidly
splinted finger(s), fingertip(s) covered with a thick but
compliant material, and/or a rigid probe or finger cover.
These constraints mainly differed in the extent to which
the observer was capable of properly tracing the object’s
contours with a contour-following EP and/or in molding
the fingers to the contours with an enclosure EP. The vari-
ous constraints impaired haptic object recognition to dif-
fering degrees in terms of accuracy and/or response time.
20
40
60
80
100
020406080100
Response Time (sec)
Accuracy (%)
1, 3
0
0
0
2
3
2, 3
1
1, 2, 3
1, 4
1, 5
1, 5
0–Unconstrained
1–Reduced # end effectors
2–Compliant covering
3–Rigid finger splinting
4–Rigid finger sheath
5–Rigid probe
Figure 7. Recognition accuracy (%) as a function of response
time (sec) for different constraint conditions involving manual
exploration, alone and in various combinations. The constraint
conditions are shown both by name and by corresponding num-
ber in the legend. The data are derived from experimental condi-
tions in Klatzky, Loomis, Lederman, Wake, and Fujita (1993) and
Lederman and Klatzky (2004). The comma indicates multiple
simultaneous constraints. Copyright 2004 by the Psychonomic
Society, Inc.
Ha p t i c pe r c e p t i o n 1449
Spatial resolving capacity of the skin
. The precision
with which humans can localize bodily contact is first and
foremost affected by the spatial resolving capacity of the
skin, which in turn is influenced by various factors, in-
cluding body site, age, and visual experience. The reader
should refer back to the previous section (The “What”
System), where we address this topic in some detail.
Spatial mislocalizations on the skin
. Research has
shown that space–time interactions produce systematic
mislocalizations of the location of body contact. Like
both vision and audition, touch is also subject to the well-
known “tau” illusion in which the apparent distance sepa-
rating three equally spaced contacts delivered sequentially
to the forearm depends on the intervening temporal in-
tervals (Helson & King, 1931). If the temporal interval
between the first and second contacts is shorter (longer)
than that between the second and third contacts, the cor-
responding distance on the forearm between the first two
contacts is perceived to be shorter (longer) than between
the second and third contacts.
A second example in which bodily contact is mislo-
calized relates to illusory movement known as phi (or
more accurately, beta) movement. This form of apparent
motion is most familiar in the vision literature, and is
easily produced by showing two spatially separated lights
that flash on and off in succession. Observers perceive a
single light moving smoothly between the two stimulus
positions when the complex spatial and temporal interac-
tions follow Korte’s laws (see Boring, 1942). The best
stimulus for creating a tactile variant of smooth apparent
motion on the skin is one that is periodic—for example,
producing vibrotactile bursts of 150 Hz (Sherrick & Rog-
ers, 1966).
Yet another form of mislocalization is known as sensory
saltation, or more familiarly, the “rabbit” illusion (e.g.,
Flach & Haggard, 2006; Geldard & Sherrick, 1972). For
example, consider a series of 15 brief taps delivered in
equal temporal succession to 3 contactor sites equally
spaced along the forearm. Five taps are delivered to the
1st contactor site, followed by 5 to the 2nd contactor site,
and finally 5 more to the 3rd contactor site. Observers
report an illusory sweeping movement of discrete taps that
occur in a linear sequence along the forearm at the real
contactor sites and at illusory ones in between. Some have
likened their impressions to the feeling of a tiny rabbit
hopping up the arm. Although initially discovered on the
skin, this form of spatial mislocalization has since been
documented in a number of the other sensory systems—
visual, auditory, and even thermal systems (Geldard,
1975; Trojan et al., 2006). Goldreich (2007) has offered a
Bayesian account of the cutaneous rabbit, as well as other
spatiotemporal tactile illusions. Neural concomitants of
the effect have been shown to occur in primary soma-
tosensory cortex (Blankenburg, Ruff, Deichmann, Rees,
& Driver, 2006).
Failing to detect changes in spatial pattern on
the skin
. There is now a substantial literature docu-
menting change blindness, a striking inability to detect
large changes to a visual or auditory scene (vision—e.g.,
Frames of Reference for
Haptic Spatial Localization
Considering touch as a system for spatial localization
immediately raises a fundamental question: What is the
frame of reference within which localization occurs? In
general, a frame of reference defines a coordinate sys-
tem, or a set of parameters, for localizing points (Klatzky,
1998). The coordinate system may be Cartesian or polar,
and its origin may be the perceiver’s body or some body
part, or defined in terms of landmarks external to the indi-
vidual. Multiple frames of reference are generally simul-
taneously available, and performance of a given task may
use a single frame or take into account multiple frames.
Both types of spatial processing mentioned above, deter-
mining the site on the body contacted and localizing within
external space, are grounded in contact between the skin
and an external object; however, the frames of reference
are obviously different. Localizing points on the body uses
a local frame of reference, such as the axes of the fingertip.
Haptic localization of points in external space often refers
to an “egocentric” frame of reference, where distances and
directions are specified relative to the actor; the origin of
this frame is called the egocenter. In contrast, a reference
frame parameterized by landmarks and axes external to the
observer is called an “allocentric” frame.
Bodily Localization
A significant issue for touch science involves under-
standing how people localize discrete contacts on their
own bodies: Where was I touched? Research has shown
that localizing the sites of body contact is affected by a
number of factors, among them the following.
Judged Dissimilarity (0−1 Scale)
.3
.4
.5
.6
.7
048121620
Exploration Time (sec)
Dissimilar global shape,
no distinctive local features
Similar global shape,
distinctive local features
Figure 8. Rated dissimilarity values (6standard error) as a
function of exploration duration (sec) for two sets of stimuli: ob-
ject pairs differing in their global features and with no distinctive
local features (open circles), and object pairs with similar global
shape and distinctive local features (filled circles). Copyright 1999
by the Psychonomic Society, Inc.
1450 Le d e r m a n a n d KL a t z K y
consider where objects are in egocentric space (i.e., rela-
tive to the body), we invoke the concept of an egocenter,
a point on or within the body that serves as the origin for
the operative reference frame. In vision, the egocenter has
been localized between the eyes (Howard & Templeton,
1966). In touch, the frame of reference has been found to
vary with the task and with the posture of the individual
who is performing it. Shimono, Higashiyama, and Tam
(2001) tested for the egocenter by asking people to align
a set of objects at different distances from their bodies so
that they pointed to themselves (see Figure 9). Different
angles of alignment were employed, and the point of inter-
section was used to determine the convergent egocenter.
The location of the convergence was not fixed, but rather
depended on both the object distance and the hand used to
perform the manual adjustments. Such variability of the
haptic egocenter has been broadly demonstrated.
In addition to the multiplicity of egocentric reference
frames that can be tapped, haptic spatial localization may
use allocentric frames, and here too there are multiple
candidates. Observers may localize objects relative to in-
trinsic environmental axes (e.g., the edge of a tabletop),
or they may use a subset of objects to define a frame for
localizing others. Some haptic spatial tasks seem to call
into play multiple frames of reference, particularly when
objects must be localized within an allocentric frame.
Kappers and colleagues demonstrated the use of multi-
ple frames when subjects were required to orient rods rela-
tive to each another. The task was to orient an adjustable
bar so that it was parallel to the angle of a reference bar
located on the same plane. Figure 10A shows an arrange-
ment of a pair of rods aligned by a hypothetical subject so
as to appear “parallel” using the standard setup for Kap-
pers’s studies. Note that the bar to the right of the subject’s
midline would require a clockwise deviation from the ref-
erence angle to be perceived as parallel, and vice versa for
Rensink, O’Regan, & Clark, 1997; audition—e.g., Vite-
vitch, 2003). Most recently, a tactile analogue of change
blindness has also been reported (Gallace, Auvray, Tan,
& Spence, 2006), whereby observers demonstrate an in-
ability to perceive spatial changes (element addition or
deletion) to simple tactile patterns. These tactile spatial
events were presented in sequence, along with a vibro-
tactile mask (tactile “mudsplash”) that coincided with the
start of the spatial change.
Localization in Space External to the Body
Here we consider how people localize points in space
external to the body that they encounter during haptic
exploration without vision. Research on haptic space
perception has produced a number of intriguing phenom-
ena, but as yet no encompassing theory (see, e.g., Millar,
1976, 1994). A salient point emerging from this literature
is that reports of haptically perceived spatial layout are
subject to a variety of distorting influences, particularly
from the nature of exploration. An interesting contrast is
found between people’s ability to return to a previously
touched location in space and their ability to report where
that location is in space (Klatzky & Lederman, 2003). The
former can be performed on the basis of a motor mem-
ory, whereas the latter calls for a representation of space
grounded in haptic processing. Construction and use of
this representation appear to produce the errors that were
observed.
In some cases, systematic error trends appear to result
because haptic perceivers have available a number of po-
tential reference frames, which can simultaneously con-
tribute to the perceptual outcome. Haptic spatial localiza-
tion may refer either to a coordinate system centered on the
body, thus constituting an egocentric frame of reference,
or to an allocentric frame of reference, such as would be
defined by the edges of a table. As noted above, when we
Head-and-Chin Rest
Comparison
Stimuli
Standard
Stimulus
Occluding
Board
AB
Rails
Midsagittal Plane (y-axis)
10 cm 10 cm
Rail
Rail
Rail
Standard
Stimuli
Comparison
Stimuli
15 cm
15 cm
15 cm
Reference Plane
(x-axis)
Participant
Figure 9. (A) Schematic side view and (B) schematic view of the apparatus and
stimulus configuration. Note that in the experiment, only one comparison stimulus,
at a distance of either 15 or 30 cm, was used in any given trial. From “Location of the
Egocenter in Kinesthetic Space,” by K. Shimono, A. Higashiyama, and W. J. Tam, 2001,
Journal of Experimental Psychology: Human Perception & Performance, 27, p. 849.
Copyright 2001 by the American Psychological Association.
Ha p t i c pe r c e p t i o n 1451
of these anisotropies has been found to depend on the pat-
terns of movement by which the extents are explored (Hel-
ler, Calcaterra, Burson, & Green, 1997; Wong, 1977).
Other Significant Issues
Vision–Touch Interactions
Vision–touch integration
. When we pick up an apple
and feel its smooth, rounded contours, we also see it,
smell it, and hear the slide of our fingers along its sur-
face. Intersensory interactions have long been of interest
to perception researchers. Not surprisingly, there has been
considerable research on interactions between haptic per-
ception and other sensory modalities. Perhaps the most
general question is: How are inputs from multiple modali-
ties about a common physical event combined? A number
of methodologies have been used to answer this question,
usually by comparing data from unimodal with that of bi-
modal or multimodal conditions.
Multimodal interactions can be characterized by estimat-
ing the relative weight given to each of the input modali-
ties in the conjoint percept. Simple additive models have
been used to fit a bimodal response function as a weighted
average of the unimodal conditions (Anderson, 1974). In
another manipulation known as intersensory conflict, the
perceiver is presented with discrepant bimodal information
about a single physical entity. The response (e.g., matching;
the bar to the left of her body midline. Figure 10B shows
a full set of objectively parallel bars. Figure 10C shows
the adjustments made by one subject with her right hand
to perceptually match the parallelism of the rods presented
in Figure 10B. Figure 10D shows the wide range (8º–91º)
of individual subject errors observed in one study (Kap-
pers, 2003), depending on the position of the adjustable
bar relative to the reference bar. A model proposed to ac-
count for these results suggested that subjects used two
competing frames of reference, one centered on the body
(most probably the hand) and the other anchored to exter-
nal space. The relative weightings of these frames differed
across subjects.
A fundamental question about haptic space perception
is whether the distance metric is uniform across space, re-
gardless of distance magnitude and direction. This would
constitute isotropy. A number of illusions have shown that
haptic space is anisotropic. In the radial/tangential illu-
sion, for example, linear extents felt along a radius to-
ward and away from the body are perceived as longer than
the same extents felt along a tangent to that radius (e.g.,
Cheng, 1968; Marchetti & Lederman, 1983). Another case
is the horizontal–vertical illusion: When people feel T- or
L-shaped raised stimuli presented on the horizontal plane,
vertical lines are overestimated relative to length-matched
horizontal components (e.g., Burtt, 1917). The magnitude
Deviation (deg)
40
50
60
70
0
10
20
30
80
90
Subjects
DC
BA
Figure 10. (A) Standard setup for experiments on the haptic perception of horizontal tabletop
space. According to empirical data, the two bars in this figure may be perceived as being close to
haptically “parallel.” (B) A set of objectively parallel lines that maximally overlap with the measure-
ments in panel C; (C) “Perceived parallel” settings to match the objectively parallel bars in panel B
by one subject using her right hand. Figures 10A, 10B, and 10C are from “Haptic Spatial Processing:
Allocentric and Egocentric Reference Frames,” by A. M. L. Kappers, 2007, Canadian Journal of Ex-
perimental Psychology, 61, pp. 209, 210. Copyright 2007 by the Canadian Psychological Association.
Reprinted with permission. (D) Histogram of the distribution of deviations, each bar representing
that of an individual subject. From “Large Systematic Deviations in a Bimanual Parallelity Task:
Further Analysis of Contributing Factors,” by A. M. L. Kappers, 2003, Acta Psychologica, 114, p. 132.
Copyright 2003 by Elsevier. Reprinted with permission.
1452 Le d e r m a n a n d KL a t z K y
when texture is defined intensively, in terms of roughness
(Lederman, Thorne, & Jones, 1986). The prediction of the
MLE approach—namely, that the modality weights reflect
their relative reliabilities—has been confirmed, for exam-
ple, with respect to visual/haptic edges (Ernst & Banks,
2002) (see Figure 12 for a depiction of the experimental
setup). However, the MLE model breaks down when the
inputs do not appear to originate from the same physical
source location (Helbig & Ernst, 2007).
Higher level vision/touch interactions
. Up to this
point, we have dealt with situations where vision and
haptic inputs provide information, potentially discrepant,
about a single property of an object or event. Intersensory
interactions extend as well to situations where vision and
touch provide information about different objects, calling
for allocation of attention or interobject interaction. In the
domain of cross-modal attention, Cinel, Humphreys, and
Poli (2002) found an analogue to illusory conjunctions,
first demonstrated with respect to intramodal visual in-
teractions such as confusions between shape and color
(Treisman, Sykes, & Gelade, 1977). Subjects in the Cinel
et al. study touched an unseen textured bar while viewing
two objects, each a shape (e.g., a square) composed of
textured material (carpet, fur, beans, or brick). They re-
ported the horizontal–vertical orientation of the touched
forced choice comparison) is used to infer the contribution
of each modality to the bimodal percept. A version of this
paradigm, based on maximum-likelihood estimate (MLE)
models (Ernst & Banks, 2002), constructs psychophysical
functions from two-alternative forced choice tasks, where
the function is a sigmoid describing the change from one
choice to the other across a modulation of the stimulus (see
Figure 11). Unimodal data are used to measure the mean
and reliability (inversely related to variance) of each sen-
sory input. A bimodal condition with discrepant stimuli
is then tested to determine whether observers weight the
sensory inputs in inverse relation to their reliability, as pre-
dicted by the MLE model.
Research on intersensory interactions of haptic inputs
with other modalities has predominately focused on how
vision is combined with touch, although haptic/ auditory
interactions have also been studied (e.g., Jousmäki &
Hari, 1998; Rock & Victor, 1964; Spence, Nicholls, &
Driver, 2001). In keeping with modality specializations
outlined above, the relative weighting of vision in rela-
tion to touch is greater when geometric properties are
being judged than when material properties are tested.
For example, vision/ haptic interactions have been found
to weight vision relatively more strongly when texture is
defined spatially, but for the weight to shift toward touch
σ
2
H
/σ
2
V
= 1
Probability
densities
Combined
Haptic Visual
σ
H
σ
V
S
H
S
H
S
0
= 5.5 cm
S
V
S
V
σ
VH
∆
.5 .5
w
*
V
∆ w
*
H
∆
1.00
.84
.50
0
ProbabilityProportion “Taller”
T
VH
PSE
Psychometric
function
σ
2
H
/σ
2
V
= 4
Probability
densities
Combined
Haptic Visual
σ
H
σ
V
S
H
S
H
S
0
= 5.5 cm
S
V
S
V
σ
VH
∆
.8 .2
w
*
V
∆ w
*
H
∆
1.00
.84
.50
0
T
VH
PSE
Psychometric
function
Estimated
height
Physical
height
Figure 11. Maximum likelihood estimate integration: two hypothetical situations. Visually and
haptically specified heights differ by ∆. Dashed Gaussians in the top panels represent probability
densities of the (unbiased) estimated height from visual and haptic assessment, and solid Gaussians
represent probability densities for the combined estimate. On the left, the visual and haptic vari-
ances are equal (σ
H
2
/σ
V
2
5 1) and both their weights are .5. The mean of the combined probability
density is equal to the mean of the visual and haptic densities and the variance is reduced by half. On
the right, the haptic variance is four times the visual variance (σ
H
2
/σ
V
2
5 4). The visual weight (w
v
) is
then .8 and the haptic weight (w
H
) is .2. Thus, the combined probability density is shifted toward the
visual estimate. From “Humans Integrate Visual and Haptic Information in a Statistically Optimal
Fashion,” by M. O. Ernst and M. S. Banks, 2002, Nature, 415, p. 430. Copyright 2002 by Macmillan.
Reprinted with permission.
Ha p t i c pe r c e p t i o n 1453
ination, perception, and recognition of external objects
and their properties. In keeping with recent trends in other
fields, the science of touch has also begun to focus on
understanding affective aspects of this modality, such as
pleasantness and emotional expression. For example, neu-
roscientists and psychophysicists have recently hypoth-
esized that the rewarding, emotional aspects of touch may
be subserved by a class of unmyelinated peripheral nerve
fibers known as CT (or C tactile) afferents that are found
in hairy, but not glabrous (hairless), skin (Löken, Wess-
berg, Morrison, McGlone, & Olausson, 2009; McGlone,
Vallbo, Olausson, Löken, & Wessberg, 2007; Olausson
et al., 2002).
Researchers have also recently shown that it is possible
to tactually communicate culturally universal human emo-
tions via contact on the arm (Hertenstein, Keltner, App,
Bulleit, & Jaskolka, 2006) and by haptically exploring
emotional expressions depicted on live faces, 3-D face-
masks, and even 2-D raised-line drawings (Lederman,
Kilgour, Kitada, Klatzky, & Hamilton, 2007; Lederman
et al., 2008).
Visual Mediation Versus Multisensory Processing
During Tactile/Haptic Perception
A somewhat controversial proposal that pertains partic-
ularly to interactions between vision and touch is whether
touch may serve as an input channel for subsequent visual
processing. This idea has been reinforced by evidence
obtained with functional-imaging techniques—namely,
that the visual cortex is generally involved in normal
tactile perception by both sighted and blind observers
(e.g., Sathian & Lacey, 2007). More specifically, judg-
ments of the layout of touched objects and of stimulus
motion on the skin have been found to activate areas in the
dorsal visual pathway (macrospatial, Kitada et al., 2006;
Sathian, Zangaladze, Hoffman, & Grafton, 1997; Stoesz
et al., 2003; motion, R. Blake, Sobel, & James, 2004;
Hagen, Zald, Thornton, & Pardo, 2002). However, hap-
tic shape perception of 3-D objects activates the ventral
visual pathway (e.g., Amedi, Jacobson, Hendler, Malach,
& Zohary, 2002; Amedi, Malach, Hendler, Peled, & Zo-
hary, 2001; Deibert, Kraut, Kremen, & Hart, 1999; James
et al., 2002; James, Servos, Kilgour, Huh, & Lederman,
2006; Kitada, Johnsrude, Kochiyama, & Lederman, 2009;
Malach et al., 1995; Pietrini et al., 2004; Reed, Shoham,
& Halgren, 2004; Stoeckel et al., 2003; Zhang, Weisser,
Stilla, Prather, & Sathian, 2004).
What remains unclear is the nature of visual process-
ing of tactile inputs that gives rise to such visual corti-
cal involvement. Visual involvement could include
(1) knowledge- directed processes (e.g., anticipatory vi-
sual imagery, visual memory) that may assist or mediate
tactual performance; (2) stimulus-directed activation of
visual cortical areas by tactual inputs, implying that these
so-called “visual” areas are actually “multisensory”; or
(3) both knowledge-driven and stimulus-driven processes
(Lacey, Campbell, & Sathian, 2007; Sathian & Lacey,
2008).
Evidence consistent with the use of visual imagery dur-
ing passive tactile and active haptic object processing has
bar and then which objects had been visually presented.
There were frequent intermodal conjunction errors, in
which the texture of the touched bar was attributed to a
reported visual object.
Intermodal interactions extend even to social attribu-
tion and intention. Williams and Bargh (2008) found that
subjects who briefly held a cup of hot coffee subsequently
perceived a companion to be more generous and caring
than did those who held an iced coffee. A similar manipu-
lation with a hot therapeutic pad increased the subject’s
tendency to give a gift to a friend rather than to retain it.
The authors conjectured that insular cortex might mediate
the linkage between thermal perception and the attribution
of personal warmth or coolness.
Affective Touch
Up to this point, we have addressed the sense of touch
in terms of crucial issues that pertain to the haptic discrim-
CRT
Stereo
glasses
Opaque
mirror
Force-
feedbac
k
devices
Visual and haptic
scene
Noise:
3 cm equals 100%
Visual height
Haptic height
Width
3-cm depth step
Figure 12. Apparatus and virtual stimulus. Observers viewed
the reflection of the visual block stimulus. Liquid-crystal shut-
ter glasses were used to present binocular disparity, producing
stereo vision; noise was implemented by reducing the stereo cues.
The haptic stimulus was presented to the unseen right hand via
two force-feedback devices, one each for the index finger and
thumb. From “Humans Integrate Visual and Haptic Informa-
tion in a Statistically Optimal Fashion,” by M. O. Ernst and M. S.
Banks, 2002, Nature, 415, p. 431. Copyright 2002 by Macmillan.
Reprinted with permission.
1454 Le d e r m a n a n d KL a t z K y
needed to clarify the contribution(s) of visual imagery to
tactile/haptic processing of familiar and unfamiliar raised
2-D patterns and 3-D objects.
Neural imaging studies also provide some evidence for
the activation of shared neural networks by the presenta-
tion of objects either haptically or visually. For example,
in the study by Kitada et al. (2009), greater modality-
independent activation of the fusiform face area within
the fusiform gyrus and of the extrastriate body area in the
lateral occipital cortex was found when subjects identified
faces or other body parts (hands, feet), respectively, as
compared with nonbiological control objects (bottles).
Lacey et al. (2007) and Sathian and Lacey (2008)
have now examined a large number of studies (including,
but not limited to, most in this section) with respect to
whether visual mediation and/or multisensory process-
ing is used during tactile/haptic perception. Overall, they
conclude that the current evidence collectively points to
the creation of a multisensory spatial representation that
may be flexibly accessed via either knowledge-driven or
stimulus-driven processes. They qualify their conclusion
by further noting that comparisons between unimodal
modality-specific representations cannot be completely
ruled out, and that unimodal representations may also
be present. Owing to the brevity of this tutorial, we refer
interested readers to the two reviews above for specific
details regarding the evidence used by Lacey and Sathian
to support their conclusions.
Plasticity
We briefly mention that the malleability of sensory rep-
resentation in the brain must be considered one of the strik-
ing developments in perception over the last two decades
or so. Pioneering work in this area involved the sense of
touch (for a review, see Buonomano & Merzenich, 1998).
Merzenich, Kaas, Wall, Sur, and Lin (1978) conducted an
early study in which the median nerve of a monkey was
transected, resulting in the cessation of inputs from portions
of the thumb, index, and middle finger to two somatosen-
sory cortical areas. In just a few weeks, representations of
the bordering skin areas were found in these areas. These
original studies have been followed by a large body of work
on functional plasticity and underlying mechanisms.
For example, Pascual-Leone and Hamilton (2001) re-
ported a study in which normal, sighted subjects were
blindfolded for a period of five days, over which serial
fMRIs were performed. As the interval progressed, the
striate and peristriate cortex was activated progressively
more during tactile stimulation. On Day 1, the contralat-
eral somatosensory cortex, but not the occipital cortex,
was activated. From Day 2 through Day 5, BOLD activa-
tion in the somatosensory cortex decreased as it increased
within the “visual” occipital areas. When the blindfold was
removed and subjects were permitted to see for a period
of 12 to 24 h, all changes produced during the blindfold-
ing interval were eliminated. Rapid reversibility of this
phenomenon, as demonstrated by Merabet et al. (2008),
suggests that the effect of visual deprivation may release
inhibition that would otherwise be present.
been obtained in several tasks involving the tactile percep-
tion of grating orientation (e.g., Sathian & Zangaladaze,
2001; Sathian et al., 1997 [see Figure 13]; Zangaladze,
Epstein, Grafton, & Sathian, 1999; Zhang et al., 2004) and
the haptic recognition of common objects depicted in 2-D
raised-outline drawings (Lederman, Klatzky, Chataway, &
Summers, 1990). However, visual imagery is by no means
necessary, as shown in an fMRI study that compared hap-
tic, visual, and visually imaged identification of specific
exemplars of 3-D plaster casts of different body parts
(Kitada et al., 2009). Auxiliary data from three comple-
mentary measures of the contribution of visual imagery
provided evidence that, at best, visual mediation could ex-
plain only a relatively small part of the category-specific
signal increase obtained with haptically presented body
parts. Nonsignificant, or significant but very low, correla-
tions were obtained between activation patterns produced
by conditions in which subjects haptically explored versus
visually imagined the objects, between the activation pat-
terns of subjects who described themselves as using visual
imagery in the haptic condition and those who did not, and
between scores on the VVIQ questionnaire (Marks, 1973),
which measures the vividness of subjects’ visual imaging
abilities, and activation during haptic object identifica-
tion. As Kosslyn and Thompson (1993) and Lacey et al.
(2007) have noted, visual imagery is a highly complex
process that consists of multiple components (e.g., image
generation, maintenance, inspection, and transforma-
tion). Greater understanding of visual imagery, together
with a more extensive battery of evaluation tasks, is much
Figure 13. The MRI of a subject showing parieto-occipital acti-
vation resulting from selective attention to grating orientation (vs.
relative size of grating ridges and grooves); 3-D rendered image
with the top of the brain cut away to reveal its location. The dis-
play threshold is p
.001 (t . 3.31; uncorrected for multiple com-
parisons). From “Feeling With the Mind’s Eye,” by K. Sathian,
A. Zangaladze, J. M. Hoffman, and S. T. Grafton, 1997, Neuro-
Report, 8, p. 3879. Copyright 1997 by Lippincott Williams &
Wilkins. Reprinted with permission.
Ha p t i c pe r c e p t i o n 1455
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Applications
In the last 10 years or so, there has been a veritable
explosion in the multidisciplinary study of haptics by psy-
chophysicists and other experimental psychologists, me-
chanical and electrical engineers, and computer scientists.
The overall goal in this field is to develop effective tactile,
haptic, and multisensory interfaces for use in a wide range
of application domains involving different teleoperational
and virtual environments. Exciting examples include, but
are not limited to, providing tactile and/or haptic cues for
minimally invasive surgery, e-commerce, recreational
games, electromechanical graphics displays for the blind,
and multisensory environments for virtual novice sur-
geons. One of the most recent and potentially pervasive
applications includes adding haptics to mobile phones,
PDAs, and large-scale displays.
In concluding, it is important to recognize that basic
and applied research on haptics mutually influence each
other in valuable ways. The results of fundamental scien-
tific research on human haptics offer valuable guides and
statistical tools for designing and evaluating the effective-
ness of haptic interfaces, sensory substitution systems,
and sensorized prostheses. Conversely, the development
of new haptic interfaces offers touch scientists powerful
new tools for systematically producing and controlling
haptic or multisensory stimuli in innovative ways never
previously possible.
AUTHOR NOTE
This article was financially supported by grants to S.J.L. from the
Canadian Institutes of Health Research (CIHR) and the Natural Sciences
and Engineering Research Council of Canada (NSERC) and to R.L.K.
from the National Science Foundation (Grant BCS-0745328). We thank
Cheryl Hamilton in the Touch Lab at Queen’s University for assisting
in the preparation of the manuscript. Correspondence concerning this
article should be addressed to S. J. Lederman, Department of Psychol-
ogy, Queen’s University, Kingston, ON, K7L 3N6 Canada (e-mail: susan
.lederman@queensu.ca) or to R. L. Klatzky, Department of Psychology,
Carnegie Mellon University, Pittsburgh, PA 15213 (e-mail: klatzky@
andrew.cmu.edu).
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APPENDIX (Continued)