Integration of auditory and vibrotactile stimuli: Effects of
E. Courtenay Wilson, Charlotte M. Reed, and Louis D. Braida
Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge,
?Received 15 October 2009; revised 24 February 2010; accepted 25 February 2010?
Perceptual integration of vibrotactile and auditory sinusoidal tone pulses was studied in detection
experiments as a function of stimulation frequency. Vibrotactile stimuli were delivered through a
single channel vibrator to the left middle fingertip. Auditory stimuli were presented diotically
through headphones in a background of 50 dB sound pressure level broadband noise. Detection
performance for combined auditory-tactile presentations was measured using stimulus levels that
yielded 63% to 77% correct unimodal performance. In Experiment 1, the vibrotactile stimulus was
250 Hz and the auditory stimulus varied between 125 and 2000 Hz. In Experiment 2, the auditory
stimulus was 250 Hz and the tactile stimulus varied between 50 and 400 Hz. In Experiment 3, the
auditory and tactile stimuli were always equal in frequency and ranged from 50 to 400 Hz. The
highest rates of detection for the combined-modality stimulus were obtained when stimulating
frequencies in the two modalities were equal or closely spaced ?and within the Pacinian range?.
Combined-modality detection for closely spaced frequencies was generally consistent with an
algebraic sum model of perceptual integration; wider-frequency spacings were generally better fit by
a Pythagorean sum model. Thus, perceptual integration of auditory and tactile stimuli at
near-threshold levels appears to depend both on absolute frequency and relative frequency of
stimulation within each modality.
© 2010 Acoustical Society of America. ?DOI: 10.1121/1.3365318?
PACS number?s?: 43.66.Lj, 43.66.Wv ?CJP?
Recent anatomical and neurophysiological research has
shown evidence of interaction between the auditory and so-
matosensory systems at various levels of the central nervous
system in both animals ?e.g., Zhou and Shore, 2004; Cappe
and Barone, 2005; Schroeder et al., 2001? and in humans
?Foxe et al., 2002; Schürmann et al., 2006?. Perceptual stud-
ies also provide evidence for auditory-somatosensory inter-
actions. For example, facilitative interactions between audi-
tion and touch have been observed using subjective
techniques such as loudness matching ?e.g., Schürmann et
al., 2004; Gillmeister and Eimer, 2007; Yarrow et al., 2008?
as well as objective measurements of detection and discrimi-
nation ?e.g., Schnupp et al., 2005; Wilson et al., 2009; Yau et
al., 2009; Ro et al., 2009?. Other studies ?Gescheider et al.,
1969; Gescheider, 1970?, however, have reported inhibitory
results for the detection of a tactile stimulus in the presence
of a suprathreshold auditory tone.
Our previous research in this area ?Wilson et al., 2009?
examined the perceptual integration of auditory and vibrotac-
tile 250 Hz tones in an objective detection task as a function
of the relative phase and temporal asynchrony of 500 ms
tone pulses. Our results showed that performance increased
significantly over unimodal detection when the auditory and
tactile signals were presented synchronously, and that the
combined performance increase was not affected by the rela-
tive phase between the auditory and tactile stimuli. The lack
of a phase effect suggests integration operates on the slowly
varying envelopes of the auditory and tactile stimuli rather
than on their temporal fine structure, the cycle by cycle
variation in the auditory and tactile waveforms. The effects
of presenting the auditory and tactile stimuli with no tempo-
ral overlap ?i.e., asynchronously? were consistent with time
constants deduced from single-modality masking experi-
ments. For example, when the tactile signal preceded the
auditory signal, a significant increase in performance was
observed for temporal separations up to 100 ms between the
offset of the tactile stimulus and the onset of the auditory
stimulus. On the other hand, when the auditory stimulus was
presented before the tactile stimulus ?with no temporal over-
lap?, performance on the combined condition was not signifi-
cantly different from performance on either the auditory- or
The current study extends our previous work by exam-
ining the effects of stimulus frequency on auditory-tactile
integration when stimuli in both modalities are presented si-
multaneously at signal levels near the threshold of detection.
Given that both of these sensory systems respond differen-
tially to frequency ?auditory: Fletcher and Wegel, 1922;
Fletcher, 1940; Dadson and King, 1952; Watson et al., 1972;
Romani et al., 1982; Bilecen et al., 1998; Schreiner et al.,
2000; Talavage et al., 2000; Talavage et al., 2004; soma-
tosensory: Bolanowski et al., 1988; Francis et al., 2000;
Gescheider et al., 2002; Gescheider et al., 2001; Harrington
and Downs, 2001; Harris et al., 2006; Hegner et al., 2007;
Iguchi et al., 2007? and that the frequency region to which
both systems are responsive is limited, it is possible that
frequency of stimulation may be an important variable in
auditory-tactile perceptual interactions. Specifically, we hy-
pothesize that if the auditory and tactile systems integrate
3044 J. Acoust. Soc. Am. 127 ?5?, May 2010 © 2010 Acoustical Society of America0001-4966/2010/127?5?/3044/16/$25.00
into a common neural pathway, then interaction effects
should be greater than when they integrate in different path-
ways. Furthermore if the same frequency is conveyed by a
common pathway and different frequencies are conveyed by
different pathways, then integration effects should be greater
when both modalities are stimulated by the same frequency
than by different frequencies.
This paper explores the frequency relationship between
audition and touch in a signal detection task in three experi-
ments. In Experiment 1, the frequency of the auditory com-
ponent assumed values in the range of 125–2000 Hz while
the frequency of the tactile component was held constant at
250 Hz. In Experiment 2, the frequency of the tactile signal
assumed values in the range of 50–400 Hz while the fre-
quency of the auditory component was held constant at 250
Hz. In Experiment 3, the frequencies of the auditory and
tactile stimuli were equal to each other and assumed values
in the range of 50–400 Hz. For comparison purposes, we
tested purely auditory detection with a 250 Hz narrowband
noise ?NBN? that was combined with a tone of frequency
ranging from 125 to 2000 Hz ?Appendix?. These experiments
were designed ?a? to test the effects of frequency separation
between the auditory and tactile components on multisensory
integration and ?b? to test the effects of frequency of stimu-
lation when the auditory and tactile stimulating frequencies
were equal to one another and covarying. Measurements of
d? ?and % correct? were obtained for auditory-alone, tactile-
alone, and combined auditory-tactile presentations. The ob-
served performance in the combined condition was then
compared to predictions of multimodal performance derived
from observed measures of detectability within each of the
two separate sensory modalities.
Green ?1958? and Marill ?1956? considered a variety of
models to relate the detectability of individual tones to the
detectability of auditory two-tone complexes. Green consid-
ered a “statistical decision model” by analyzing linear com-
binations of the observations made on the two tones of the
complex ?X?f1? and X?f2??:
Z = aX?f1? + bX?f2?.
He showed that ?i? under the assumption that X?f1? and X?f2?
are uncorrelated Gaussian random variables, the optimal
choice of a and b leads to a detectability index
d?Z= ??d?1?2+ ?d?2?2?1/2,
where d?1and d?2are the detectability indices of the two
tones separately and ?ii? when X?f1? and X?f2? are perfectly
correlated, the optimal choice of a and b leads to a detect-
d?Z= d?1+ d?2.
Thus when the observations are contaminated by indepen-
dent noise, the Pythagorean sum applies, whereas when they
are contaminated by correlated noise, the arithmetic sum ap-
plies. Green’s ?1958? “no-summation model” assumed that
the detectability of the complex was equal to the detectability
index of the more detectable of the tones:
Green ?1958? also considered a form of “probability summa-
tion” that assumes that in the detection of a single tone, a
decision variable must exceed a threshold value. In the par-
ticular probability summation model considered, the “two
independent thresholds model,” when two tones are pre-
sented and the decision variables associated with them are
independent, a detection response will result if either or both
tones exceeds the threshold value of the decision variable.
Green ?1958? measured the detection of pure tones of
frequency 500, 1000, 1823, and 2000 Hz as well as all pairs
made up from these tones. Green tested three listeners on the
detection of 50, 200, and 1000 ms tone bursts in 60 dB
spectrum level noise using a four-alternative forced choice
procedure. He rejected the no-summation model because the
percentage of correct detections of the two-tone complex was
greater than the percentage of correct detections of the most
detectable component in the complex in 53 out of 54 cases.
Green ?1958? rejected the two independent thresholds model
because it had an average error of roughly 5% whereas the
Pythagorean form of the statistical decision model had an
average error of only 1.5%. He did not consider the arith-
metic sum form of the statistical decision model, although it
seems unlikely to have made good predictions for these data.
Marill ?1956? tested two listeners on the detection of 1 s
bursts of 500 and 1100 Hz tones in 57 dB spectrum level
noise as a function of signal level in a two-interval, two-
alternative forced choice ?2I, 2AFC? experiment. He then
measured the detection of pairs of tones ?500, 540?, ?1060,
1100?, and ?500, 1100? Hz. Marill ?1956? compared his re-
sults to models similar to Green’s ?1958? no-summation
model and the arithmetic sum form of the statistical decision
model. He found that the no-summation model predicted the
detectability of the ?500, 1100 Hz? pair whereas the arith-
metic sum form of the statistical decision model predicted
the detectability of the ?1060, 1100 Hz? pair. The detectabil-
ity of the ?500, 540 Hz? pair fell between the predictions of
these two models, and would likely been explained by the
Pythagorean form of the statistical decision model.
Recently, Grose and Hall ?1997? tested eight listeners
using a three-alternative forced choice adaptive procedure
with a masker consisting of 20 Hz wide bands of noise pre-
sented at 35 dB spectrum level. They found that a Pythagor-
ean sum type model accounted for the detection of pairs
consisting of 870 and 1125 Hz tones of duration 400 ms.
In previous work on multimodal auditory-tactile detec-
tion ?Wilson et al., 2009?, we compared results to three dif-
ferent models that were similar to those considered by Green
?1958?. The optimal single channel model ?OSCM? is similar
to Green’s no-summation model; the Pythagorean sum model
?PSM? is similar to the Pythagorean sum form of Green’s
statistical decision model; and the algebraic sum model
?ASM? is similar to the arithmetic sum version of Green’s
statistical decision model. The OSCM assumes that the ob-
servers’ responses are based on the better of the tactile or
auditory input channels; the PSM assumes that integration
occurs across channels ?e.g., as in audiovisual integration,
J. Acoust. Soc. Am., Vol. 127, No. 5, May 2010Wilson et al.: Auditory-tactile integration: Frequency3045
Braida, 1991? and that the combined auditory-tactile re-
sponse is the Pythagorean sum of the separate channels; and
the ASM assumes that integration occurs within a given
channel and that the combined response is the linear sum of
the scores for the separate channels. We did not consider
models based on probability summation based on Green’s
finding that the predictions of such models were inferior to
the Pythagorean sum version of the statistical decision
model. We found that on average, the observed scores tended
to be greater than the prediction of the OSCM and the PSM
but less than the prediction of the ASM. The same models of
integration were applied in the current research to determine
the manner in which properties of integration are affected by
frequency of stimulation in each modality.
The auditory stimuli were pure tones presented in a
background of pulsed 50 dB sound pressure level ?SPL?
Gaussian broadband noise ?bandwidth of 0.02–11.0 kHz?.
The frequency of the auditory stimulus across the three ex-
periments was 50, 125, 250, 400, 500, 1000, and 2000 Hz.
The tactile stimuli were sinusoidal vibrations with a fre-
quency of 50, 125, 250, and 400 Hz across the three experi-
ments. The background noise was used to mask possible au-
ditory cues arising from the tactile device and was present in
all auditory ?A?, tactile ?T?, and combined auditory plus tac-
tile ?A+T? test conditions. Sinusoidal signals in both modali-
ties were generated digitally ?using MATLAB 7.1 software? to
have a total duration of 500 ms that included 20 ms raised
cosine-squared rise/fall times.
The digitized signals were played through a D/A sound
card ?Lynx Studio Lynx One, Costa Mesa, CA? with a sam-
pling frequency of 24 kHz and 24 bit resolution. The audi-
tory signal was sent through channel 1 of the sound card to a
programmable attenuator ?TDT PA4? and headphone buffer
?TDT HB6? before being presented diotically through head-
phones ?Sennheiser HD 580?. The tactile signal was passed
through channel 2 of the sound card to a programmable at-
tenuator ?TDT PA4? and amplifier ?Crown D-75? before be-
ing delivered to an electromagnetic vibrator ?Alpha-M Cor-
poration, model AV-6, Dallas, TX?. The subject’s left middle
fingertip made contact with the vibrator ?0.9 cm diameter?
which was housed inside a wooden box for visual shielding
and sound attenuation. A heating pad was placed inside the
box to keep the box and tactile device at a constant tempera-
ture. A laser accelerometer was used to calibrate the tactile
device so that displacement could be measured from input
Eight subjects ranging in age from 18 to 45 years ?four
females? participated in this study. Audiological testing was
conducted on the first visit to the laboratory. Only those sub-
jects who met the criterion of normal audiometric thresholds
?20 dB hearing level or better at frequencies of 125, 250,
500, 1000, 2000, 4000, and 8000 Hz? were included in the
studies. All subjects were paid an hourly wage for their par-
ticipation in the experiments and signed an informed-consent
document prior to entry into the study. All subjects except
S13were right handed. Five subjects participated in Experi-
ment 1 ?S1, S6, S10, S13, and S14?, four in Experiment 2 ?S1,
S6, S10, and S11?, and four in Experiment 3 ?S6, S10, S18, and
S22?. Three of the subjects participated in multiple experi-
ments ?S1: Experiments 1 and 2; S6and S10: Experiments 1,
2, and 3?. These three subjects also participated in experi-
ments conducted by Wilson et al. ?2009? and subject identi-
fication is consistent with that used in our previous paper.
C. Experimental conditions
The experiments examined the perceptual integration of
sinusoidal auditory and vibrotactile signals with different
values of frequency, which were presented near the threshold
of detection. Within a given test session, threshold measure-
ments were first obtained under each of the two single-
modality conditions ?A and T separately?. Then the detect-
ability of the combined A+T signal was measured at levels
established for threshold within each of the two individual
modalities. The experimental conditions examined the effects
of frequency under different relative conditions: Auditory
frequency varied, tactile frequency constant ?Experiment 1?;
tactile frequency varied, auditory frequency constant ?Ex-
periment 2?; and auditory and tactile frequency equal and
covaried ?Experiment 3?.
For all A+T conditions, the auditory and tactile sinuso-
ids were presented in sinusoidal phase with equal onset and
Baseline condition. A baseline condition employing an
equal frequency of 250 Hz for both A and T stimulation was
included in each of the experiments.1
Experiment 1. Experiment 1 examined the effect of
varying the frequency of the auditory stimulus while holding
the tactile stimulus frequency constant. The frequency of the
tactile stimulus was held constant at 250 Hz while the fre-
quency of the auditory stimulus took on five different values:
125, 250, 500, 1000, and 2000 Hz resulting in five separate
experimental conditions: A125+T250, A250+T250, A500
+T250, A1000+T250, and A2000+T250. The order of the
five experimental A+T conditions was randomized for each
of four replications for each of the five subjects. Subjects S1,
S6, S10, S13, and S14participated in this experiment. Subjects
required a total of 5 days ?S6? to 12 days ?S1? of testing to
complete the experiment.
Experiment 2. Experiment 2 examined the effect of
varying the frequency of the tactile stimulus while holding
the auditory stimulus frequency constant. The frequency of
the auditory stimulus was held constant at 250 Hz while the
frequency of the tactile stimulus took on four different val-
ues: 50, 125, 250, and 400 Hz resulting in four separate
experimental conditions: A250+T50, A250+T125, A250
+T250, and A250+T400. The order of the four experimental
A+T conditions was randomized for each of four replications
for each of the four subjects. Subjects S1, S6, S10, and S11
participated in this experiment. One subject ?S11? required 6
days to complete the repetitions of the four combined runs,
3046J. Acoust. Soc. Am., Vol. 127, No. 5, May 2010 Wilson et al.: Auditory-tactile integration: Frequency
while the remaining three subjects ?S1, S6, and S10? required
Experiment 3. Experiment 3 examined the effect of co-
varying the frequencies of both the tactile and auditory
stimulus while holding them equal to one another. The fre-
quencies of the auditory and tactile stimuli were 50, 125,
250, and 400 Hz resulting in four separate experimental con-
ditions: A50+T50, A125+T125, A250+T250, and A400
+T400. The order of the four experimental A+T conditions
was randomized for each of four replications for each of the
four subjects. Subjects S6, S10, S18, and S22participated in
this experiment. Two subjects ?S10and S22? required 9 total
days, while S6and S18required 11 and 12 days of testing,
respectively, to complete the experiment.
D. Experimental procedures
For all experimental conditions, subjects were seated in
a sound-treated booth and were presented with 50 dB SPL
broadband noise diotically via headphones. For testing in
conditions that involved presentation of the tactile stimulus
?T and A+T?, the subject placed the left middle finger on the
electromagnetic vibrator. In each experimental session, test-
ing was first conducted for A-alone and T-alone separately to
establish a signal level for single-modality performance in
the range of 63% to 77% correct. Performance was then
measured in the A+T conditions for a given experiment. The
number of experimental A+T conditions that could be com-
pleted within a given test session was generally dependent on
the time required to establish signal levels that met the
single-modality performance criterion. Each experimental
session lasted no more than 2 h on any given day and sub-
jects were required to take frequent breaks throughout the
session. For each subject, three training sessions identical to
the experimental sessions were provided before data were
In Experiments 1 and 2, certain single-modality condi-
tions were retested in the fixed-level procedure before the
end of each session to ensure that thresholds remained stable
throughout the session. For Experiment 1, only T-alone was
retested and for Experiment 2, only A-alone was retested. No
post-session test was performed for Experiment 3 because
the thresholds were measured immediately preceding each
combined run. If single-modality thresholds were less than
56% correct or greater than 84% correct ??2 standard devia-
tions assuming an original score of 70% correct?, the data for
that session were discarded. If a subject’s threshold shifted
more than 2 standard deviations in three nontraining ses-
sions, our policy was to terminate that subject from the
study; however, all subjects met the qualification for thresh-
old stability and none was disqualified on these grounds.
2I, 2AFC tests. The threshold estimates under the single-
modality A and T conditions employed a 2I, 2AFC fixed-
level procedure with 75 trials per run. Stimulus levels were
adjusted and runs were repeated until scores of 63% to 77%
correct were obtained. These stimulus levels were then used
in testing the combined A+T conditions with the fixed-level
2I, 2AFC procedure.
On each presentation, the stimulus ?A, T, or A+T? was
presented with equal a priori probability in one of the two
intervals. The interval duration was 1.1 s for all experiments.
Each observation interval was marked by a visual cue that
appeared on a computer terminal located in front of the sub-
ject. Noise was presented diotically over headphones starting
500 ms before the first interval, and played continuously
throughout a trial ?including the durations of the two inter-
vals and the 500 ms duration between intervals? before being
turned off 500 ms after the end of the second interval. Each
trial had a fixed duration of 3.7 s, plus the time it took sub-
jects to respond. The onset of the stimulus ?A, T, or com-
bined A+T? was always coincident with the onset of the
observation interval in which it appeared. Subjects re-
sponded between trials by selecting the interval in which
they thought the stimulus was presented ?using either a
mouse or keyboard? and were provided with visual correct-
answer feedback after each trial. Attention to the combined
A+T stimulus was encouraged by having subjects count the
number of times they perceived a signal.
E. Data analysis
A two-by-two stimulus-response confusion matrix was
constructed for each 75-trial experimental run, and was used
to determine percent-correct scores and signal-detection
measures of sensitivity ?d??. These measures were averaged
across the repetitions of each experimental condition within
a given subject. Statistical tests performed on the data in-
cluded analyses of variance ?ANOVAs? on the arcsine-
transformed percent-correct scores, with statistical signifi-
cance level defined for probability ?p-values? less than or
equal to 0.01. For statistically significant effects a post hoc
Tukey–Kramer analysis was performed with alpha=0.05.
F. Models of integration
The results of the experiments were compared with three
different models of integration: OSCM, PSM, and ASM. The
OSCM assumes that the observers’ responses are based on
the better of the tactile or auditory input channels. The pre-
greater of the tactile ?d?T? or auditory ?d?A?, D?OSCM
=max?d?T,d?A?. The PSM assumes that integration occurs
across channels ?e.g., as in audiovisual integration, Braida,
1991? and that the d? in the combined auditory-tactile con-
dition is the Pythagorean sum of the d? values for the sepa-
rate channels, D?PSM=?d?A
hand, assumes that integration occurs within a given channel
and that the combined d? is the linear sum of the d? values
for the separate channels, D?ASM=d?A+d?T. For example, if
the auditory d?Awas 1.0 ?69% correct? and the tactile d?T
was 0.8 ?66% correct?, the OSCM would predict a D?OSCMof
1.0 ?69% correct?, the PSM would predict a D?PSMof 1.28
?74% correct?, and the ASM would predict a D?ASMof 1.8
?82% correct?. The OSCM prediction is never greater than
the PSM prediction, which in turn is never greater than the
prediction of the ASM.
Chi-squared goodness-of-fit calculations were employed
to compare observed with predicted values from each of the
three models. The predictions of the models were evaluated
3for the combined A+T condition is the
2. The ASM, on the other
J. Acoust. Soc. Am., Vol. 127, No. 5, May 2010Wilson et al.: Auditory-tactile integration: Frequency3047
as follows: First, d? values were determined for each audi-
tory ?d?A? and tactile ?d?T? experiment, on the basis of 75
total trials. Second, predicted d? values were computed for
the three models according to the formulas given above.
Third, predicted % correct scores were computed for each of
the modelsin thefollowing
=100???D?A+T?/2?, where ? is the cumulative of the Gauss-
ian distribution function, and D?A+Tis the predicted D?.
Fourth, the observed A+T confusion matrix was analyzed to
estimate d?A+Tand the “no bias” estimate of % correct score
was computed as %A+T=100???d?A+T?/2?. This relatively
small adjustment ?1.6 percentage points on average, 13
points maximum? was necessary because the predictions of
the models assumed that the observer is not biased. Predic-
tions ?D?OSCM, D?PSM, and D?ASMor %OSCM, %PSM, and
%ASM? were compared with observations ?d?A+Tor %A+T?.
The proportion of the observations that agreed with predic-
tions was judged by having a chi-squared value less than
3.841 ?the 95% criterion? between predicted and observed
scores ?corrected as discussed above? using a contingency
table analysis ?Neville and Kennedy, 1964?. This analysis
allows for errors in both the observed score and the predicted
manner: % correct
A. Signal levels employed in single-modality
Levels for auditory-alone conditions. The mean signal
levels that yielded performance in the range of 63% to 77%
correct for auditory pure tones in 50 dB SPL broadband
noise are shown in the upper panel of Fig. 1. Frequencies
measured in these experiments included 50, 125, 250, 400,
500, 1000, and 2000 Hz. Mean levels are plotted for each
individual subject for the frequencies tested in each of the
three experiments. Each data point depicted in the plot is
based on an average of at least 4 and as many as 11 mea-
surements per frequency. Averaged across subjects and ex-
periments, the mean threshold level for each of the tones is
shown as a solid line. Within a given subject, levels for all
frequencies tested were highly stable for measurements made
within a given experiment and across experiments. For all
but one subject, values of ?2 standard error of the mean
?SEM? ?accounting for 96% of the measurements? ranged
from 0.0 to 1.92 dB across subjects and experiments. For that
subject ?S10?, variability was slightly higher ?2.77 dB? in the
400 Hz condition in Experiment 3.
Critical ratios ?CRs? were calculated for the tone-in-
noise levels shown in Fig. 1 by subtracting the spectrum
level of the noise from the presentation levels of the different
tones employed in these experiments. The spectrum level
was flat from approximately 100 Hz to 11 kHz ?7.4 dB? but
was 20 dB at 50 Hz. The magnitude of the CR was consistent
with the values reported by Hawkins and Stevens ?1950? in
the range of 125–2000 Hz, and with values reported by
Houtsma ?2004? for 50 Hz tones. These results indicate that
subjects were listening to tones at levels near masked thresh-
Levels for tactile-alone conditions. The mean signal lev-
els that yielded performance in the range of 63%–77% cor-
rect for a sinusoidal vibration ?50, 125, 250, and 400 Hz? to
the left middle fingertip are shown in the lower panel of Fig.
1. All threshold measurements were obtained in the presence
of a diotic 50 dB SPL broadband noise presented over head-
phones. Mean levels are shown for individual subjects who
participated in each of the three experiments. Each data point
is based on 4–20 measurements per frequency across indi-
vidual subjects and experiments. The average level across
subjects is represented by the solid line in the lower panel of
Fig. 1. Within-subject values of ?2 SEM ?accounting for
96% of the measurements? ranged from 0 to 2.2 dB across
subjects and experiments.
Mean thresholds measured across the three experiments
were 1.0 dB re 1 ?m peak at 50 Hz, ?21.7 dB at 125 Hz,
?24.2 dB at 250 Hz, and ?14.6 dB at 400 Hz. These
threshold values are consistent with previous measurements
using contactor areas in the range of 28–150 mm2?e.g.,
Gescheider et al., 2002; Verrillo et al., 1983; Lamoré et al.,
1986; Rabinowitz et al., 1987; Verrillo, 1963? and show a
FIG. 1. ?Color online? Single-modality signal levels employed for indi-
vidual subjects tested in each of the four experiments. Auditory levels are
for detection of pure tones in 50–dB SPL broadband noise. Tactile levels are
for detection of sinusoidal vibrations presented to the fingertip. Different
symbols represent results obtained in different experiments. Some subjects
participated in more than one experiment. Solid line indicates the average
across subjects and experiments for each frequency. Error bars are 1 SEM.
3048 J. Acoust. Soc. Am., Vol. 127, No. 5, May 2010Wilson et al.: Auditory-tactile integration: Frequency
similar frequency dependence. Specifically, maximal sensi-
tivity is obtained at 250 Hz and thresholds increase at fre-
quencies above and below this value.
B. Baseline experiment
Results from the baseline experiment are shown for in-
dividual subjects in Experiments 1–3 in the three panels of
Fig. 2 ?Figs. 2?a?–2?c?, respectively?. The mean % correct
scores with error bars depicting ?1 SEM are plotted for the
three conditions of A-alone, T-alone, and A+T ?auditory and
tactile frequency=250 Hz across the three experiments? for
each subject within each experiment. Averages across sub-
jects are provided as the rightmost data bars within each
panel. For each of the three experiments, there is a substan-
tial increase in the % correct score for the A+T condition
compared with the A-alone and T-alone conditions. The
mean scores on each condition, averaged over subjects, were
similar across experiments: A-alone values were 70.5, 71.5,
and 72.9% correct ?Experiments 1–3, respectively?; T-alone
values were 70.9, 72.6, and 74.3% correct ?Experiments 1–3,
respectively?; and A+T values were 86.6, 86.3, and 87.9%
correct ?Experiments 1–3, respectively?. Variability on the
combined A+T condition was generally low, with values of
?2 SEM ranging from 2.8 to 7.0 percentage points across
subjects and experiments. These results are consistent with
values previously reported by Wilson et al. ?2009? for the
A two-way ANOVA was performed on the arcsine-
transformed percent-correct scores of the baseline experi-
ment to examine the main effects of condition ?A, T, and A
+T? and subject ?eight different subjects across experiments?.
The results indicate a significant main effect for condition
?F?2,111?=88.5, p?0.01? but not for subject ?F?7,111?
=2.09, p?0.01? or for their interaction ?F?14,111?=1.99,
p?0.01?. A post hoc analysis of the main effect of condition
showed that scores on the A+T condition were significantly
greater than on the A-alone and T-alone conditions and that
the A-alone and T-alone conditions were not significantly
different from one another.
C. Experiment 1: Auditory frequency varied, tactile
The results of Experiment 1 are shown in Fig. 3?a?.
Percent-correct scores averaged across five subjects and four
repetitions per condition are shown for each of the five ex-
perimental conditions: A-alone, T-alone, and combined A
+T with five different values for the frequency of the audi-
tory tone ?125, 250, 500, 1000, and 2000 Hz? while the fre-
quency of the tactile tone remained constant at 250 Hz. The
average score for T-alone was 70.9% correct. The average
score for A-alone ranged from 69.1% correct ?2000 Hz? to
FIG. 2. ?Color online? Summary of results for the baseline condition in Experiments 1–3. Percent-correct scores for the individual subjects in each experiment
are averaged across multiple repetitions per condition; number of repetitions varies by subject, and is equal to or greater than four per subject. AVG is an
average across subjects and repetition in each experiment. White bars represent auditory-alone conditions, gray bars represent tactile-alone conditions, and
black bars represent the A+T baseline condition with auditory and tactile frequencies=250 Hz, simultaneous presentation. Error bars are 1 SEM.
J. Acoust. Soc. Am., Vol. 127, No. 5, May 2010 Wilson et al.: Auditory-tactile integration: Frequency3049
72.3% correct ?125 Hz?. Variability in terms of ?2 SEM was
small and ranged from 1.3 ?A=2000 Hz? to 2.3 ?A
=1000 Hz? percentage points across all single-modality con-
ditions. Average scores for the A+T conditions changed as a
function of auditory stimulus frequency. The highest score of
86.6% correct was obtained with A=250 Hz. The A+T con-
ditions with other auditory frequencies resulted in lower
scores: 125 Hz=82.5% correct, 500 Hz=82.0% correct,
1000 Hz=77.5% correct, and
Variability was small, with ?2 SEM values ranging from 2.9
?A=125 Hz? to 5.0 ?A=1000 Hz? percentage points.
A two-way ANOVA was performed on the arcsine-
transformed percent-correct scores with main factors of con-
dition ?A, T, and A+T? and subject. The A condition includes
A-alone measures at the five auditory frequencies, the T con-
dition includes T-alone measures at 250 Hz, and the A+T
condition includes five auditory-tactile frequency combina-
tions. The results of the ANOVA indicate significant main
effects for condition ?F?14,225?=27.41, p?0.01? and sub-
ject ?F?4,225?=7.71, p?0.01? as well as a significant inter-
action between them ?F?56,225?=3.67, p?0.01?. The post
hoc analysis of the condition effect indicated that all of the
A-alone scores and T-alone scores were statistically equiva-
2000 Hz=80.6% correct.
lent and that the scores on each of the five A+T frequency
combinations were significantly higher than each of the uni-
modal scores. Within the five A+T frequency combinations,
the post hoc analysis indicated that the A250+T250 score
was significantly greater than the scores for A500+T250,
A1000+T250, and A2000+T250 but was not significantly
different from the score for A125+T250; no other significant
differences were found among the remaining A+T frequency
combinations. The mean performance of the subjects was
ordered as S14?S13?S6?S1?S10. A post hoc analysis of
the main effect for subject indicated that the following dif-
ferences among subjects were significant: the scores of S14
were significantly less than those of S1and S10, the scores of
S13were significantly lower than those of S10, and the scores
of S6were not significantly different from those of any other
subject. The interaction effect arises in part from different
patterns of performance for individual subjects on the
D. Experiment 2: Tactile frequency varied, auditory
The results of Experiment 2 are shown in Fig. 3?b?.
Percent-correct scores averaged across four subjects and four
FIG. 3. ?Color online? Summary of results for Experiment 1 ?3a?, Experiment 2 ?3b?, and Experiment 3 ?3c?. Percent-correct scores are averaged across
subjects and sessions. Scores are shown for A-alone ?white bars?, T-alone ?light gray bars?, and for combined A+T conditions ?dark gray bars?. In Experiment
1, scores are shown as a function of auditory frequency with tactile frequency=250 Hz. In Experiment 2, scores are shown as a function of tactile frequency
with auditory frequency=250 Hz. In Experiment 3, scores are shown as a function of frequency where auditory=tactile. Error bars are 1 SEM.
3050J. Acoust. Soc. Am., Vol. 127, No. 5, May 2010Wilson et al.: Auditory-tactile integration: Frequency
repetitions per condition are shown for each of the four ex-
perimental conditions: A-alone, T-alone, and combined A
+T with constant auditory stimulus frequency ?250 Hz? and
four different values of the tactile stimulus frequency ?50,
125, 250, and 400 Hz?. The average score for A-alone was
71.3% correct. T-alone scores ranged from 69.8% correct ?at
T=50 Hz? to 73.4% correct ?at T=250 Hz?. Variability in
terms of ?2 SEM was small and ranged from 1.6 ?A
=250 Hz? to 2.4 ?T=250 Hz? percentage points across all
single-modality conditions. Average scores for the A+T con-
ditions changed as a function of tactile stimulus frequency.
The highest score of 86.4% correct was obtained with a tac-
tile frequency of 250 Hz. Lower scores were obtained with
other tactile frequencies: 50 Hz=76.2% correct, 125 Hz
=85.8% correct, and 400 Hz=78.8% correct. Variability
was small, with ?2 SEM values ranging from 2.1 ?T
=250 Hz? to 4.4 ?T=400 Hz? percentage points.
A two-way ANOVA was performed on the arcsine-
transformed percent-correct scores with main factors of con-
dition ?A, T, and A+T? and subject. The A condition includes
A-alone measures at 250 Hz, the T condition includes
T-alone measures at 50, 125, 250, and 400 Hz, and the A
+T condition includes the four auditory-tactile frequency
combinations. The results of the ANOVA indicate a signifi-
cant main effect for condition ?F?11,144?=21.03, p?0.01?
but not for subject ?F?3,144?=1.96, p?0.01?, and a signifi-
cant interaction effect ?F?33,144?=2.12, p?0.01?. The post
hoc analysis of the condition effect indicated the following:
All of the A-alone scores and T-alone scores were statisti-
cally equivalent; the A250+T50 score was not statistically
different from any of the A-alone and T-alone scores or from
the A250+T400 score, the A250+T400 score was signifi-
cantly higher than six of the eight unimodal scores ?including
those at A250 and T400? but significantly lower than the
A250+T125 and A250+T250 scores, and that the scores on
A250+T125 and A250+T250 were not statistically different
but were significantly higher than all the other unimodal and
bimodal scores. The subject?condition interaction arises
primarily from the superior performance of S10on the
E. Experiment 3: Auditory and tactile frequency equal
The results of Experiment 3 are shown in Fig. 3?c?.
Percent-correct scores averaged across four subjects and four
repetitions per condition are shown for each of the four ex-
perimental conditions: A-alone, T-alone, and combined A
+T with four different values of frequency where A=T ?50,
125, 250, and 400 Hz?. Average scores for A-alone ranged
from 70.5% correct ?at 125 Hz? to 72.5% correct ?at 50 and
250 Hz? and the T-alone scores ranged from 70.6% correct
?at 50 Hz? to 74.1% correct ?at 250 Hz?. Variability in terms
of ?2 SEM was small and ranged from 1.9 ?A=50 Hz? to
2.4 ?T=50 Hz? percentage points across all single-modality
conditions. Average scores for the A+T conditions were
78.3%, 86.47%, 87.25%, and 85.8% correct for auditory-
tactile frequencies of 50, 125, 250, and 400 Hz, respectively.
Variability was smallest on the 250 Hz condition, with a ?2
SEM value of 2.8 percentage points, while that of other fre-
quencies ranged from 5.0 ?125 Hz? to 5.6 ?50 Hz? percentage
A two-way ANOVA was performed on the arcsine-
transformed percent-correct scores with main factors of con-
dition ?A, T, and A+T? and subject. The A condition includes
A-alone measures at four frequencies, the T condition in-
cludes T-alone measures at four frequencies, and the A+T
condition includes the four auditory-tactile frequency combi-
nations. The results of the ANOVA indicate significant main
effects for condition ?F?11,141?=31.38, p?0.01? and sub-
ject ?F?3,141?=10.15, p?0.01? as well as a significant in-
teraction effect ?F?33,141?=5.92, p?0.01?. The post hoc
analysis of the condition effect indicated that all of the
A-alone scores and T-alone scores were statistically equiva-
lent, that scores on A50+T50 were significantly higher than
seven of the eight unimodal scores ?including A50 and T50?
but significantly lower than those of the remaining three A
+T conditions, and that scores on A125+T125, A250
+T250, and A400+T400 were statistically equivalent and
significantly higher than all remaining conditions. The post
hoc analysis of the subject effect indicated that the scores of
S10were significantly higher than those of the remaining
three subjects ?whose scores were not significantly different
from each other?. The interaction effect arises primarily from
differential performance among subjects on the A50+T50
F. Comparisons to model predictions
Chi-squared goodness-of-fit tests were performed on the
data in order to examine which model, the OSCM, the PSM,
or the ASM, best fit the measured percent-correct scores
?Sec. II F?. The proportion of observations in agreement with
predictions, i.e., having a chi-squared value less than 3.841,
is summarized in Table I. Figures 4?a? and 4?b? show plots of
the observed versus predicted percent-correct scores for PSM
and ASM, respectively, for the data set from Experiment 3
?auditory and tactile frequencies equal and covaried?. These
conditions were chosen because they represent an extension
of the baseline data from Wilson et al. ?2009? and because
they demonstrate the best fits to the PSM and ASM models.
?For the original Baseline condition ?250 Hz panel?, data are
also included from Experiments 1 and 2.? The remaining
conditions ?i.e., in which the frequency of the auditory and
tactile stimuli were different from one another? are summa-
rized in Table I, but not displayed. In Figs. 5?a?–5?c?, the
ratio of observed d? to predicted D? is plotted as a function
of stimulus frequency for each of the three experiments ?Ex-
periments 1–3, respectively?.
The baseline condition ?250 Hz panels of Figs. 4?a? and
4?b?? was included in all experiments and involved a total of
53 comparisons. Of these, 30 ?57%? agreed with OSCM pre-
dictions, 40 ?76%? agreed with PSM predictions, and 46
?87%? agreed with ASM predictions. All of the OSCM and
PSM prediction failures are due to under-prediction while the
ASM under-predicted only two out of seven failures. It can
be seen that most of the data points that do not satisfy the
chi-squared test are higher than the predictions of the PSM
J. Acoust. Soc. Am., Vol. 127, No. 5, May 2010 Wilson et al.: Auditory-tactile integration: Frequency3051
?Fig. 4?a?, 250 Hz panel? and lower than the predictions of
the ASM ?Fig. 4?b?, 250 Hz panel?, consistent with results
found previously in Wilson et al., 2009. Of the eight subjects
tested, two ?S13and S18? had more than 95% of measure-
ments passing the chi-squared test for the PSM, while two
had more than 95% of measurements passing the chi-squared
test for the ASM ?S11and S18?. The “extended baseline”
conditions will be discussed below in the context of results
from Experiment 3.
The results of Experiment 1 indicated a change in best-
model fit as a function of auditory frequency. When the au-
ditory and tactile frequencies were equal ?250 Hz, baseline
condition?, the ASM model ?81%? outperformed the PSM
and OSCM ?67% and 52%, respectively?. When the auditory
and tactile stimuli were not equal in frequency, however, the
PSM outperformed the ASM and OSCM by 4–18 percentage
points. The largest prediction difference between models was
measured at 125 Hz, and the three models predicted obser-
TABLE I. Chi-squared tests: predicted vs observed. This table enumerates the number of observations that have passed/failed the chi-squared goodness of fit
test for each of the three models ?i.e., optimal single channel, Pythagorean sum, and algebraic sum?.
Optimal single channelPythagorean sum Algebraic sum
FIG. 4. ?Color online? Predicted vs observed values for the two models of integration, showing data for conditions in which the auditory and tactile
frequencies are equal to one another. The top row ?4a? represents the results of the Pythagorean sum model for the four equal-frequency conditions across
experiments ?from left to right: 50, 125, 250, and 400 Hz?. The 250 Hz panel pools data across Experiments 1–3, while the remaining panels show data from
Experiment 3. The bottom row ?4b? represents the results of the algebraic sum model for the four equal-frequency conditions across experiments ?from left
to right: 50, 125, 250, and 400 Hz?. The 250 Hz panel pools data across Experiments 1–3, while the remaining panels show data from Experiment 3. Results
for each subject are delineated by shape ?see legend? in each panel. Open symbols indicate that the observed value failed the chi-squared test and filled
symbols indicate the observed value passed the chi-squared test.
3052 J. Acoust. Soc. Am., Vol. 127, No. 5, May 2010 Wilson et al.: Auditory-tactile integration: Frequency
vations almost equally well at 2000 Hz ?resulting in the
smallest prediction difference?. The OSCM did not accu-
rately model any conditions of Experiment 1 ?between 50%
and 68% of observations passing the prediction criterion?.
Even though the 2000 Hz condition had the same percentage
of observations passing the model prediction using the
OSCM and ASM ?55%?, all of the failures of the OSCM
were under-predictions, while only 30% of the failures of the
ASM were under-predictions. Figure 5?a? shows that the ra-
tio of observed d? to predicted D? values was close to 1 for
the ASM when the auditory frequency was 250 and 2000 Hz,
and close to 1 for the PSM when the auditory frequency was
1000 Hz. For the 125 and 500 Hz conditions, the ratios fell
between the PSM and ASM predictions.
For Experiment 2, a frequency-dependent trend was also
observed. When the tactile frequency was 125 or 250 Hz, the
ASM model best fit the observations ?88% and 94% passing
the chi-squared tests, respectively?. In the 50 Hz tactile fre-
quency condition, both the OSCM and PSM best fit the ob-
servations ?94% passing the chi-squared test in each model?.
Similarly, in the 400 Hz tactile frequency condition, both the
OSCM and PSM fit the observations equally well ?75% pass-
ing chi-squared tests in each model?. Again, the same trend
occurred such that the OSCM and PSM tended to under-
predict the observations, while the ASM tended to over-
predict observations. Figure 5?b? shows that the ratio of ob-
served d? to predicted D? values is consistent with the
percentages passing the chi-squared test. Tactile frequency
conditions of 125 and 250 Hz were best predicted by the
ASM ?with ratios close to 1? while conditions in which the
tactile frequency was equal to 50 or 400 Hz were best pre-
dicted by the OSCM or PSM, respectively.
For Experiment 3, in which the auditory and tactile fre-
quencies were equal and covaried ?Figs. 4?a? and 4?b??, the
ASM best fit the observations for the 125 and 250 Hz con-
ditions, with 57% and 88% passing the chi-squared tests,
respectively. In the 125 Hz condition, five out of seven of the
failures are due to ASM under-prediction. In the 50 Hz con-
dition, the PSM best fit the data with 94% of observations
passing the chi-squared test, with no under-predictions for
either PSM or ASM. In the 400 Hz condition, each model
scored the same percentage of observations passing the chi-
squared test ?63%?. However, all three models under-
predicted the observations and of the six ASM failures, three
are due to model under-prediction. Figure 5?c? shows a simi-
lar trend such that the ASM was most accurate in predicting
FIG. 5. ?Color online? Ratio of the observed d? values to the Predicted D? values for each of the three models averaged across subjects and repetitions of each
experimental condition. ?a? Ratios for Experiment 1, in which the tactile frequency=250 Hz and the auditory frequency was varied between 125 and 2000 Hz.
?b? Ratios for Experiment 2, in which the auditory frequency=250 Hz and the tactile frequency was varied between 50 and 400 Hz. ?c? Ratios for Experiment
3, in which the auditory and tactile frequencies were equal and covaried between 50 and 400 Hz. The horizontal bar on each graph indicates a ratio of 1.0 ?i.e.,
observed=predicted values?. The dark gray bars represent the optimal single channel model, the gray bars represent the Pythagorean sum model, and the light
gray bars represent the Algebraic sum model. Error bars are 1 SEM.
J. Acoust. Soc. Am., Vol. 127, No. 5, May 2010Wilson et al.: Auditory-tactile integration: Frequency 3053
the observations when the auditory and tactile frequencies
were equal to 125, 250, and 400 Hz, but that the PSM was
the most accurate in predicting the observations when the
stimulus frequencies were equal to 50 Hz.
A. Effects of frequency separation
Effects of the frequency of stimulation on auditory-
tactile integration of signals presented at near-threshold lev-
els were observed in each of the three experiments. Such
effects were present both for signal detectability ?as mea-
sured in percent-correct scores? of the combined A+T stimu-
lus and for best fits to different models of integration. Gen-
erally, a tendency was observed for higher rates of detection
of the combined-modality stimulus when the stimulating fre-
quencies in the two modalities were equal or close to one
another, and for lower rates of detection as the frequency
separation of the auditory and tactile stimuli increased. Fur-
thermore, the ASM ?indicative of within-channel integration?
provided a better fit to the data when the auditory and tactile
stimulating frequencies were equal or close to one another
compared to a better fit of the PSM ?indicative of cross-
channel integration? for larger frequency spacings. Measure-
ments of the detectability of purely auditory stimulus pairs
?Appendix? gave similar results to our measurements of
auditory-tactile stimuli, with the exception of the ?125, 250?
Hz condition. Apparently the auditory separation, roughly 3
equivalent rectangular bandwidths ?ERBs? ?Moore et al.,
1990?, is effectively greater than the tactile separation.
A baseline condition employing 250 Hz stimulation in
both auditory and tactile modalities was included in each of
the three experiments, as it was in Wilson et al., 2009. The
results of this condition, which are in good agreement with
those reported by Wilson et al. ?2009?, indicate a roughly 15
percentage-point increase in the percent-correct score for A
+T compared with A-alone or T-alone. On average, A+T
performance on the baseline condition was well modeled by
the within-channel integration process of the ASM.
The baseline measurement was extended in Experiment
3 where the auditory and tactile stimulating frequencies were
set equal to one another but took on values of 50, 125, and
400 Hz in addition to the original baseline value of 250 Hz.
The results of this experiment indicate detection rates of the
A+T stimulus at 125 and 400 Hz that are equivalent to those
at 250 Hz ?i.e., roughly 86% correct? and that are well mod-
eled by the within-channel model of integration ?ASM?. At
the 50 Hz frequency, however, average performance on the
A+T condition ?78% correct? was lower than for the remain-
ing three frequencies and was best modeled by the cross-
channel model of integration ?PSM?, with only two of the
four subjects showing ASM-type integration. Whereas the
three higher frequencies ?125, 250, and 400 Hz? are well
within the range of the Pacinian receptor system ?Verrillo,
1963; Hamer et al., 1983?, at 50 Hz it is likely that the
non-Pacinian and Pacinian receptors may also convey as-
pects of the tactile stimulus: the non-Pacinian receptors re-
spond robustly for frequencies less than 50 Hz ?“flutter”? and
Pacinian receptors respond robustly for frequencies greater
than 50 Hz ?“vibration”?.
Intersubject differences observed at 50 Hz may be in-
dicative of differences in tactile physiology. In fact, the ob-
servation that two of the four subjects ?S10and S18? showed
sizable A+T scores ??85% correct?, when both frequencies
were equal to 50 Hz while two others ?S6and S22? did not,
suggests that the cross-over point between the non-Pacinian
and Pacinian receptors may be different across individuals.
Those subjects with high A+T scores at 50 Hz may have a
cross-over point lower in frequency than those subjects
whose A+T scores at 50 Hz were similar to single-modality
scores. Additional data collected on subject S6at 60 and 75
Hz corroborates this claim: at 50 and 60 Hz, responses to the
combined A+T stimulus were approximately 77% correct,
but at 75 Hz, combined responses were approximately 90%
correct. This result suggests a cross-over frequency between
non-Pacinian and Pacinian receptors somewhere in the range
of 60–75 Hz for this subject.
When different auditory frequencies were combined
with a 250 Hz tactile signal ?Experiment 1?, A+T scores
were similar for auditory values of 125, 500, 1000, and 2000
Hz and, on average, were lower than that obtained for the
equal-frequency 250 Hz auditory condition. For the nonequal
frequency conditions ?with the exception of 2000 Hz?, mul-
timodal performance was over-predicted by the PSM but
under-predicted by the ASM, whereas the ASM provided an
excellent fit to the baseline condition. Unexpectedly, average
performance for the condition with an auditory frequency of
2000 Hz was also well modeled by the ASM. Individual-
subject differences were observed on this condition, indicat-
ing that the results of one subject ?S14? were well modeled by
the OCSM while that of two other subjects ?S1and S10? were
well modeled by the ASM. No obvious explanation for these
intersubject differences is apparent.
When different tactile stimulating frequencies were
combined with an auditory frequency of 250 Hz ?Experiment
2?, integration of the two stimuli was similar for tactile fre-
quencies of 125 and 250 Hz ?indicating within-channel inte-
gration predicted by the ASM? but was less effective for
tactile frequencies of 50 and 400 Hz. The integration effects
with a 400 Hz tactile signal were fairly well modeled with
the PSM whereas those with a 50 Hz signal were closer to
the OSCM. In comparing the results of Experiments 1 and 2,
one can conclude that the filtering in Experiment 1 is similar
to auditory critical-band filtering whereas a broader tactile
filter is implied by the results of Experiment 2.
B. Comparisons with previous studies
Other perceptual studies have explored the frequency
relationship between the auditory and tactile stimuli through
“roughness judgments.” For example, the “parchment-skin
illusion” ?Jousmäki and Hari, 1998; Guest et al., 2002? dem-
onstrates that the percept of tactile roughness can be modu-
lated by manipulating the high- frequency components of the
auditory signal. The attenuation of high frequencies results in
a “less rough” percept of the tactile stimuli compared to no
3054 J. Acoust. Soc. Am., Vol. 127, No. 5, May 2010Wilson et al.: Auditory-tactile integration: Frequency
manipulation, whereas the amplification of high-frequency
components leads to a percept of greater roughness com-
pared to the baseline condition.
Two recent perceptual studies have reported effects of
frequency-discrimination tasks performed in the presence of
auditory “distracter” tones ?Ro et al., 2009; Yau et al., 2009?.
Ro et al. ?2009? examined the ability to discriminate between
100 Hz and 200 Hz vibratory stimuli using a one-interval,
2AFC procedure for stimulus presentations that included tac-
tile stimulation alone and tactile stimulation in conjunction
with a synchronous auditory tone of 100 or 200 Hz. The
tactile stimuli were 250 ms in duration and were presented at
levels that were subjectively matched to produce a “moder-
ately intense percept” through a piezoelectric element at the
dorsal surface of the left hand. The auditory stimuli, which
were also 250 ms in duration, were presented through a loud-
speaker located in front of the subject’s left hand at a level of
roughly 60 dB SPL. The mean hit rates were 0.62 for the
tactile-alone stimulus presentations, 0.74 for presentations
with equal-frequency auditory and tactile tones, and 0.43 for
presentations with different-frequency auditory and tactile
tones. Thus, performance was aided by the presence of audi-
tory tones matched in frequency to the tactile sinusoids but
declined in the presence of incongruous auditory tones. In
fact, performance appears to be substantially worse than that
expected on the basis of chance alone for the incongruous
conditions. For the 200 Hz tactile, 100 Hz auditory condi-
tion, the hit rate was only 0.37, suggesting that subjects were
able to discriminate the stimuli but reversed their corre-
sponding response labels of “high” and “low.” Thus, the 100
Hz auditory tone appears to have lowered the perception of
the higher-frequency tactile signal.
Yau et al. ?2009? used a 2I, 2AFC procedure to measure
frequency discrimination for 1 s sinusoidal tactile signals
presented to the right index finger. For a 200 Hz standard
tactile stimulus ?delivered over a contactor with 1 mm diam-
eter?, tactile comparison stimuli were seven sinusoids that
were equally spaced in frequency over the range of 100–300
Hz and whose levels were equated for perceived intensity
with the 200 Hz standard ?whose level was 11.2 ?m?. On
most trials of the experiment, an auditory tone ?one of eight
values in the range of 100–1500 Hz with individual-tone
levels in the range of 56.5–76.4 dB SPL selected to be
equated for loudness? was presented synchronously with the
comparison stimulus. ?Although absolute thresholds for the
tactile and auditory stimuli were not reported in this study, it
is reasonable to assume that all signals were substantially
above threshold—see discussion of tactile thresholds in Sec.
III A of the current paper.? The remaining trials, conducted
without the auditory “distracter” tones, were used to estab-
discrimination task. The psychometric functions showed a
significant reduction in sensitivity ?i.e., ?F for 73% correct
performance? compared to baseline performance only for
those auditory distracters that were less than or equal to 300
Hz and a significant change in bias ?i.e., the point of per-
ceived subjective equality? for auditory distracters of 100 Hz
only. An analogous frequency-discrimination experiment
for thetactile frequency-
conducted with a 400 Hz tactile standard stimulus ?delivered
over a contactor with 8 mm diameter at a level of 1 ?m?
indicated a significant reduction in sensitivity for auditory
distracters in the range of 100–400 Hz and changes in bias
for auditory tones of 100–300 Hz. Thus, these results suggest
a significant interaction between auditory and tactile stimuli
that are similar in frequency in performing a tactile
frequency-discrimination task. No such effects of the fre-
quency of auditory distracter tones were observed, however,
in a tactile intensity-discrimination task employing either a
100 Hz standard ?at a level of 14.2 ?m and comparisons in
the range of 7.1–21.4 ?m? or a 200 Hz standard ?at a level
of 7.6 ?m and comparisons in the range of 3.8 to 11.5 ?m?.
The psychometric functions derived from trials with each of
the auditory distracter frequencies were nondistinguishable
from those of the baseline trials with no auditory distractors.
Substantial differences in approach exist between the de-
tection experiments described in the current paper and the
frequency-discrimination experiments of Ro et al. ?2009?
and Yau et al. ?2009?. In the detection experiments ?con-
ducted near threshold?, both the auditory and tactile stimuli
in the A+T condition are relevant to performing the task
whereas in the tactile frequency-discrimination experiments
?conducted at suprathreshold levels? only the T stimulus is
task relevant during A+T presentations. However, both ap-
proaches suggest that the frequency of stimulation within
each of the two modalities affects performance on A+T con-
ditions. In the case of the tactile frequency-discrimination
experiments conducted by Yau et al. ?2009?, performance on
a 200 Hz tactile target was affected only by the presence of
auditory frequencies in the range of 100–300 Hz and on a
400 Hz tactile target by auditory frequencies in the range of
100–400 Hz. Thus, similar to our results in Experiments 1
and 2, perceptual interactions appear to be greater when the
frequencies of A and T are more closely spaced and further-
more when both frequencies are within the Pacinian range.
The results of Yau et al. ?2009? indicate that subjects
were able to effectively ignore interactions of the auditory
and tactile tones in performing the intensity-discrimination
task but not the frequency-discrimination task. In the case of
intensity discrimination, Weber’s law predicts an increase in
?I with an increase in the level of the standard stimulus that
would arise from integration of the auditory and tactile
stimuli; thus, subjects may choose to ignore the auditory in-
tensity component in order to maximize their performance.
In the case of tactile frequency discrimination, however, per-
formance was strongly affected by the presence of auditory
frequencies in the Pacinian range ?i.e., below 300 or 400
Hz?. In fact, our own analysis of the data of Yau et al. ?2009?
suggests that performance in the presence of these distracters
closely matches what would be predicted from the baseline
function for a comparison tone that is the average of the
frequency of the tactile comparison tone and the auditory
distracter. A similar averaging operation may also be inferred
from the results of Ro et al. ?2009?, described above.
J. Acoust. Soc. Am., Vol. 127, No. 5, May 2010 Wilson et al.: Auditory-tactile integration: Frequency3055
C. Tonotopy, filtering, and pathways in the auditory
and tactile systems
Tonotopic mapping from the brainstem to the cortex has
been demonstrated in neurophysiological studies with ani-
mals ?for a review see Schreiner et al., 2000? as well as in
imaging studies of the human auditory cortex ?Romani et al.,
1982; Bilecen et al., 1998; Talavage et al., 2000; Talavage et
al., 2004?. In the perceptual domain, a variety of experiments
have shown that the auditory system exhibits critical-band
filtering ?e.g., Moore et al., 1990; Zwicker, 1961; Green-
wood, 1961?. Interaction of multiple auditory stimuli is
greatest when those two stimuli fall within a single critical
band, and decreases as the frequency separation between
them increases ?i.e., as they fall into separate critical bands?.
The peripheral tactile receptor system has also been
shown to respond to different ranges of frequencies: a “non-
Pacinian” channel responding to frequencies ranging from
less than 1 to approximately 50 Hz, and a Pacinian channel,
responding to frequencies ranging from approximately 50–
500 Hz ?Verrillo, 1963; Verrillo et al., 1983; Hamer et al.,
1983; Bolanowski et al., 1988; Morley and Rowe, 1990;
Formby et al., 1992; Gescheider et al., 2001; Gescheider et
al., 2002?. There is also some evidence for possible fre-
quency selectivity at the level of the somatosensory cortex.
The primary somatosensory cortex responds to frequencies
in the “flutter” range ?i.e., frequencies less than 50 Hz: Harris
et al., 2006; Hegner et al., 2007? while the secondary soma-
tosensory cortex responds to frequencies in the “vibration”
range ?i.e., frequencies between 50 and 500 Hz: Francis et
al., 2000; Harrington and Downs, 2001; Iguchi et al., 2007?.
The results of other studies, however, suggest that a fre-
quency organization in S1 may not exist in humans ?Hash-
imoto et al., 1999? or in animal models ?Romo et al., 1998;
Romo et al., 2000; Hernandez et al., 2000; Luna et al., 2005;
de Lafuente and Romo, 2005?. Psychophysical studies have
also shown evidence of “critical-band” filtering in the tactile
system although over a frequency range that is greatly com-
pressed compared to that of the auditory system ?Marks,
1979; Makous et al., 1995?.
Given that recent anatomical studies have shown that the
somatosensory system projects to the auditory system
?Cappe and Barone, 2005? and that physiological studies
have shown that these two sensory systems interact with one
another in the auditory cortex ?Schroeder et al., 2001; Foxe
et al., 2002; Schürmann et al., 2006?, our data suggest the
possibility of a cross-modal tonotopic mapping. The results
from Experiments 1–3 indicate that critical-band filtering is
exhibited in both the auditory and somatosensory systems
and that these filters interact with one another across the
different sensory modalities. In comparing the results of Ex-
periments 1 and 2, our data suggest that the auditory and
somatosensory filters are of different shapes, with the audi-
tory filters being more sharply defined than those of the tac-
Our modeling results are suggestive of different ana-
tomical pathways for cross-modal integration depending on
the frequencies of the A and T stimuli. When auditory and
tactile stimulus frequencies are similar to each other and
within the Pacinian range, cross-modal scores are well mod-
eled by the ASM. A pathway for within-channel integration
may occur through ascending somatosensory inputs to early
auditory centers in the brainstem and thalamus. Auditory and
tactile sensations may be integrated at these early levels be-
fore their combination reaches the auditory cortex. When
auditory and tactile frequencies of stimulation are farther
apart, cross-modal scores tend to be well modeled by the
PSM, suggesting cross-channel integration. A potential ana-
tomical pathway for this type of integration may be the as-
cending inputs to the somatosensory cortex, which then
project to the auditory cortex. Interactions between auditory
and tactile stimuli would take place at the level of the cortex
using input derived from independent pathways for each mo-
It has been suggested that the inner ear evolved out of
the skin as a highly frequency-specific responder ?Fritzsch
and Beisel, 2001; Fritzsch et al., 2007?. The tactile system
may thus serve to extend the range of low-frequency hearing
where sensitivity to auditory signals is not as good as at
higher frequencies. Recent research suggests that in large
mammals such as elephants and lions, vibrational events in
the ground may be used for communication ?O’Connell-
Rodwell et al., 2001?. In this light, the tactile and auditory
systems could represent a continuum of detectable frequen-
cies, with one sense picking up where the other one leaves
V. SUMMARY AND CONCLUSIONS
Our experiments have shown that the detection of com-
binations of near-threshold auditory and tactile stimuli is de-
pendent on the frequencies of stimulation employed within
each modality. When stimulating frequencies in the two mo-
dalities are equal or close to one another, detection rates tend
to be higher than for combinations employing larger differ-
ences in frequency. Observed auditory-tactile performance
was compared to the predictions of three different models of
integration using single-modality scores as input. Different
types of integration were observed with different combina-
tions of auditory and tactile stimuli. In particular, the within-
channel integration of the ASM provided a close fit to data
for conditions in which the auditory and tactile stimulating
frequencies were equal or close to one another and were
within the Pacinian frequency range. The cross-channel inte-
gration of the PSM tended to provide the best fit to condi-
tions with larger frequency spacings. Little integration of any
type was observed for 50 Hz stimulation in both modalities,
suggesting that integrative effects may not extend to fre-
quency regions conveyed by non-Pacinian receptors.
Further research is being conducted on auditory-tactile
integration with suprathreshold stimuli and concerned in par-
ticular with the relation between frequency spacing and loud-
ness. In the auditory domain, it is well established that two-
tone stimuli that lie within a critical band are more
effectively integrated as far as detection is concerned than
two tones that lie in different critical bands. This effect is
similar to that observed in our experiments with auditory and
tactile stimuli: detection is higher when the frequencies of
the auditory and tactile stimuli are equal or closely spaced
3056 J. Acoust. Soc. Am., Vol. 127, No. 5, May 2010Wilson et al.: Auditory-tactile integration: Frequency
than when they are farther apart. For loudness, on the other
hand, two auditory tonal stimuli are louder when they oc-
cupy different critical bands than when they lie within the
same critical band. It will be important to determine whether
the frequency spacing of auditory and tactile stimuli has a
similar effect on perceived strength of combined auditory-
Research was supported by grants from the National In-
stitutes of Health Grant Nos. 5T32-DC000038, R01-
DC000117, and R01-DC00126, and a Hertz Foundation Fel-
lowship ?ECW?. We also wish to acknowledge the
contributions of Jing Wang and Catherine McCurry to this
study, and to thank the Associate Editor and reviewers for
their helpful comments.
APPENDIX: AUDITORY NARROWBAND NOISE
COMBINED WITH AUDITORY PURE TONES
To test our methods we conducted a purely auditory ex-
periment as a complement to Experiment 1, in which an
auditory NBN of bandwidth 48 Hz and centered on 250 Hz
was substituted for the tactile stimulus. This experiment was
conducted on five audiometrically normal subjects ?three fe-
males; age range of 19–59 years?. Each subject completed
four repetitions of the experimental conditions. One subject
?S12? was disqualified after testing because of abnormally
high threshold levels for the pure tones. The auditory pure
tone ?PT? frequencies used were the same as in Experiment
1: 125, 250, 500, 1000, and 2000 Hz. The level of the nar-
rowband noise was determined by the same procedure that
was used to determine the levels of the tones ?see Sec. II D?.
Figure 6 shows the results of the detection experiment.
At threshold, percent-correct values for a single stimulus
?PT-alone and NBN-alone? ranged from 69.8% correct
?NBN? to 73% correct ?1000 Hz tone?. In the combined PT
+NBN presentations, the highest percent-correct score was
obtained when the tone was 250 Hz ?87.8% correct?, while
the response levels were lower for other PT frequencies.
A two-way ANOVA was performed on the arcsine-
transformed percent-correct scores with main factors of con-
dition ?NBN-alone, PT-alone, and NBN+PT? and subject.
The results of the ANOVA indicate significant main effects
for condition ?F?14,180?=18.04, p?0.01? and subject
?F?3,180?=11.87, p?0.01? as well as a significant interac-
tion between them ?F?42,180?=2.65, p?0.01?. A post hoc
Tukey–Kramer analysis of the condition effect indicated that
?i? all of the NBN-alone and PT-alone scores were statisti-
cally equivalent, ?ii? NBN+250 scores were significantly
higher than scores on all other conditions, ?iii? scores on the
remaining four NBN+PT conditions were not significantly
different from each other, and ?iv? NBN+125 and NBN
+2000 scores were significantly greater than scores on all
NBN-alone and PT-alone conditions but that scores on
NBN+500 and NBN+1000 were not significantly higher
than the NBN-alone and PT-alone scores. A post hoc analysis
of the main effect for subject indicated the following signifi-
cant differences: the scores of S6were significantly lower
than those of S10and S19, the scores of S15were significantly
lower than those of S10, the scores of S19were significantly
higher than those of S6, and the scores of S10were signifi-
cantly higher than those of all other subjects. The interaction
effect arises in part from different patterns of performance
among subjects on the NBN+1000 and NBN+2000 condi-
The responses were analyzed in terms of the three mod-
els ?OSCM, PSM, and ASM? discussed in Sec. III F. The
PSM best fit the results of conditions 125 and 500 Hz ?both
with 94% passing the chi-squared test?. The ASM best fit the
results of the 250 Hz condition ?with 75% passing?, while the
OSCM best fit the 1000 and 2000 Hz conditions ?with 69%
and 81% passing, respectively?.
The results of the three studies reviewed in Sec. I B are
fairly consistent with ours if one assumes that the ASM ap-
plies to frequency separations less than 0.3 ERB ?Moore et
al., 1990?, the PSM to separations between 0.4 and 5 ERB,
and the OSCM to separations greater than roughly 11 ERB.
The studies give conflicting results for separations of 5.5–
10.4 ERB, with the findings of Green ?1958? supporting the
PSM rule, while our results and those of Marill ?1956? sup-
port the OCSM rule.
1For subjects who participated in more than one experiment ?S1, S6, and
S10?, this baseline condition was not repeated for each experiment. For S1,
the baseline condition was measured in Experiment 1 only and the same
data were used for Experiment 2. For S6, the baseline condition was mea-
sured in Experiment 1; for Experiments 2 and 3, the baseline data used
measurements for this subject taken previously by Wilson et al. ?2009?.
For subject S10, the baseline condition was measured for Experiments 1
and 3; for Experiment 2, baseline data were taken from measurements
made previously by Wilson et al. ?2009?.
2Subjects S1, S6, and S10participated in an earlier study ?Wilson et al.,
2009? and received their three training sessions at that time in the baseline
3We denote d? values that can be estimated directly from the data using
lower case ?d??, and d? values that are predicted by models by upper case
FIG. 6. % correct scores averaged across four subjects and four repetitions
per condition. Scores are shown for auditory PTs alone ?white bars?, audi-
tory NBN alone ?light gray bars?, and for combined PT+NBN ?dark gray
bars?. Scores are shown as a function of auditory PT frequency with NBN
centered at 250 Hz and bandwidth of 48 Hz. Error bars are 1 SEM.
J. Acoust. Soc. Am., Vol. 127, No. 5, May 2010 Wilson et al.: Auditory-tactile integration: Frequency 3057
Bilecen, D., Scheffler, K., Schmid, N., Tschopp, K., and Seelig, J. ?1998?. Download full-text
“Tonotopic organization of the human auditory cortex as detected by
BOLD-FMRI,” Hear. Res. 126, 19–27.
Bolanowski, S. J., Gescheider, G. A., and Verrillo, R. T. ?1988?. “Four
channels mediate the mechanical aspects of touch,” J. Acoust. Soc. Am.
Braida, L. D. ?1991?. “Crossmodal integration in the identification of con-
sonant segments,” Q. J. Exp. Psychol. 43A, 647–677.
Cappe, C., and Barone, P. ?2005?. “Heteromodal connections supporting
multisensory integration at low levels of cortical processing in the mon-
key,” Eur. J. Neurosci. 22, 2886–2902.
Dadson, R. S., and King, J. H. ?1952?. “A determination of the normal
threshold of hearing and its relation to the standardization of audiom-
eters,” J. Laryngol. Otol. 66, 366–378.
de Lafuente, V., and Romo, R. ?2005?. “Neuronal correlates of subjective
sensory experience,” Nat. Neurosci. 8, 1698–1703.
Fletcher, H. ?1940?. “Auditory patterns,” Rev. Mod. Phys. 12, 47–65.
Fletcher, H., and Wegel, R. L. ?1922?. “The frequency-sensitivity of normal
ears,” Proc. Natl. Acad. Sci. U.S.A. 8, 5–6.2.
Formby, C., Morgan, L. N., Forrest, T. G., and Raney, J. J. ?1992?. “The role
of frequency selectivity in measures of auditory and vibrotactile temporal
resolution,” J. Acoust. Soc. Am. 91, 293–305.
Foxe, J. J., Wylie, G. R., Martinez, A., Schroeder, C. E., Javitt, D. C.,
Guilfoyle, D., Ritter, W., and Murray, M. M. ?2002?. “Auditory-
somatosensory multisensory processing in auditory association cortex: An
fMRI study,” J. Neurophysiol. 8, 540–543.
Francis, S. T., Kelly, E. F., Bowtell, R., Dunseath, W. J. R., Foger, S. E., and
McGlone, F. ?2000?. “fMRI of the responses to vibratory stimulation of
digit tips,” Neuroimage 11, 188–202.
Fritzsch, B., and Beisel, K. W. ?2001?. “Evolution of the nervous system,”
Brain Res. Bull. 55, 711–721.
Fritzsch, B., Beisel, K. W., Pauley, S., and Soukup, G. ?2007?. “Molecular
evolution of the vertebrate mechanosensory cell and ear,” Int. J. Dev. Biol.
Gescheider, G. A. ?1970?. “Some comparisons between touch and hearing,”
IEEE Trans. Man-Machine Syst. 11, 28–35.
Gescheider, G. A., Barton, W. G., Bruce, M. R., Goldberg, J. H., and
Greenspan, M. J. ?1969?. “Effects of simultaneous auditory stimulation on
the detection of tactile stimuli,” J. Exp. Psychol. 81, 120–125.
Gescheider, G. A., Bolanowski, S. J., and Hardick, K. R. ?2001?. “The
frequency selectivity of information-processing channels in the tactile sen-
sory system,” Somatosens. Mot. Res. 18, 191–201.
Gescheider, G. A., Bolanowski, S. J., Pope, J. V., and Verrillo, R. T. ?2002?.
“A four-channel analysis of the tactile sensitivity of the fingertip: Fre-
quency selectivity, spatial summation, and temporal summation,” Soma-
tosens. Mot. Res. 19, 114–124.
Gillmeister, H., and Eimer, M. ?2007?. “Tactile enhancement of auditory
detection and perceived loudness,” Brain Res. 1160, 58–68.
Green, D. M. ?1958?. “Detection of multiple component signals in noise,” J.
Acoust. Soc. Am. 30, 904–911.
Greenwood, P. D. ?1961?. “Auditory masking and the critical band,” J.
Acoust. Soc. Am. 33, 484–502.
Grose, J. H., and Hall, J. W., III ?1997?. “Multiband detection of energy
fluctuations,” J. Acoust. Soc. Am. 102, 1088–1096.
Guest, S., Catmur, C., Lloyd, D., and Spence, C. ?2002?. “Audiotactile in-
teractions in roughness perception,” Exp. Brain Res. 146, 161–171.
Hamer, R. D., Verrillo, R. T., and Zwislocki, J. J. ?1983?. “Vibrotactile
masking of Pacinian and non-Pacinian channels,” J. Acoust. Soc. Am. 73,
Harrington, G. S., and Downs, J. H., III ?2001?. “FMRI mapping of the
somatosensory cortex with vibratory stimuli. Is there a dependency on
stimulus frequency?” Brain Res. 897, 188–192.
Harris, J. A., Arabzadeh, E., Fairhall, A. L., Benito, C., and Diamond, M. E.
?2006?. “Factors affecting frequency discrimination of vibrotactile stimuli:
Implications for cortical encoding,” PLoS Biol. 1, 1–9.
Hashimoto, I., Saito, Y., Iguchi, Y., Kimura, T., Fukushima, T., Terasaki, O.,
and Sakuma, K. ?1999?. “Frequency representation in the human hand
somatosensory cortex: A reappraisal,” NeuroReport 10, 959–963.
Hawkins, J. E., and Stevens, S. S. ?1950?. “The masking of pure tones and
of speech by white noise,” J. Acoust. Soc. Am. 22, 6–13.
Hegner, Y. L., Saur, R., Veit, R., Butts, R., Leiberg, S., Grodd, W., and
Braun, C. ?2007?. “BOLD adaptation in vibrotactile stimulation: Neuronal
networks involved in frequency discrimination,” J. Neurophysiol. 97,
Hernandez, A., Zainos, A., and Romo, R. ?2000?. “Neuronal correlates of
sensory discrimination in the somatosensory cortex,” Proc. Natl. Acad.
Sci. U.S.A. 97, 6191–6196.
Houtsma, A. J. ?2004?. “Hawkins and Stevens revisited with insert ear-
phones,” J. Acoust. Soc. Am. 115, 967–970.
Iguchi, Y., Hoshi, Y., Nemoto, M., Taira, M., and Hashimoto, I. ?2007?.
“Co-activation of the secondary somatosensory and auditory cortices fa-
cilitates frequency discrimination of vibrotactile stimuli,” Neuroscience
Jousmäki, V., and Hari, R. ?1998?. “Parchment-skin illusion: Sound-biased
touch,” Curr. Biol. 8, R190.
Lamoré, P. J., Muijser, H., and Keemijik, C. J. ?1986?. “Envelope detection
of amplitude-modulated high-frequency sinusoidal signals by skin mecha-
noreceptors,” J. Acoust. Soc. Am. 79, 1082–1085.
Luna, R., Hernandez, A., Brody, C. D., and Romo, R. ?2005?. “Neural codes
for perceptual discrimination in primary somatosensory cortex,” Nat. Neu-
rosci. 8, 1210–1219.
Makous, J. C., Friedman, R. M., and Vierck, C. J., Jr. ?1995?. “A critical
band filter in touch,” J. Neurosci. 15, 2808–2818.
Marill, T. ?1956?. “Detection theory and psychophysics,” Technical Report
No. 319, Research Laboratory of Electronics, MIT, Cambridge, MA.
Marks, L. E. ?1979?. “Summation of vibrotactile intensity: An analog to
auditory critical bands?,” Sens. Processes 3, 188–203.
Moore, B. C. J., Peters, R. W., and Glasberg, B. R. ?1990?. “Auditory filter
shapes at low center frequencies,” J. Acoust. Soc. Am. 88, 132–140.
Morley, J. W., and Rowe, M. J. ?1990?. “Perceived pitch of vibrotactile
stimuli: Effects of vibration amplitude, and implications for vibration fre-
quency coding,” J. Physiol. ?London? 431, 403–416.
Neville, A. M., and Kennedy, J. B. ?1964?. Basic Statistical Methods for
Engineers and Scientists ?International Textbook Co., Scranton, PA?, p.
O’Connell-Rodwell, C. E., Hart, L. A., and Arnason, B. T. ?2001?. “Explor-
ing the potential use of seismic waves as a communication channel by
elephants and other large mammals,” Am. Zool. 41, 1157–1170.
Rabinowitz, W. M., Houtsma, A. J., Durlach, N. I., and Delhorne, L. A.
?1987?. “Multidimensional tactile displays: Identification of vibratory in-
tensity, frequency and contactor area,” J.Acoust. Soc.Am. 82, 1243–1252.
Ro, T., Hsu, J., Yasar, N. E., Elmore, L. C., and Beauchamp, M. S. ?2009?.
“Sound enhances touch perception,” Exp. Brain Res. 195, 135–143.
Romani, G. L., Williamson, S. J., and Kaufman, L. ?1982?. “Tonotopic or-
ganization of the human auditory cortex,” Science 216, 1339–1340.
Romo, R., Hernandez, A., Zainos, A., Brody, C. D., and Lemus, L. ?2000?.
“Sensing without touching: Psychophysical performance based on cortical
microstimulation,” Neuron 26, 273–278.
Romo, R., Hernandez, A., Zainos, A., and Salinas, E. ?1998?. “Somatosen-
sory discrimination based on cortical microstimulation,” Nature ?London?
Schnupp, J. W. H., Dawe, K. L., and Pollack, G. ?2005?. “The detection of
multisensory stimuli in an orthogonal sensory space,” Exp. Brain Res.
Schreiner, C. E., Read, H. L., and Sutter, M. L. ?2000?. “Modular organiza-
tion of frequency integration in primary auditory cortex,” Annu. Rev. Neu-
rosci. 23, 501–529.
Schroeder, C. E., Lindskey, R. W., Specht, C., Marcovici, A., Smiley, J. F.,
and Javitt, D. C. ?2001?. “Somatosensory input to auditory association
cortex in the macaque monkey,” J. Neurophysiol. 85, 1322–1327.
Schürmann, M., Caetano, G., Hlushchuk, Y., Jousmaki, V., and Hari, R.
?2006?. “Touch activates human auditory cortex,” Neuroimage 30, 1325–
Schürmann, M., Caetano, G., Jousmaki, V., and Hari, R. ?2004?. “Hands
help hearing: Facilitatory audiotactile interaction at low sound-intensity
levels,” J. Acoust. Soc. Am. 115, 830–832.
Talavage, T. M., Ledden, P. J., Benson, R. R., Rosen, B. R., and Melcher, J.
R. ?2000?. “Frequency-dependent responses exhibited by multiple regions
in human auditory cortex,” Hear. Res. 150, 225–244.
Talavage, T. M., Sereno, M. I., Melcher, J. R., Ledden, P. J., Rosen, B. R.,
and Dale, A. M. ?2004?. “Tonotopic organization in human auditory cortex
revealed by progressions of frequency sensitivity,” J. Neurophysiol. 91,
Verrillo, R. T. ?1963?. “Effect of contactor area on the vibrotactile thresh-
old,” J. Acoust. Soc. Am. 35, 1962–1966.
Verrillo, R. T., Gescheider, G. A., Calman, B. G., and Van Doren, C. L.
?1983?. “Vibrotactile masking: Effect of one- and two-site stimulation,”
Percept. Psychophys. 33, 379–387.
3058 J. Acoust. Soc. Am., Vol. 127, No. 5, May 2010 Wilson et al.: Auditory-tactile integration: Frequency