ORIGINAL RESEARCH ARTICLE
published: 11 December 2012
doi: 10.3389/fpsyg.2012.00545

Illusory reversal of causality between touch and vision has
no effect on prism adaptation rate
Hirokazu Tanaka 1 *, Kazuhiro Homma 2 and Hiroshi Imamizu 3,41

School of Information Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan
Nagaoka University of Technology, Niigata, Japan
3
Center for Information and Neural Networks, National Institute of Information and Communications Technology, Osaka, Japan
4
Cognitive Mechanisms Laboratories, Advanced Telecommunication Research Institute International, Kyoto, Japan
2

Edited by:
Rufin VanRullen, Centre de Recherche
Cerveau et Cognition, France
Reviewed by:
Makoto Miyazaki, Yamaguchi
University, Japan
Makoto Ichikawa, Chiba University,
Japan*Correspondence:
Hirokazu Tanaka, School ofInformation Science, Japan Advanced
Institute of Science and Technology,
Asahidai 1-1, Nomi, Ishikawa
923-1291, Japan.
e-mail: hirokazu@jaist.ac.jp

Learning, according to Oxford Dictionary, is “to gain knowledge or skill by studying, fromexperience, from being taught, etc.” In order to learn from experience, the central nervous
system has to decide what action leads to what consequence, and temporal perception
plays a critical role in determining the causality between actions and consequences. In
motor adaptation, causality between action and consequence is implicitly assumed so thata subject adapts to a new environment based on the consequence caused by her action.
Adaptation to visual displacement induced by prisms is a prime example; the visual error
signal associated with the motor output contributes to the recovery of accurate reaching,
and a delayed feedback of visual error can decrease the adaptation rate. Subjective feelingof temporal order of action and consequence, however, can be modified or even reversed
when her sense of simultaneity is manipulated with an artificially delayed feedback. Our
previous study (Tanaka et al., 2011; Exp. Brain Res.) demonstrated that the rate of prism
adaptation was unaffected when the subjective delay of visual feedback was shortened.
This study asked whether subjects could adapt to prism adaptation and whether the rate ofprism adaptation was affected when the subjective temporal order was illusory reversed.
Adapting to additional 100 ms delay and its sudden removal caused a positive shift of pointof simultaneity in a temporal order judgment experiment, indicating an illusory reversalof action and consequence. We found that, even in this case, the subjects were able toadapt to prism displacement with the learning rate that was statistically indistinguishable tothat without temporal adaptation. This result provides further evidence to the dissociation
between conscious temporal perception and motor adaptation.
Keywords: motor adaptation, subjective simultaneity, physical simultaneity, temporal adaptation, spatial
adaptation, illusory reversal

INTRODUCTION
Learning from experience implicitly assumes that the temporalorder of an action and a consequence is causally preserved. It isthus natural to expect that action-consequence timing plays animportant role in learning and that a delay in consequence feedback would affect the course of motor learning. Standard theories
for learning sequential tasks assume temporal proximity as a critical factor in determining a causal relationship between actions andconsequences (Sutton and Barto, 1998). In reinforcement learning,for instance, an action and a reward are associated with a socalled eligibility trace that is elicited at the moment of action andis decreased gradually. Another example of action-consequencetiming can be found in motor adaptation to a visual displacement induced by wedge prisms that bend the light path. Initial
movements miss the target by an amount proportional to theprisms diopter, but accurate reaching is gradually recovered withsuccessive trials (Martin et al., 1996). The timing between arm
movements and the feedback of the visual errors plays an essential
role in the rate of prism adaptation. Previous psychophysics studies demonstrated that a short delay of endpoint error feedback

www.frontiersin.org

in prism adaptation decreases the learning rate both in humans(Kitazawa et al., 1995) and monkeys (Kitazawa and Yin, 2002).
Most remarkable was that an almost imperceptibly short delayof 50 ms decreased the learning rate significantly. These results
indicate that the motor system employs an accurate time keeping
system between an action and an outcome during motor control
and motor adaptation.
Recent lines of psychophysical studies, on the other hand, havedocumented that our subjective perception of temporal durationand temporal order is not innately fixed but rather flexibly modifiable after passively exposed to stimuli that are temporally out ofsync with a persistent lag (for review, see Vroomen and Keetels,2010). After adapting to asynchronized stimuli, the psychometriccurve is shifted so that the point of subjective simultaneity (PSS)
moves toward the exposed lag (lag adaptation; Fujisaki et al., 2004)
or away from the exposed lag (Bayesian-like adaptation; Miyazaki
et al., 2006). A recent study demonstrated that, in audiovisual
temporal order judgments (TOJ), Bayesian calibration is at work
behind lag adaptation (Yamamoto et al., 2012), so these adaptation
mechanisms are not mutually exclusive but rather competitive to

December 2012 | Volume 3 | Article 545 | 1

Tanaka et al.

each other. This effect of temporal adaptation has been reported
within a single modality and across multiple modalities, indicating that our sense of timing is not innately determined but instead
flexibly adaptive.
Temporal adaptation is observed not only in passive exposureof cross-modal stimulus pairs but also between voluntary actions
and sensory consequences (Cunningham et al., 2001; Stetson et al.,2006; Heron et al., 2009; Wenke and Haggard, 2009; Keetels andVroomen, 2012), often referred to as intentional binding (Haggard
et al., 2002). Of particular interest is an intriguing perception after
adapting to a delay between an action and a consequence. After
adapting to a visual feedback delay in response to a button press, asudden removal of the delay causes a sensation that the visual feedback occurred in prior to the button press, a phenomenon known
as illusory reversal (Cunningham et al., 2001; Stetson et al., 2006;
Heron et al., 2009). This reversal can be quantitatively evaluatedby comparing psychometric curves in a TOJ experiment. With adelay of 100 ms, the PSS reportedly shifted by 40 ms (Stetson et al.,2006).
An essential question in studying neural temporal processing
is whether there is a single “master clock” that controls timings
regardless of stimulus characteristics (i.e., visual, auditory, or tactile) or there are “distributed clocks” that control timings depending stimulus modalities and/or behavioral contexts (see Buonomano and Karmarkar, 2002 for review). There is experimental
evidence for the master clock hypothesis. Individual differencesin produced intervals for finger and foot movements correlatedwith the acuity of auditory timing judgment (Keele et al., 1985),
indicating common timing systems among perceptual and motor
systems. The distributed-clock hypothesis, on the other hand, is
supported by the finding that the performance of sub-second
interval discrimination tasks was significantly worse when intervals were bounded by intermodal stimuli (i.e., a tone and a flashof light) than when intervals were bounded by unimodal stimuli (i.e., two tones or two flashes of light; Rousseau et al., 1983).
Recently, degrees of temporal adaptation were evaluated with various pairs of multimodal stimuli (auditory/visual, auditory/tactile,and visual/tactile), and adaptation to auditory-visual stimuli waslarger than that to auditory-tactile or visual-tactile pairs (Harrarand Harris, 2008). Both hypotheses thus have been supported byexperimental findings, but in what conditions and contexts thebrain uses a single clock or multiple clocks remains unanswered.
Although temporal perception has long been studied in both
perceptual and motor processing, it is little investigated how temporal perception affects the courses of motor adaptation (Tanaka
et al., 2011; Honda et al., 2012). When temporally associating anaction and a consequence in motor learning, there are two possible timings: subjective and physical timings. Our previous study
asked whether the learning rate in prism adaptation depends on
subjective delay or physical delay (PD; Tanaka et al., 2011). Psychometric curves in a TOJ experiment shifted by about 40 ms after
adapting to a persistent delay of 100 ms of visual feedback stimulus. The learning rate in prism adaptation was not influenced byprior lag adaptation but was predicted by PD (i.e., delay during
a prism adaptation session). Therefore, in that study, subjective
shortening of feedback delay had no effect on the learning rate inprism adaptation. The current study extends our previous study

Frontiers in Psychology | Perception Science

Prism and temporal adaptation

by examining the learning rate in prism adaptation when subjective temporal order between an action and a consequence isillusory reversed. Subjects adapted to a temporal delay (100 ms)
of visual feedback in finger pointing movement, and then adapted
to a visual displacement with the delay removed. This caused anillusory reversal of touching and visual feedback. By evaluating thelearning rate of prism adaptation, the effect of illusory reversal on
motor adaptation was studied.

MATERIALS AND METHODSSUBJECTS

Six right-handed male adults from our institution and a nearby
university (age: 21–46) participated in the experiments. This
study was approved by an institutional ethics committee, anda written consent form was obtained from all subjects. They
reported no known neurological history and had normal orcorrected-to-normal vision.
EXPERIMENTAL SETTING

Detailed descriptions about the experimental setup were found in
our previous study (Tanaka et al., 2011), so a brief summary isprovided here. The experimental setup consisted of a 1700 CRT(85 Hz refresh rate: CV772X, TOTOKU Electric Coop, Tokyo,
Japan) for presenting visual stimuli, a touch screen on the displaythat measured pointed locations (resolution was 3 mm × 3 mm),a custom-made liquid-crystal shutter for controlling the timing ofvisual feedback (Takei Coop, Niigata, Japan), a button for measuring movement onset time, and a mouse for recording subjects’
responses (Figure 1A). The subjects sat comfortably in front of
the desk with their heads stabilized on a chin rest. The distance
between the subject’s face and the CRT screen was 30 cm. Subjects
wore goggles whose glasses were removed and front was covered
with a black cardboard having two holes (each diameter = 1.7 cm;
Figure 1B). The holes restricted subjects’ vision in the central
field (visual angle = 27.3˚). The goggles were worn for all trials
including adaptation and test trials for Experiment 1 and baseline, adaptation, washout trials for Experiment 2. We restricted
the vision to the central field so that the subjects could not see
the edges of the CRT screen; otherwise, the subjects could havenoticed the prism displacement by observing the screen edges. In
the adaptation trials, wedge prisms were put on the goggles covering the holes of the cardboard (Figure 1B) and inducing rightward
visual displacement (15 diopter or 10.7 cm on the screen). The
CRT position was adjusted with or without the prisms so that targets appeared within the central visual field (Figure 1C). Due tothe holes and the position adjustment, the size of the visual field
was constant and independent of existence the prisms. A target was
displayed at a random location (taken from a uniform distribution) in a 4 cm × 4 cm at the center of display. The starting button
was placed 20 cm in front of the screen. The distance between
the button and the center of the display was 30 cm. For visual
stimulus-presentation, recoding of behavioral responses and control of the shutter, in-house Matlab codes (MathWorks, MA, USA)
based on the Psychtoolbox extension (Brainard, 1997; Pelli, 1997).
By using a commercial high-speed digital camera (EX-F1, Casio,
Japan, maximum 1,200 frames per second), we measured a temporal delay from the moment the subject’s finger contacted with theDecember 2012 | Volume 3 | Article 545 | 2

Tanaka et al.

Prism and temporal adaptation

FIGURE 1 | (A) Schematic of experimental setting. (B) Goggles restricting
visual field of subjects. Wedge prisms were put on the goggles in adaptation
conditions. (C) Display locations (gray rectangles) with and without prism,

adjusted so that the target location and the visual feedback fall within thecentral visual field. (D) Time flow of a single trial. ∆t feedback is the interval frommovement completion to visual feedback and is adjusted in various conditions.

touch screen to the moment the visual feedback was made visible tothe subject. When no delay included in the stimulus-presentation
code, the measured delay was 36.4 (SD 5.08) ms. This inevitabledelay was referred to as the minimum delay (MD). When a 100-ms
delay was imposed, the measured delay was 136.4 (SD 4.67) ms.

no visual displacement) was imposed. Before participating in theexperiments, the subjects went through training sessions until they
achieved accuracy (50% of trials with movement error ≤1 cm)
and timing criteria [within both the response-time (200 ms) andmovement-time (250 ms) limits in no less than 90% of trials in asingle training session].

PSYCHOPHYSICAL EXPERIMENTS

Commonly in all conditions described below, the subjects were
instructed, in a single trial, to make a rapid pointing movementwith their right arm as soon as a visual target (a yellow cross,
1 cm × 1 cm) was presented on the screen (Figure 1D). The visionof the hand was provided not during the movement but after the
movement. Several conditions were tested by changing the timingof visual feedback (∆t feedback in Figure 1D) and/or by imposing
the visual displacement with the prisms. The visual feedback wasprovided immediately (36 ms) or with an additional 100 ms delay(thus 136 ms) after the subjects touched the screen. The visualdisplacement was imposed when subjective temporal order wastested in the delay adaptation experiment (Experiment 1) andwhen prism adaptation was measured in the prism adaptation
experiment (Experiment 2). Otherwise, the veridical vision (i.e.,

www.frontiersin.org

Experiment 1: delay adaptation experiment

The first experiment tested whether TOJ adapted in a largeamplitude movement involving full upper-limb movement underconditions of laterally displaced vision. A single session consistedof 60 initial delay adaptation trials (without prism) followed by
20 subsequent test trials (with prism). During the delay adaptation trials the feedback delay was 36 ms for the MD condition
and was 136 ms for the delay adaptation condition. In the test
trials, the delay was the average movement duration during theinitial adaptation trials (t̄movement ) plus a Gaussian random number (mean 0 ms, SD 80 ms), so the visual feedback appeared either
before or after the actual touch on the screen (feedback timings
summarized in Table 1). Subsequently, during the test trials the
subjects reported, with a computer mouse held in their left hands,

December 2012 | Volume 3 | Article 545 | 3

Tanaka et al.

Prism and temporal adaptation

Table 1 | Feedback delays (∆t feedback ) used for the minimum delay andTable 2 | Actual feedback delays used for the minimum delay, physicaldelay adaptation conditions.

delay, delay adapted, and subjective delay conditions.

Condition

Adaptation

Test (20 trials)

Condition(60 trials; ms)

Baseline

Adaptation

Washout(60 trials; ms)(30 trials; ms)(30 trials; ms)

Minimum delay

36t̄movement + N(0 ms, 80 ms)

Minimum delay (MD)

36

36

36

Delay adaptation

136t̄movement + N(0 ms, 80 ms)

Physical delay (PD)

36

136

36

Delay adapted (DA)

136

136

36

During the test trials (gray shaded column) a visual shift was imposed whereas

Subjectively

136

36

36

no visual shift was imposed during the adaptation trials.

reversed (SR)whether the visual feedback was felt before or after the moment
they touched the screen.

During the adaptation trials (gray shaded column) a visual shift was imposed

Experiment 2: prism adaptation

where t denotes the time of visual feedback measured from thetime of touching the screen. Namely, a positive value of t indicatesthat the visual feedback appears after a screen touch, and a negativevalue of t indicates otherwise. t 0 and b are the intercept and theslope, respectively. In particular, t 0 is the time when the probability becomes 0.5, thereby the PSS. Therefore, by comparing thevalues of t 0 in the baseline condition and in the delay adaptation
condition, the shift of PSS was evaluated.
For the prism adaptation experiment (Experiment 2), the learning rate during adaptation trials was estimated by a discrete-model
approach (Kitazawa et al., 1995; Yin and Kitazawa, 2001; Tanaka
et al., 2011), in which a learning coefficient (k) is defined as a portion of an error in previous trial that reduces an error in current
trial:The second experiment investigated the effect of temporal adaptation on the adaptation rate in prism adaptation. One session
consisted of (1) 60 baseline trials, (2) 30 adaptation trials, and(3) 30 washout trials, a total of 120 trials. Only during theadaptation trials, the visual displacement was imposed by theprisms.
There were four conditions of variable feedback timings assummarized in Table 2. Each subject was tested two sessions foreach condition, totally participating in eight sessions, and the orderof the four conditions was randomized subject by subject. In the
MD condition the delay was minimal (36 ms) through baseline,
prism adaptation, washout trials. Therefore, learning coefficientsobtained in this condition were regarded as a reference comparedto those in other conditions. In the PD condition an additional
delay (136 ms) was added to the timings of visual feedback during
the prism adaptation trials so that the effect of delayed visual feedback on prism adaptation could be evaluated. The delay adapted(DA) and subjectively reversed (SR) conditions were specificallydesigned to evaluate the effect of lag adaptation on the learning rateduring prism adaptation. In the DA condition, the 136-ms delay
was imposed during both the baseline and prism adaptation trials,
so the effect of temporal adaptation was evaluated by comparing with the PD condition. In the SR condition, the 136-ms delay
was imposed to induce temporal adaptation during the baseline
trials and was then reduced to the MD during the prism adaptation trials; in this condition, subjective illusory reversal between
screen touch and visual feedback was expected. All the subjects
completed two sessions of each of the four conditions (i.e., totallyeight sessions).

whereas no visual shift was imposed during the baseline or washout trials.

εn = εn−1 − kεn−1(2)Here, εn denotes a horizontal error in n-th trial. The coefficient,by definition, takes a value between 0 and 1. Rewriting Eq. 2 into
εn − ε1 = −k

n−1
X

εi

(3)

i−1

suggests that the coefficient is a slope of a line connecting the orin−1

gin (0, 0) and a point ( Σ εi , εn − ε1 ), so the learning coefficienti=1

for one session can be obtained by minimizing a least-squares sum
30Xεn − ε1 + k

n−1
X

!2
εi

.

(4)

DATA ANALYSIS

n=2

All the analyses described below were performed Matlab (MathWorks, MA, USA). For the delay adaptation experiment (Experiment 1), the probability that the visual feedback was judged to beafter the screen touch was computed from the subjects’ responses(Stetson et al., 2006; Tanaka et al., 2011). We then fitted a sigmoid
function

For each condition the subjects attended two sessions, so learning coefficients for the two sessions were averaged to represent thelearning coefficient of one subject for one condition. The coefficients were computed for the four conditions (denoted as k MD ,k PD , k DA , and k SR , respectively).


Pr ob visual feedback judged after touch|t1
,=0
1 + exp t −tb

Frontiers in Psychology | Perception Science

i=1

RESULTSPSS SHIFT FOUND IN DELAY ADAPTATION EXPERIMENT(1)Experiment 1 (delay adaptation experiment) checked whether andwhat amount the PSS was shifted in full arm movements underDecember 2012 | Volume 3 | Article 545 | 4

Tanaka et al.

Prism and temporal adaptation

visual displacement. Psychometric curves in the TOJ task werecomputed in both baseline and delay adaptation conditions. For
all subjects, PSS shift was positively shifted toward the timing ofvisual feedback (lag adaptation) with mean 40.1 ms and SE 8.5 ms(see individual PSS data summarized in Table 3). These shifts
were statistically significant [t (5) = 4.74, p = 0.005]. Therefore,
the subjective simultaneity was shifted due to the delayed visualfeedback.
NO EFFECT OF ILLUSORY REVERSAL ON PRISM ADAPTATION RATE IN
PRISM ADAPTATION EXPERIMENTIn Experiment 2 (prism adaptation experiment) we asked whether
the rate of prism adaptation was affected by illusory reversal
between screen touch and visual feedback. Four conditions (MD,PD, DA, and SR conditions) were tested. Figure 2 and Table 3
summarize learning curves averaged over all subjects and learning
coefficients of individual subjects. The feedback delay during theadaptation trials (61–90 trials) was 36 ms in the MD and SR conditions, and 136 ms in the PD and DA conditions (see Materials
and Methods and Table 2). We applied a one-way repeated measures ANOVA to learning coefficients (learning rates), and founda significant effect of condition [F (3, 15) = 3.89, p = 0.03]. Then
we investigated which pair of conditions is significantly different
in learning rates using a t -test in which p-values were corrected fornumber of comparisons (possible pairs of the four conditions = 6)
using the Bonferroni method.
In order to assess the effect of delay adaptation in prior toprism adaptation, the learning coefficients in the MD and SR
conditions and the learning coefficients in the PD and DA conditions should be statistically compared. The learning rates in the
PD and DA conditions were not statistically significantly different[t (10) = 0.56, p > 0.5 corrected (0.59 × 6), N.S.], confirming theresults of our previous study (Tanaka et al., 2011). Therefore, inthese two conditions, there was no significant effect of delay adaptation on the learning rates. There was no statistically significant
difference between the learning rates in the MD and SR conditions
either [t (10) = 0.12, p > 0.5 corrected (0.90 × 6), N.S.], so again
in these two conditions no significant effect of delay adaptation on
the learning rates was observed. Taken together, delay adaptation,even when illusory reversal was expected, had no significant effects
on the learning rates during prism adaptation.
We also investigated, when no temporal adaptation was
induced, how the visual feedback delay during prism adaptation
affected the adaptation time courses. The learning rate in the
PD condition was smaller than that in the MD condition, for all
six subjects. However, the above t -test could not detect a significant difference [t (10) = 1.24, p > 0.5 corrected (0.24 × 6), N.S.].
Because our previous study using the same experimental setting

Table 3 | Summary of results of experiment 1 (PSS shift) and experiment 2 (k MD , k PD , k DA , and k SR ).
Subject number

PSS shift (ms)

k MD

k PD

k DA

k SR

1

6.3

25.0

15.9

15.4

18.1

2

29.7

7.3

3.4

3.2

7.5

3

42.9

4.1

2.8

2.5

6.7

4

44.0

7.2

5.1

4.9

6.3

5

49.9

6.7

6.4

4.3

6.5

6

67.9

23.9

19.8

11.15

33.3

Group (mean and SE)

40.1 (SE 8.5)

12.3 (SE 3.5)

8.9 (SE 2.9)

6.9 (SE 2.1)

13.1 (SE 4.5)

The subjects are arranged in order of increasing PSS shifts.

FIGURE 2 | (A) Learning curves averaged over six subjects for four conditions(MD: black circle, PD: blue upward-pointing triangle, DA: red
downward-pointing triangle, and SR: green diamond). The gray shaded trials

www.frontiersin.org(movements 61–90) indicate the block of prism adaptation. (B) Learning
coefficients for six individual subjects for four conditions. Error bars
indicate SE.

December 2012 | Volume 3 | Article 545 | 5

Tanaka et al.

Prism and temporal adaptation(Tanaka et al., 2011) as well as studies from the other group(Kitazawa et al., 1995; Kitazawa and Yin, 2002) have indicatedthat the additional delay of 100 ms during prism adaptation was
sufficient to cause a significant decrease in the learning rate, we
conducted an additional analysis using a paired t -test only for thecomparison between the PD and MD conditions to confirm theeffect of the delay. We found a statistically significant difference[t (5) = 2.71, p = 0.04], suggesting decrease in learning rate due todelay of the visual feedback.

DISCUSSION
We investigated whether and how temporal lag adaptation affected
subsequent motor adaptation by quantifying the learning coefficients of prism adaptation under various timings of visual feedback. Specifically, by imposing a visual feedback delay of additional
100 ms during delay adaptation trials and then removing the delay
during prism adaptation trials, an illusory reversal between an
action (button press) and a consequence (visual feedback) was
induced. Even with the subjective reversal, the learning coefficientwas not found to be statistically different from that calculated in thebaseline condition. This result was in line with our previous resultthat subjective shortening of visual feedback delay did not haveany significant effect on the rate of prism adaptation (Tanaka et al.,2011). Taken together, we conclude that the subjective temporal
adaptation has no significant effect on adaptation to visual displacement by wedge prisms, thereby adding supporting evidence
for the distributed-clock hypothesis, i.e., independent timing systems for perception of subjective causality and adaptation to prism
displacement.
Our finding of independence between temporal adaptation andprism adaptation appears to be remarkable for the following threereasons. First, there are previous studies reporting the influence ofa perceptual or cognitive task on a simultaneous motor task. Dualtask paradigms composed of a sensorimotor task and a cognitivetask, for example, usually impair the performance of sensorimotor
adaptation (Redding et al., 1985; Taylor and Thoroughman, 2007).
In addition, reaction times of a motor task are significantly influenced by subjective judgment of temporal order (Cardoso-Leiteet al., 2007). Second, brain areas that are responsible for temporalperception of sub-second overlap those that are responsible formotor control (Lewis and Miall, 2003a,b). In particular, the cerebellum is associated with various tasks that require precise timingthat is equal to or shorter than a few seconds (Ivry, 1996; Ivry and

REFERENCES
Brainard, D. H. (1997). The psychophysics toolbox. Spat. Vis. 10,
433–436.
Buonomano, D. V., and Karmarkar, U.
R. (2002). How do we tell time?
Neuroscientist 8, 42–51.
Bushara, K. O., Grafman, J., and Hallett, M. (2001). Neural correlates ofauditory-visual stimulus onset asynchrony detection. J. Neurosci. 21,
300–304.
Bushara, K. O., Hanakawa, T., Immisch,I., Toma, K., Kansaku, K., and Hallett, M. (2003). Neural correlates ofcross-modal binding. Nat. Neurosci.
6, 190–195.
Cardoso-Leite, P., Gorea, A., andMamassian, P. (2007). Temporalorder judgment and simple reaction times: evidence for a common
processing system. J. Vis. 7, 11.
Cunningham, D. W., Billock, V. A., andTsou, B. H. (2001). Sensorimotor
adaptation to violations of temporalcontiguity. Psychol. Sci. 12, 532–535.
Dhamala, M., Assisi, C. G., Jirsa, V.
K., Steinberg, F. L., and Kelso, J.
A. (2007). Multisensory integration for timing engages different

Frontiers in Psychology | Perception Science

Spencer, 2004). The cerebellum is, on the other hand, associatedwith sensorimotor adaptation such as prism adaptation (Martin
et al., 1996). Finally, a range of temporal delays that is detrimental
for prism adaptation (50–500 ms; Kitazawa et al., 1995; Kitazawa
and Yin, 2002) is conspicuously similar to that for illusory reversal(100–200 ms; Cunningham et al., 2001; Stetson et al., 2006). Fromthese lines of evidence one might expect that adapted temporalperception can affect the learning course of prism adaptation.
The results reported here, however, showed no significant effect ofillusory reversal on the learning coefficients of prism adaptation.
Neural correlates of synchronous detection and temporal binding among cross-modal sensory stimulus onsets have been wellinvestigated especially for audiovisual stimulus pairs (Bushara
et al., 2001, 2003; Dhamala et al., 2007; Noesselt et al., 2007;
Powers III et al., 2012). Cortical and subcortical areas that are
activated for sub-second temporal tasks include insular, parietal, prefrontal, cerebellar, and superior colliculus. Depending
on subjective reports of synchrony and asynchrony between
stimuli, distributed sub-networks among these areas were distinctly employed. In contrast, a relatively few studies have beenreported for neural correlates related to temporal binding between
voluntary actions and consequential feedback stimuli (Stetson
et al., 2006; Stekelenburg et al., 2011). Stetson et al. (2006) suggested multiple timing systems and argued that the observed
activation in the anterior cingulate cortex reflected subliminal
error detection or error detection between subjective and physical intervals. Although there are some overlaps between areas
involved in temporal binding of cross-modal sensory stimuli andareas involved in temporal binding of action and consequence,
it is not understood whether the two kinds of temporal processing are processed by shared or distinct neural mechanisms.
Further studies are necessary to clarify the neural mechanismsthat underlie temporal binding of sensory signals and motor
control.

ACKNOWLEDGMENTS
We thank John E. Jacobson for discussions on temporal perception, Kaoru Nakamoto for conducting a preliminary experiment,
Yuka Furukawa for organizing the experiments, Makoto Miyazaki
for his comment on data analysis, and two anonymous reviewers
for warm comments. We are also grateful to Mitsuo Kawato andYasuhiro Wada for providing the supportive environment for thisstudy.
brain networks. Neuroimage 34,
764–773.
Fujisaki, W., Shimojo, S., Kashino,M., and Nishida, S. (2004).
Recalibrationofaudiovisual
simultaneity. Nat. Neurosci. 7,
773–778.
Haggard, P., Clark, S., and Kalogeras, J.
(2002). Voluntary action and conscious awareness. Nat. Neurosci. 5,
382–385.
Harrar, V., and Harris, L. R. (2008).
The effect of exposure to asynchronous audio, visual, and tactile stimulus combinations on the perceptionof simultaneity. Exp. Brain Res. 186,
517–524.
Heron, J., Hanson, J. V., and Whitaker,
D. (2009). Effect before cause:
supramodal recalibration of sensorimotor timing. PLoS ONE 4:e7681.
doi:10.1371/journal.pone.0007681
Honda, T., Hirashima, M., andNozaki, D. (2012). Adaptation tovisual feedback delay influences
visuomotor learning. PLoS ONE
7:e37900. doi:10.1371/journal.pone.
0037900
Ivry, R. B. (1996). The representation of temporal information in

December 2012 | Volume 3 | Article 545 | 6

Tanaka et al.

perception and motor control. Curr.
Opin. Neurobiol. 6, 851–857.
Ivry, R. B., and Spencer, R. M. (2004).
The neural representation of time.
Curr. Opin. Neurobiol. 14, 225–232.
Keele, S. W., Pokorny, R. A., Corcos,
D. M., and Ivry, R. (1985). Do
perception and motor production
share common timing mechanisms:
a correctional analysis. Acta Psychol.
(Amst) 60, 173–191.
Keetels, M., and Vroomen, J. (2012).
Exposure to delayed visual feedbackof the hand changes motor-sensory
synchrony perception. Exp. Brain
Res. 219, 431–440.
Kitazawa, S., Kohno, T., and Uka, T.
(1995). Effects of delayed visual
information on the rate and amountof prism adaptation in the human. J.
Neurosci. 15, 7644–7652.
Kitazawa, S., and Yin, P. B. (2002). Prism
adaptation with delayed visual error
signals in the monkey. Exp. Brain
Res. 144, 258–261.
Lewis, P. A., and Miall, R. C. (2003a).
Brain activation patterns during
measurement of sub- and suprasecond intervals. Neuropsychologia
41, 1583–1592.
Lewis, P. A., and Miall, R. C. (2003b).
Distinct systems for automatic andcognitively controlled time measurement: evidence from neuroimaging.
Curr. Opin. Neurobiol. 13, 250–255.

www.frontiersin.org

Prism and temporal adaptation

Martin, T. A., Keating, J. G., Goodkin, H. P., Bastian, A. J., and Thach,
W. T. (1996). Throwing while looking through prisms. I. Focal olivocerebellar lesions impair adaptation.
Brain 119(Pt 4), 1183–1198.
Miyazaki, M., Yamamoto, S., Uchida, S.,
and Kitazawa, S. (2006). Bayesiancalibration of simultaneity in tactile temporal order judgment. Nat.
Neurosci. 9, 875–877.
Noesselt, T., Rieger, J. W., Schoenfeld,
M. A., Kanowski, M., Hinrichs, H.,
Heinze, H. J., et al. (2007). Audiovisual temporal correspondence modulates human multisensory superior temporal sulcus plus primarysensory cortices. J. Neurosci. 27,
11431–11441.
Pelli, D. G. (1997). The VideoToolbox
software for visual psychophysics:
transforming numbers into movies.
Spat. Vis. 10, 437–442.
Powers, A. R. III, Hevey, M. A., and Wallace, M. T. (2012). Neural correlatesof multisensory perceptual learning.
J. Neurosci. 32, 6263–6274.
Redding, G. M., Clark, S. E., and Wallace, B. (1985). Attention and prism
adaptation. Cogn. Psychol. 17, 1–25.
Rousseau, R., Poirier, J., and Lemyre,
L. (1983). Duration discriminationof empty time intervals marked
by intermodal pulses. Percept. Psychophys. 34, 541–548.

Stekelenburg, J. J., Sugano, Y., andVroomen, J. (2011). Neural correlates of motor-sensory temporal recalibration. Brain Res. 1397,
46–54.
Stetson, C., Cui, X., Montague, P. R.,
and Eagleman, D. M. (2006). Motorsensory recalibration leads to an illusory reversal of action and sensation.
Neuron 51, 651–659.
Sutton, R. S., and Barto, A. G. (1998).
Reinforcement Learning: An Introduction. Cambridge, MA: MIT Press.
Tanaka, H., Homma, K., and Imamizu,
H. (2011). Physical delay but not
subjective delay determines learning
rate in prism adaptation. Exp. Brain
Res. 208, 257–268.
Taylor, J. A., and Thoroughman, K. A.
(2007). Divided attention impairs
human motor adaptation but not
feedback control. J. Neurophysiol. 98,
317–326.
Vroomen, J., and Keetels, M. (2010). Perception of intersensory synchrony: atutorial review. Atten. Percept. Psychophys. 72, 871–884.
Wenke, D., and Haggard, P. (2009).
How voluntary actions modulate
time perception. Exp. Brain Res. 196,
311–318.
Yamamoto, S., Miyazaki, M., Iwano,T., and Kitazawa, S. (2012).
Bayesian calibration of simultaneity
in audiovisual temporal orderjudgments. PLoS ONE 7:e40379.
doi:10.1371/journal.pone.0040379
Yin, P. B., and Kitazawa, S. (2001). Longlasting aftereffects of prism adaptation in the monkey. Exp. Brain Res.
141, 250–253.
Conflict of Interest Statement: The
authors declare that the research was
conducted in the absence of any commercial or financial relationships that
could be construed as a potential conflict of interest.
Received: 23 July 2012; accepted: 16
November 2012; published online: 11
December 2012.
Citation: Tanaka H, Homma K andImamizu H (2012) Illusory reversal of causality between touch andvision has no effect on prism adaptation rate. Front. Psychology 3:545. doi:
10.3389/fpsyg.2012.00545
This article was submitted to Frontiers in
Perception Science, a specialty of Frontiersin Psychology.
Copyright © 2012 Tanaka, Homma andImamizu. This is an open-access article distributed under the terms of theCreative Commons Attribution License,
which permits use, distribution andreproduction in other forums, provided
the original authors and source are credited and subject to any copyright notices
concerning any third-party graphics etc.

December 2012 | Volume 3 | Article 545 | 7