Acta Psychologica 151 (2014) 32–39

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Effectively responding to tactile stimulation: Do homologous cue and effector locations really matter? Cristy Ho ⁎, Charles Spence Crossmodal Research Laboratory, Department of Experimental Psychology, University of Oxford, UK

a r t i c l e

i n f o

Article history: Received 27 January 2014 Received in revised form 20 May 2014 Accepted 26 May 2014 Available online xxxx PsycINFO classification: 2320 4010

a b s t r a c t We report a study designed to investigate the extent to which speeded behavioral responses following tactile stimulation are influenced by differences in neural conduction latencies at different body sites and/or by the characteristics of the compatibility between the cue and effector. The results showed that it may not be particularly desirable to present tactile cues (e.g., warning signals) to an interface operator's feet if a speeded foot response is required, for even though such an arrangement maximizes the set-level compatibility between the stimulus and the response, it turns out that response latencies are primarily determined by conduction latencies through the peripheral nervous system. © 2014 Elsevier B.V. All rights reserved.

Keywords: Tactile stimulation Spatial compatibility Conduction latency Haptics Interface design

1. Introduction Over the last decade or so, researchers have highlighted the potential utility of incorporating tactile cues into contemporary interface design (e.g., Baldwin et al., 2012; Ho, Reed, & Spence, 2005, 2006; Ho, Tan, & Spence, 2005; Nagel, Carl, Kringe, Martin, & Konig, 2005; Stepp & Matsuoka, 2012; van Erp & van Veen, 2004). In fact, there has been a rapid development in the availability of consumer touch technology, ranging from touch screen smartphones for everyday use through to motion controllers for gaming and interaction with computer devices (see Gallace & Spence, 2014, for a recent review). We envision that it will not be too long before devices capable of delivering virtual touch (e.g., imagine wearing a sensor for gesture control on your wrist that you can use to open the door automatically) will become an integral part of many people's everyday lives in the western world. However, one issue that has as yet to receive sufficient attention from researchers concerns the question of whether presenting tactile cues to the part of the body that will be used to make the desired behavioral response to an event by an interface operator is more efficient than presenting tactile cues to any other part of the body instead. In other words, does

⁎ Corresponding author. Tel.: +44 1865 271364; fax: +44 1865 310447. E-mail addresses: [email protected] (C. Ho), [email protected] (C. Spence).

http://dx.doi.org/10.1016/j.actpsy.2014.05.014 0001-6918/© 2014 Elsevier B.V. All rights reserved.

the compatibility between the location from which a tactile cue is presented and the required behavioral response matter, given the increasing demand for different gestural controls for increasingly complicated commands? Previous studies attempted to quantify particular stimulus–response mappings in terms of spatial compatibility (or element-level mapping effect), set-level compatibility effects, and/or the Simon effect (Kornblum, Hasbroucq, & Osman, 1990; Proctor & Vu, 2006; Simon, 1990). In particular, spatial compatibility refers to the finding that reaction times (RTs) are faster when the stimulus and response both occur on the same (compatible) side (e.g., as when participants are instructed to press a button with their left hand when a target appears on the left and to press a button with their right hand when the target appears on the right), rather than when the stimulus and response occur on opposite (i.e., incompatible) sides (e.g., when instructed to press a button with their left hand when a target appears on the right and to press a button with their right hand when the target appears on the left). Such element-level compatibility effects (i.e., a mapping between individual elements of the stimulus and response sets) can be distinguished from set-level compatibility effects. The latter refers to the manipulation of the relationship between stimulus and response at the level of the set of stimulus and response characteristics. For example, when instructed to respond to a target appearing on the left/right by left/ right keypresses vs. when instructed to respond to the words “left” and “right” with vocal “left” and “right” responses, responding is faster

C. Ho, C. Spence / Acta Psychologica 151 (2014) 32–39

with these two combinations than with those for which the left–right location stimuli are responded to with left–right vocal responses or the words “left” and “right” are responded to with left–right keypresses. The Simon effect constitutes a special case of spatial compatibility and refers to the fact that RTs are typically faster when the stimulus and response both occur in the same location than when they occur on opposite sides (i.e., different locations), even under conditions where the location of the stimulus itself is entirely irrelevant to the participant's task (cf. Hasbroucq & Guiard, 1992; Hasbroucq, Guiard, & Kornblum, 1989; Leuthold & Schroter, 2006). For example, when instructed to press a button on the left (with their left hand) when they see a circle and to press a button on the right (with their right hand) when they see a square displayed on the computer screen, participants will typically respond more rapidly if the circle happens to be presented on the left side of the screen than on those trials where it happens to be presented on the right of the screen, even though this spatial dimension of stimulus presentation is entirely irrelevant to the participant's shape discrimination task. With respect to its application in the design of tactile interfaces, it is important to specify the relation between the parameters of the body sites being tactually-stimulated and any consequences that this might have on the desired motor response. Think, for example, of the practical problem of determining where it is best to present a vibrotactile cue in order to get a driver to depress the brake pedal. Should that vibration be presented to the driver's foot, as this would be compatible with the required response, or to the driver's hand as conduction latencies to the brain should be shorter (even though the set-level compatibility between the vibrotactile cue and target braking response is thereby reduced)? Psychophysical research on tactile perception dating back to at least the 1960s has examined variations in perceptual thresholds (e.g., twopoint thresholds) for tactile stimuli delivered to different positions on the body (e.g., see Deatherage, 1972; Geldard, 1962; Godde, Stauffenberg, Spengler, & Dinse, 2000; von Békésy, 1963; Weinstein, 1968). In relation to people's detection sensitivity and their ability to localize tactile stimuli, the majority of previous studies have concentrated primarily on stimulating people's forearms, hands, and/or their fingertips (e.g., Burke, Gilson, & Jagacinski, 1980; Harris, Thein, & Clifford, 2004; Jagacinski, Flach, & Gilson, 1983; Schumann, Godthelp, Farber, & Wontorra, 1993; Sklar & Sarter, 1999; Smith, 1977; Vitense, Jacko, & Emery, 2003), and also the waist in certain more recent application-inspired research (e.g., Cholewiak, Brill, & Schwab, 2004; Gallace & Spence, 2014; Ho, Gray, & Spence, 2014; Ho & Spence, 2008; Nagel et al., 2005; van Erp & van Veen, 2004). A few driving studies have also investigated the possibility of stimulating a driver's feet (e.g., Godthelp & Schumann, 1993; Mulder, Abbink, Boer, 2008; see also Kume, Shirai, Tsuda, & Hatada, 1998). However, only limited research has attempted to examine the relative efficacy of tactile stimulation on different parts of the body. In particular, surprisingly few studies have compared the speed of tactile responding as a function of the required response sites (e.g., hand vs. foot responses). Thus, the question remains as to whether any tactile stimulation delivered to the surface of the human body will necessarily lead to a performance advantage in the same task or whether any benefit may be body-site specific (see Campbell et al., 1996). The present study was therefore designed to examine the relationship between vibrotactile cues presented on the hands (wrists) and feet (shins) with the body sites required to produce a response. One might expect to observe a set-level compatibility distinction: that is, faster performance in speeded discrimination tasks when the vibrotactile target position and the effector (i.e., hand or foot) are homologous (i.e., manual responses to targets presented to the wrists and foot responses to targets presented to the shins) rather than when they are non-homologous (i.e., manual responses to targets presented to the shins and foot responses to targets presented to the wrists; see Fig. 1a). Alternatively, however, it might be that behavioral responses are

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primarily influenced by any differences in neural conduction latencies (cf. Campbell, Ward, & Swift, 1981). Hence, the closer the vibrotactile cue (and response location) is presented to the brain (i.e., the shorter the conduction latency), the faster the RT. This account would predict the fastest RT for manual responses to vibrotactile targets presented on the wrists (see Fig. 1b). In addition, a distinction can also be made at the set-level whereby one might expect to observe faster responses to higher set-level compatibility conditions (i.e., wrist-hand and shin-foot pairings) than to lower set-level compatibility conditions (i.e., wristfoot and shin-hand pairings).

2. Methods 2.1. Participants Sixteen participants (mean age of 27 years, age range from 19 to 37 years; 6 males and 10 females) took part in this study. All of the participants reported having a normal sense of touch and were right-handed by self-report. The experiment lasted for approximately 40 minutes. The participants received a £5 UK sterling gift voucher in return for taking part in the study. The experiment was conducted in accordance with the ethical guidelines laid down by the Department of Experimental Psychology, University of Oxford.

2.2. Apparatus and materials The participants were seated in front of a desk in a completely darkened experimental booth. A green light-emitting diode (LED) placed 70 cm directly in front of the participant served as the central fixation point. Four tactors (2.54 × 1.85 × 1.07 cm, VBW32, Audiological Engineering Corporation, Somerville, MA) were used to present the vibrotactile signals. These tactors were fastened to the back of the participants' wrists and to the front of their shins (about 10 cm above their ankles) with Velcro belts (see Fig. 2; cf. Sklar & Sarter, 1999). The belts and tactors were fastened directly over the participants' skin, below their clothing. The tactors were driven by a 250 Hz sinusoidal signal at an intensity that was adjusted individually for each tactor for each participant at the start of the experiment in order to deliver clearly perceptible vibrotactile stimuli of approximately equal perceived intensity at the four positions. White noise was delivered via headphones (QuietComfort™ headset, Bose Corporation, Framingham, MA) at 75 dB(A) to mask the noise caused by the operation of the tactors. Two response keys (placed 2.5 cm apart horizontally) mounted in a box were used to record the participants' manual responses. Two footpedals were placed on the floor at a comfortable distance from the participants, one below the toes of their left foot and the other below the toes of their right foot. These footpedals were used to record the participants' foot responses.

2.3. Design The experimental session consisted of three tasks: 1) a compatible spatial discrimination task; 2) an incompatible spatial discrimination task; and 3) a gap discrimination task. All of the participants completed the three tasks in the same order. We did not counterbalance order as we were not so concerned about carryover effect. Each task consisted of one block of 8 practice trials (or 48 practice trials in the gap discrimination task) followed by two blocks of 160 experimental trials (one block with foot responses and the other with manual responses; the order of presentation of these two blocks was counterbalanced across participants). The vibrotactile stimuli were randomly presented in any one of the four positions and were equiprobable within each block of experimental trials.

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C. Ho, C. Spence / Acta Psychologica 151 (2014) 32–39

Fig. 1. Hypothetical results in terms of the (a) stimulus–response compatibility and (b) conduction latency account of tactile discrimination responses. Interaction between Target position and Response effector in the RT data from the (c) spatial discrimination task and (d) gap discrimination task. Error bars indicate the standard errors of the means.

2.4. Procedure The participants were seated comfortably resting their arms on the desk and holding the response box with both hands. They were instructed to maintain the same posture and to fixate the central LED throughout each block of experimental trials. The participants were instructed to keep both footpedals depressed throughout each trial in the foot response blocks and to lift their toes off one of the two footpedals as rapidly as possible to indicate their responses. In the manual response blocks, the participants were instructed to press one of the two buttons with their left or right thumb as rapidly as possible to indicate their responses. Prior to the start of the experimental session, the intensity of the tactors was individually adjusted to match their perceived intensity as reported subjectively by each participant. Each trial in the compatible spatial discrimination and incompatible spatial discrimination tasks began with the presentation of a vibrotactile target stimulus for 50 ms. The participants had to indicate whether the target had been presented to the left or right side of their body. They responded by lifting their foot off the footpedal or pressing the button on the same side as the target in the compatible spatial discrimination task blocks. In the incompatible spatial discrimination task blocks, the participants were instructed to respond by lifting their foot off the footpedal or pressing

the button on the side opposite to the target. A trial was terminated after the participant's response or if no response had been recorded within 1500 ms of the onset of the target stimulus. The inter-trial interval was 1000 ms. In the gap discrimination task, the participants had to discriminate between two patterns of three vibrotactile bursts (50 ms on – 30 ms off – 50 ms on – 200 ms off – 50 ms on vs. 50 ms on – 200 ms off – 50 ms on – 30 ms off – 50 ms on). This nonspatial discrimination task was designed to measure participants' speed of responding to vibrotactile stimuli presented to their four limbs as a function of the response effector and/or body side, while holding the nature of the task irrelevant to any spatial and/or bodily reference (as in a typical study of the Simon effect; see Simon, 1990, for a review). The two target patterns were designed in such a way as to be easily discriminable while keeping the intensity of each individual vibrotactile stimulus constant. Each trial began with the random presentation of one of the vibrotactile patterns presented equiprobably in each of the four positions in each block of experimental trials. The participants were told prior to the start of the condition the left/right response footpedal/button mapping to the two patterns (counterbalanced across participants). A trial was terminated after participants responded or if no response had been recorded within 3000 ms of the onset of the target stimulus. The inter-trial interval was again set at 1000 ms. The participants were given no feedback regarding their

C. Ho, C. Spence / Acta Psychologica 151 (2014) 32–39

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tasks in order to assess what effect, if any, the target and response positions had on participants' speeded discrimination performance. 3.1. Spatial discrimination task

Fig. 2. The setup used in the present study. The room was completely dark during the actual experiment.

performance during the experiment except at the end of the practice block in the gap discrimination task, when they were told how many errors they had made out of the 48 practice trials. 3. Results RTs that fell 3 standard deviations above or below the mean RT for a particular condition for each participant were discarded from the data analysis. On average, 1.8% of the trials were removed as a result of either this criterion or because participants had failed to make a response before the trial was terminated. Trials in which participants made an incorrect response were discarded from the analysis of the RT data. Separate analyses of variance (ANOVAs) were performed on the RT and error data from the spatial discrimination and gap discrimination

Table 1 Mean RTs (ms) and percentages of errors (and their standard errors in brackets) in the spatial discrimination task as a function of Spatial compatibility, Target position, Response effector, and Response side. Target position Shin Response effector

Spatial compatibility

Wrist

Foot

Hand

RT

% error

RT

% error

Left

420 (25)

4.7 (1.1)

379 (19)

Right

423 (23)

3.0 (0.8)

Left

532 (28)

Right

548 (34)

Foot

Hand

RT

% error

RT

% error

3.8 (0.9)

403 (25)

4.9 (1.3)

347 (18)

4.5 (1.2)

383 (20)

2.6 (1.2)

408 (24)

2.1 (0.7)

350 (18)

3.5 (1.3)

1.0 (0.6)

474 (27)

2.4 (1.0)

522 (30)

1.0 (0.3)

447 (26)

0.0 (0.0)

1.2 (0.5)

463 (24)

1.8 (1.0)

525 (32)

0.7 (0.4)

436 (25)

0.9 (0.4)

Response side

Compatible

Incompatible

Table 1 highlights the RTs and percentages of errors in the spatial discrimination task. The four factors in the within-participants design were Spatial compatibility (i.e., spatial stimulus–response compatibility: compatible vs. incompatible), Target position (or stimulus position: shin vs. wrist), Response effector (foot vs. hand; i.e., toe-lifting vs. buttonpressing), and Response side (left vs. right). The analysis of the RT data revealed significant main effects of Spatial compatibility, F(1,15) = 73.1, p b .001, η2 = .830, Target position, F(1,15) = 63.2, p b .001, η2 = .808, and Response effector, F(1,15) = 44.4, p b .001, η2 = .747. The participants responded significantly more rapidly in the compatible response mapping blocks (M = 389 ms) than in the incompatible response mapping blocks (M = 493 ms), as expected. The participants also responded more rapidly to vibrotactile targets presented to their wrists (M = 430 ms) than to their shins (M = 453 ms), and when responding with their hands (M = 410 ms) than with their feet (M = 473 ms). There was no main effect of Response side, F(1,15) b 1, n.s., η2 = .018 (M = 441 ms for left and M = 442 ms for right responses, respectively). The analysis of the RT data also revealed a significant interaction between Target position and Response effector, F(1,15) = 6.2, p = .025, η2 = .292 (see Fig. 1c), thus suggesting that although responding with hands was the fastest for both shin and wrist targets, the hand benefit was greater for vibrotactile targets presented to the wrists than to the shins. In other words, there was a set-level compatibility effect, even though the magnitude of the influence was small. Posthoc Duncan analysis revealed significant differences between all combinations of these two factors, p b .001 for all comparisons, thus demonstrating that participants responded most rapidly with their hands to vibrotactile targets presented to their wrists (M = 395 ms), followed by vibrotactile targets presented to their shins with manual responses (M = 425 ms), more slowly to vibrotactile targets presented to their wrists when responding with their feet (M = 464 ms), and with the slowest responses being recorded following vibrotactile targets presented to the participants' shins when responded to with the feet (M = 481 ms). This pattern of results is more consistent with the conduction latency account than with the compatibility account of tactile response latencies (see Fig. 1b). The interactions between Spatial compatibility and Response effector, F(1,15) = 3.7, p = .074, η2 = .197, and between Spatial compatibility and Response side, F(1,15) = 3.9, p = .066, η2 = .208, did not reach statistical significance. None of the other interactions between the four factors were significant, all Fs b 2.0, ps N .19. A similar analysis of the error data from the spatial discrimination task revealed a significant main effect of Spatial compatibility, F(1,15) = 21.9, p b .001, η2 = .594, with participants making slightly more mistakes in the compatible (M = 3.6%) than in the incompatible response-mapping condition (M = 1.1%), contrary to our expectations. There was, however, no significant main effect of Target position, F(1,15) = 1.2, p = .29, η2 = .075, nor of Response effector, F(1,15) b 1, n.s., η2 = .005. The main effect of Response side was statistically significant, F(1,15) = 8.2, p = .012, η 2 = .353, with participants making significantly more mistakes when responding with the limbs on the left side of their body (M = 2.8%) than with the limbs on the right side of their body (M = 2.0%). The interaction between Spatial compatibility and Response side just failed to reach statistical significance, F(1,15) = 4.4, p = .053, η2 = .227, with participants making marginally more mistakes when responding on the left side (M = 4.5%) than on the right (M = 2.8%) in the compatible condition, p = .001, but equally well to both sides in the incompatible condition (M = 1.1% for both sides), p = .96. There was also a significant interaction between Spatial compatibility,

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C. Ho, C. Spence / Acta Psychologica 151 (2014) 32–39

Target position, and Response effector, F(1,15) = 12.7, p = .003, η2 = .460. Post-hoc Duncan analysis revealed significant differences across all combinations of compatible versus incompatible conditions, p b .01 for all comparisons. None of the post-hoc comparisons within the compatible condition were significant, all ps N .06. As for the comparisons within the incompatible condition, however, participants made significantly more errors when responding manually to targets presented on their shins (M = 2.1%) than in any of the other three conditions (M = 1.1%, 0.8%, and 0.4%, for foot responses to targets presented on the shins, foot responses to targets on the wrists, and manual responses to targets on the wrists, respectively), all ps b .01, comparisons between the other three conditions were all insignificant, all ps N .12. None of the other main interactions were significant, all Fs b 1.5, ps N .24. Note that even though it might appear as if there was a trend toward a speed-accuracy trade-off in terms of the compatibility factor (e.g., faster RTs coupled with more errors in the compatible as compared to the incompatible conditions), subsequent analysis of the inverse efficiency (IE) data suggested otherwise. IE scores are computed by combining RT and error data into a single performance measure (see Townsend & Ashby, 1983), namely IE equals RT divided by the proportion of correct responses (Spence, Kingstone, Shore, & Gazzaniga, 2001). IE analysis provides a standardized means of offsetting any potential speed-accuracy trade-off in performance. The analysis of the IE data showed a similar pattern of results to that reported earlier in the RT analysis, hence ruling out a speed-accuracy trade-off account of the compatibility effect seen in the RT data from the spatial discrimination task. 3.2. Gap discrimination task Table 2 highlights the mean RTs and percentages of errors in the gap discrimination task. Analysis of the RT data from the gap discrimination task, with the within-participants factors of Target position (shin vs. wrist), Target side (left vs. right), Response effector (foot vs. hand), and Response side (left vs. right), revealed significant main effects of Target position, F(1,15) = 7.7, p = .014, η2 = .340, and Response side, F(1,15) = 8.2, p = .012, η2 = .353. Participants responded more rapidly to vibrotactile targets presented to their wrists (M = 861 ms) than to targets presented to their shins (M = 898 ms). Interestingly, participants responded more rapidly with their left limbs (M = 860 ms) than with their right limbs (M = 900 ms). This bias toward responding more rapidly on the left than on the right is particularly puzzling given that all of our participants were right-handers whom one would normally expect to respond preferentially with their dominant right hand (and presumably also with their right foot). Previous studies on the temporal processing of musical stimuli, such as in tasks involving rhythmic perception, have primarily shown left

Table 2 Mean RTs (ms) and percentages of errors (and their standard errors in brackets) in the gap discrimination task as a function of Target position, Target side, Response effector, and Response side. Target position Shin Response effector

Target side

Wrist

Foot

Hand

RT

% error

RT

% error

Left

901 (55)

6.7 (1.7)

848 (42)

Right

956 (64)

5.9 (1.9)

Left

921 (49)

Right

928 (49)

Foot

Hand

RT

% error

RT

% error

7.7 (2.5)

828 (24)

8.6 (2.3)

833 (44)

7.9 (2.2)

881 (45)

5.2 (1.9)

880 (44)

6.1 (1.5)

866 (43)

4.5 (1.6)

7.9 (2.2)

869 (52)

9.0 (2.4)

836 (32)

7.0 (2.4)

840 (46)

5.5 (1.7)

6.8 (1.9)

878 (43)

8.2 (2.3)

914 (48)

7.2 (2.3)

893 (55)

5.7 (1.8)

Response side

Left

Right

hemisphere specialization (see Limb, 2006; Okamoto, Stracke, Draganova, & Pantev, 2009; cf. Nicholls, 1994; Nicholls & Whelan, 1998; see also Spence, Shore, & Klein, 2001), and hence one would have expected, if anything, to see right hand/side facilitation (since the left hemisphere controls the right hand). There was, however, no significant main effect of Target side, F(1,15) = 2.6, p = .13, η2 = .148, nor of Response effector, F(1,15) = 1.1, p = .32, η2 = .067. The interaction between Target position and Response effector was again significant, F(1,15) = 12.0, p = .003, η2 = .444 (see Fig. 1d). This suggests that for targets delivered to the participant's wrist, it did not matter much whether the participants were responding with their hands or feet, whereas for shin targets there was an advantage for responding with their hands. Post-hoc Duncan analysis revealed significantly slower responses when participants had to respond to vibrotactile targets presented to their shins with their feet (M = 926 ms) than in any one of the other three conditions (M = 869 ms for shin targets with manual responses; M = 865 ms for wrist targets with foot responses; and M = 858 ms for manual responses to targets presented to the wrists), all ps b .001. None of the differences among the latter three conditions was significant, all ps N .33. There was a significant interaction between Target position, Target side, and Response side, F(1,15) = 5.7, p = .030, η2 = .276. No consistent evidence of the Simon effect was observed, with any response given with the left limbs to be faster than those with the right limbs, regardless of whether the target was presented on the left or right. This lack of an overall Simon effect could be due, at least in part, to the gap discrimination task being administered following the incompatible spatial discrimination task (see Proctor, Yamaguchi, Zhang, & Vu, 2009). The advantage of responding with the left limb was more evident for shin targets than for wrist targets. Post-hoc analysis revealed that participants responded significantly more rapidly to targets presented to their wrists with their left limbs (regardless of the target side), followed by responses to either left wrist targets with their right limbs or left shin targets with their left limbs, and the slowest in the other conditions (all ps b .041 across these three groups, ps N .10 within each group). Note that none of the other interactions involving the factors of Target position and Response reached statistical significance. The interaction between Target position and Response side was not significant, F(1,15) = 4.2, p = .057, η2 = .221. The trend here was for the Response side effect (that is, faster RTs on the left than right side) to be more pronounced for manual responses (M = 54 ms) than for responses made with the feet (M = 26 ms), consistent with people being more strongly lateralized for their hands than for their feet, as one might expect. None of the other interactions between the four factors were significant, all Fs b 1.3, ps N .28. A similar analysis of the error data in the gap discrimination task revealed no significant main effects or interactions, all Fs b 2.8, all ps N .11. The overall mean error rate was 6.8% (SE = 1.3%). 4. Discussion The present study was designed to examine the nature of the relationship between the presentation of vibrotactile stimuli to a particular limb and their effectiveness in terms of producing a desired speeded behavioral response. In particular, we were interested to find out whether people would respond more rapidly to vibrotactile stimuli presented on the same effector that they had to respond with, than when they had to respond with a different effector to the one stimulated. The results showed that participants in the present study were able to detect and respond to vibrotactile targets that were presented to their wrists more rapidly than those presented to their shins in both the spatial discrimination and gap discrimination tasks. These results replicate the general findings from several previous studies (e.g., Bergenheim, Johansson, Granlund, & Pedersen, 1996; Campbell et al., 1981; Harrar & Harris, 2005; von Békésy, 1963). For example, Bergenheim and colleagues (1996) reported significantly

C. Ho, C. Spence / Acta Psychologica 151 (2014) 32–39

slower tactile speeded detection responses to tactile stimuli presented on the arch or back of their foot than when similar tactile stimuli were presented to their upper arm. They reported simple detection latencies of 151 ± 44 ms for the arm and 165 ± 33 ms for the foot. Harrar and Harris (2005) estimated the tactile conduction velocity along the nerves to be about 22 m/s (i.e., the simple detection RT can be expressed as a function of the distance to the brain with the speed being 45 ms/m). An alternative account for the present results would be in terms of differences in sensitivity across different body sites rather than because of any differences in conduction latencies (i.e., perhaps participants were simply more sensitive on their wrists than on their shins; see Weinstein, 1968). However, this explanation does not provide a particularly plausible account for our results given that the perceived strengths (intensities) of the vibrotactile stimuli presented from the four positions were matched for each individual participant (and the stimuli were kept to the same 50 ms duration and intensity level throughout the experiment). Interestingly, however, while some might argue that that toe-lifting and button-pressing are not directly comparable responses, the advantage for faster RTs when giving manual than foot responses in the spatial discrimination task was not observed in the gap discrimination task. Given that spatial discrimination tasks have to be performed in relation to some kind of spatial frame of reference (no matter whether that reference frame is defined anatomically or externally; e.g., see Riemer, Trojan, Kleinböhl, & Hölzl, 2010), while a temporal (gap) discrimination task does not, the latter task may be less susceptible to any influence that bodily reference frames (e.g., responding with a particular effector) may exert on participants' performance (Spence & McGlone, 2001; Tamè, Farnè, & Pavani, 2011; cf. Spence, 2013). The present results also revealed an interesting interaction between the stimulated positions and effectors in both the spatial discrimination and gap discrimination analyses. In particular, the fastest speeded discrimination responses were obtained when our participants had to respond manually to vibrotactile target stimuli presented to their wrists (HH), than when either the target (FH) or response (HF) involved the feet. On the other hand, participants responded more sluggishly with their feet to vibrotactile targets presented to their shins (FF). Not only did this condition differ from the others reported in the gap discrimination task, the poorer performance reported in the FF condition was also observed in the compatible blocks of the spatial discrimination task (FF M = 422 ms, FH M = 381 ms, HF M = 406 ms, HH M = 348 ms; cf. Anzola, Bertoloni, Buchtel, & Rizzolatti, 1977; Fitts & Seeger, 1953; Proctor, Tan, Vu, Gray, & Spence, 2005). This result would therefore seem to suggest some kind of interference in initiating (or executing) a foot response when tactile stimuli are delivered to the shins. In terms of the applied domain, the results outlined here imply that it may not be particularly effective to present vibrotactile stimuli to the feet if the desired response relates to the feet. So, on the basis of our results, vibrating a driver's feet is not recommended if the desired response relates to the accelerator or brake pedal (cf. McGehee & Raby, 2003; Mulder, Abbink, van Paassen, et al., 2008). This observation has implications for the design of tactile feedback for, for example, automated parallel parking system that becoming widely available in new cars. It should, however, be noted that a different pattern of results from those reported here might possibly have been obtained had the vibrations come from directly below the feet that had to be depressed (the notion being that this might have been somehow more ideomotor compatible) than vibrating the shin to signal lifting of the foot as utilized in the present study. Closely linked to this point is the issue that the design of a combined accelerator and brake pedal with force feedback might require more careful evaluation as there may be undesirable effects on a driver's speed in initiating a foot response in the presence of force feedback vibrations (e.g., Nilsson, 2002). Alternatively, however, the presentation of vibrotactile stimuli to signal hand movements such as the turning of the steering wheel looks to be a

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promising area for future research (e.g., Mulder, Abbink, van Paasseen, et al., 2008; Steele & Gillespie, 2001; Sungjae & Jung-hee, 2010; Wang, Proctor, & Pick, 2003; see also Guiard, 1983). Given that the target vibrations occurred equiprobably in each of the four positions in the present study, it is possible that increasing the probability of occurrence of targets being presented to the shins might have improved performance in the FF condition. For instance, Wuhr (2006) found that people adopted different response preparation strategies depending on the reliability of the cues that they were given, and that the Simon interference effect was modulated as a consequence (cf. Umilta, Rubichi, & Nicoletti, 1999). Specifically, 75% valid cues increased the Simon effect while 100% valid cues decreased it. More generally, people probably have a tendency to bias their attention more toward their hands than toward their feet (given the visual attentional control over so many of our everyday manual activities; Schicke, Bauer, & Röder, 2009), even under conditions of divided attention, such as those studied here, and also because of the greater neural representation of the hands than of the feet in the somatosensory cortex (Kell, von Kriegstein, Rosler, Kleinschmidt, & Laufs, 2005; Narici et al., 1991; Penfield & Boldrey, 1937). So, how then should we account for the difference between HH and FF conditions in all three of our tasks? Schicke and Röder's (2006) data from a tactile temporal order judgment (TOJ) task suggests a common frame of reference for the representation of tactile information presented to different body parts. They reported that their participants appeared to use a non-anatomical (i.e., non-somatotopic) external reference frame that was independent of body posture when attempting to detect the order of occurrence of two tactile stimuli presented on different limbs. On the other hand, Yamamoto and Kitazawa (2001) proposed that the temporal order of tactile stimuli was determined by the participants in their study after the stimuli had been localized in space (see also Gallace & Spence, 2014; Kitazawa, 2002; Shore, Spry, & Spence, 2002; Shore, Gray, Spry & Spence, 2005). Taking a somewhat different perspective, Kim and Cruse (2001) studied the speed of hand-reaching movements to one of eight tactually simulated sites in both crossed and uncrossed hands conditions. Their study was designed to investigate how people decide which hand to use when they have to reach for a given target position on their body (see also Nelson, McCandlish, & Douglas, 1990). These researchers found that the reaching decision seemed to depend on both the spatial information about the body position and also the relative position of their hands (i.e., crossed vs. uncrossed). With respect to our own results, it might have been more costly (i.e., in terms of a longer time delay) to localize distal foot stimuli over hand stimuli. Thus, the increased delay in the transmission of tactile information to/from the feet and brain (both at the perceptual and motor response stages) may have contributed to the slower performance seen in the FF condition (see Campbell et al., 1981). Brunia and van Den Bosch (1984) argued that there may be different activations in the brain prior to finger movements and foot movements of right-handed participants. In particular, they observed larger movement-related slow potentials over the contralateral hemisphere for finger movements, but larger potentials over the ipsilateral side for foot movements. The differential distances of these brain areas from the somatosensory cortex may be one factor contributing to the differences in our hand versus foot responses data (cf. Damen, Freude, & Brunia, 1996; see also Holroyd, Dien, & Coles, 1998, for results regarding the existence of an error-processing system that is independent of the particular limbs involved). One interesting question to arise from the results of the present study is whether the poor FF performance reflects a physiological limitation or a cognitive one (such as an inhibition of attending to the feet). With respect to the latter idea, Lakatos and Shepard (1997) investigated the effect of varying the distance between the attended location and tactile target location on the body. Specifically, in each trial in their study, an auditory cue instructed the participants to attend to one of

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eight different body locations (consisting of the left and right wrists, arms, thighs, and calves). Shortly (800 ms) thereafter, a target location was announced and at the same time air puffs were presented to four of the eight locations. The participants' task involved having to discriminate whether the air puff was presented to the target location or not by pressing one of two footpedals. Lakatos and Shepard (1997) reported an increase in speeded RTs (that is, a slowing of performance) as the distance between the attended and target locations increased. They also reported faster attention shifts when the attended and target locations were on opposite sides rather than on the same side of the participant's body. Their results were contingent upon the number of locations that their participants could simultaneously attend to and the ease with which they could shift their attention to the target location upon hearing the instruction (cf. Menning, Ackermann, Hertrich, & Mathiak, 2005). 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