Exp Brain Res (2012) 218:227–235

DOI 10.1007/s00221-012-3003-1

RESEARCH ARTICLE

What to do and how to do it: action representations in tool use

Cristina Massen · Christine Sattler

Received: 26 September 2011 / Accepted: 12 January 2012 / Published online: 24 January 2012© Springer-Verlag 2012

Abstract Research on bimanual coordination has shownthat the eYciency of programming an action is determinedby the way the action is cognitively represented. In tool use,actions can be represented with respect to the spatial goal ofthe action (e.g., the nail that is to be hit by a hammer) orwith respect to the tool and its transformation (i.e., thefunction that maps external target locations onto corre-sponding bodily movements). We investigated whether theway of cuing bimanual actions with tools aVects their cog-nitive representation and the eYciency with which they areprogrammed. In one group of participants, tool transforma-tions were speciWed by symbolic cues, whereas the targetswere indicated by direct spatial cues. In another group ofparticipants, symbolic cues speciWed the targets of the tool-use actions, whereas tool transformations were indicated bydirect spatial cues. In a third group, both targets and tooltransformations were cued directly by spatial cues. It washypothesized that diVerent cognitive representations wouldresult in more or less eYcient programming of the action.Results indicated longer reaction times and a higher errorrate in the group with symbolic cuing of the targets as com-pared to the group with symbolic cuing of the transforma-tions. The latter did not diVer much from the direct cuinggroup. These results suggest that it is more eYcient to rep-resent bimanual tool-use actions in terms of the tool trans-

formations involved than in terms of the targets at whichthey are directed.

Keywords Bimanual coordination · Visuomotor transformation · Tool use · Symbolic cuing · Action representations

Introduction

In research on bimanual coordination, it has often beenshown that the eYciency of programming an action isdetermined by the way the action is cognitively repre-sented. DiVerent action representations may result as a con-sequence of the way actions are cued in an experimentalcontext. For instance, in a study by Diedrichsen et al.(2003), participants had to execute bimanual aiming move-ments to colored target locations on a table. Target loca-tions had to be selected on the basis of two color cues thatwere presented in each trial. The speed and accuracy withwhich the movements were executed were not dependenton the target locations themselves (i.e., by whether theyrequired similar movement amplitudes or movement direc-tions), but were strongly inXuenced by whether they wereof the same color or of diVerent color. When movementshad to be executed to targets of the same color, perfor-mance was much better than when movements had to beexecuted to targets of diVerent color, irrespective ofwhether the required movements were the same or diVerentfor both hands. To account for their results, Diedrichsenet al. (2003) argued that movements are represented interms of target color under these conditions, and interfer-ence arises at the level of target selection, when diVerent-colored targets have to be selected for the two hands.Conversely, interference may arise for movements with

C. Massen (&)Leibniz Research Centre for Working Environment and Human Factors, Ardeystr. 67, 44139 Dortmund, Germanye-mail: massen@ifado.de

C. SattlerDepartment of Psychology, Max-Planck-Institute for Human Cognitive and Brain Sciences, Stephanstrasse 1A, 04103 Leipzig, Germanye-mail: sattler@cbs.mpg.de

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diVerent amplitudes or directions, when the required move-ment characteristics are explicitly cued, for instance, withletters signaling whether a short or a long movement has tobe executed (e.g., Spijkers et al. 1997, 2000). This suggeststhat participants represent the movements in terms of theiramplitudes or directions (rather than in terms of target char-acteristics) under these conditions. There is also evidencethat no interference (Diedrichsen et al. 2001) or at leastconsiderably less interference (Heuer and Klein 2006) isfound when movement targets are cued by direct spatialcues at the respective locations in space.

In this study, we were interested in the cognitive repre-sentation of tool-use actions and in whether diVerent actionrepresentations may aVect the eYciency of bimanual coor-dination in tool use. In actions made with tools, the externalgoal or target of the tool use action (e.g., the nail that is tobe hit by a hammer) and the target-to-movement transfor-mation (i.e., the function that maps external target locationsonto bodily movements) realized by the tool have to bespeciWed before the bodily movement parameters can beprogrammed. Consider the situation, that a participant hasto execute a tool-use action and is given two cues, one sig-naling the tool to be used (i.e., the target-to-movementtransformation), and the other cue indicating the target ofthe action. The participant has to derive the bodily move-ment parameters from these cues. There are (at least) twopossibilities to represent the tool-use action under theseconditions. Following the ideomotor principle (Herbart1825; Greenwald 1970; HoVmann 1993; Prinz 1997), atool-use action might be cognitively represented withrespect to the intended goal and its associated sensoryeVects, whereas the corresponding motor activity is Xexiblytuned in (cf. Kunde et al. 2007; Mechsner et al. 2001;Müsseler et al. 2008). According to this view, the target-movement transformation might be considered a kind ofmotor or environmental constraint that is taken into accountto dynamically compute the bodily movement parameters,but is not included in the high-level representation of theaction. Alternatively, the action might also be representedwith respect to the tool and the target-to-movement trans-formation it implements. This representation could take theform of a generalized motor program (Schmidt 1975, 1986)that includes the target-to-movement transformation of thetool as an abstract invariant, and the target as a variable, sit-uationally deWned parameter value.

In a previous study on unimanual tool-use actions(Massen and Prinz 2007a), we employed a precuing methodto investigate the cognitive representation of tool-useactions. Participants had to touch targets in space withdiVerent kinds of levers. In each trial, participants receivedeither a precue about the target location to be touched or aboutthe lever (transformation) that had to be used in the upcomingtrial. If tool-use actions are represented as generalized motor

programs with the tool transformation as an invariant andthe spatial target as a parameter, then giving participantsadvance information about the transformation should bemore eVective than giving advance information about thespatial target. This is because setting up a motor program ismore time-consuming than specifying only a parameter ofthis program (cf. Stelmach and Teulings 1983; Roth 1988;Quinn and Sherwood 1983). On the other hand, precuingthe tool transformation should not be very eVective when itis taken into account later in the processing stream (i.e., nota central level), because the processes that determine thepatterns of muscle activation remain outside consciousawareness and should therefore not be susceptible to strate-gic preparatory processes.

The results of this study indicated a large reaction timebeneWt when the tool transformation was precued, whereasprecuing the target was generally not eVective. Theseresults provided Wrst evidence for the notion that tool-useactions are cognitively represented with respect to the tooltransformation, the spatial target being a variable parameterof the motor program.

However, the validity of the precuing method as a meansto investigate movement programming processes has beenquestioned (Goodman and Kelso 1980; Larish 1986), forinstance, because it forces participants to program singleparameters of an action in a sequential way, which mightnot be the case under more natural conditions outside thelaboratory. Furthermore, in the study by Massen and Prinz(2007a), movement targets were directly cued and did notcarry symbolic meaning, which might have led participantsto adopt an action representation based on the transforma-tion, rather than on the target. Finally, representations basedon action goals or targets might be more importantin situations where some kind of coordination is required,for instance, coordination with another person, or bimanualcoordination.

In the present study, we investigated whether diVerentways of cuing target locations and tool transformations inbimanual tool use aVect the eYciency with which actionsare programmed. Participants had to simultaneously touchtwo target locations in space with two levers that wereoperated by the left and right hand, respectively (cf. Fig. 1).The levers implemented either a compatible or an incom-patible tool transformation. In some trials, the hand move-ment had to be executed in a direction that was compatiblewith the direction of the target (and hence the direction inwhich the eVective part of the tool moved), whereas inother trials, the hand movement had to be executed in adirection that was incompatible with the direction of thetarget (and hence the direction in which the eVective part ofthe tool moved). Target direction and tool transformationcould either be congruent or incongruent for the two hands.In three diVerent groups (cf. Fig. 3), participants either

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received only direct spatial cues specifying targets and tooltransformations for a bimanual tool-use action (group 1),received a symbolic letter cue specifying the tool transfor-mations for a bimanual tool-use action, while the targetswere indicated by direct spatial cues (group 2), or receiveda symbolic letter cue specifying the targets for the upcom-ing action, the transformations being indicated by directspatial cues (group 3). The basic research question waswhether diVerent ways of cuing the action would aVect theoverall eYciency of programming. If tool-use actions arerepresented as generalized motor programs with the tooltransformation as an invariant and the spatial target as aparameter, then symbolic cuing of the transformationsshould help participants to focus on the relevant aspect ofthe task and speedup programming of the action. Further-more, transformation congruency should be more importantthan target congruency in programming bimanual actions.If tool-use actions are cognitively represented with respectto the intended goal and its associated sensory eVects,1 thensymbolic cuing of the targets should induce a more eYcientrepresentation of the action and lead to faster reactiontimes. Furthermore, target congruency should be moreimportant than transformation congruency.

Methods

Participants

Three groups of 20 right-handed participants from the sub-ject pool of the Max-Planck-Institute in Leipzig served asparticipants. In each group, ten of the participants werewomen. The mean ages were 24.2 (group 1), 23.7 (group 2)and 25.0 years (group 3). Participants were paid 7 Euro fortheir participation. The local ethics committee approved thestudy, and all participants gave informed consent.

Apparatus

The apparatus consisted of a pair of metal levers(42 cm £ 1 cm) that were mounted on two plastic plates(each 25.5 cm £ 22 cm in size) and oriented parallel to thefrontal horizontal axis of the body. They had to be graspedand operated at the lateral ends, which were in a distance of89 cm from one another (cf. Fig. 1). Each lever was mov-able in the horizontal plane around a pivotal point in itsmiddle.

For each lever, there were four possible target locations.Two of them required a movement of the lever in the direc-tion toward the participant, and two required a movementin the opposite direction, away from the participant. Fur-thermore, they diVered in position relative to the lever’spivotal point. (Two targets were located between the piv-otal point and the lever’s handle, and two were locatedbetween the pivotal point and the lever’s distal end, cf.Fig. 1.) The target locations were illuminable by lightdiodes situated under the plastic surface of the plate. Thelateral distance of each target to the pivotal point was4.75 cm, and the distance in the vertical/sagittal directionwas 3.25 cm. The lever had to be rotated by about 34.4° totouch either of these targets.

If one of the targets near the lever’s handle was illumi-nated, the handle had to be moved toward the body inorder to touch the body-near target (cf. Fig. 2, secondrow, right side) and away from the body in order to touchthe more distant one (cf. Fig. 2, second row, left side). Inthis case, the proximal part of the lever hits the target andthe relationship between target direction and movementdirection is compatible. If one of the targets near thelever’s distal end was illuminated, the handle had to berotated toward the body in order to touch the more distanttarget (cf. Fig. 2, third row, right side) and away from thebody in order to touch the body-near target (cf. Fig. 2,fourth row, right side). In this case, the distal part of thelever hits the target and there is an incompatible relation-ship between target direction and body movement direc-tion (because the handle has to be moved in the directionopposite to the target).

1 We would like to emphasize here that we not do not mean to say thateither only the transformation or only the target is represented. Ofcourse, both components of the action have to be take into account andtherefore for both, some kind of representation is needed. Rather, thequestion is whether there are diVerences in the level at which the com-ponents are represented (e.g., more central or more peripheral level) orin the functions they take in the action plan (i.e., one is the invariant ofan action and one a parameter).

Fig. 1 Illustration of basic experimental setup with start position oflevers. Each lever is rotatable around the pivotal point in its middle. Ineach trial, one of the four possible target locations for each lever hasto be touched. The participant has to decide in which direction (towardor away from the body) to move the lever handles in order to touch thetargets

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The apparatus was controlled by a standard IBM-compatible computer and connected to it via the parallelport. The light diodes could be turned on and oV by sig-nals from the computer. Furthermore, it was possible tolock and unlock each lever with the experimental soft-ware by activating magnets attached beneath it. In turn,the computer received signals about the position of eachlever by means of an incremental shaft encoder (resolu-tion 6,000 counts per revolution). Movement initiationin one or the other direction was deWned as a leverrotation of 0.06° in a clockwise or counterclockwisedirection.

Design and procedure

The experiment took place in a dimly illuminated room.Participants in the group with symbolic cuing of the targetdirection Wrst had to memorize a mapping between one ofthe four letters I, G, M, and U and one of the four targetdirection combinations for the two hands (left body-neartarget + right body-near target, left body-near target + rightbody-far target, left body-far target + right body-near tar-get, and left body-far target + right body-far target). Partici-pants in the group with symbolic cuing of the tooltransformations had to memorize a mapping between oneof the four letters I, G, M, and U and one of the four tooltransformation combinations for the two hands (left com-patible transformation + right compatible transformation,left compatible transformation + right incompatible trans-formation, left incompatible transformation + right compat-ible transformation, and left incompatible transformation +right incompatible transformation). The assignment of thefour letters to the conditions was counterbalanced betweenparticipants. After participants had learned the mapping,they received two practice blocks (32 trials each). In theWrst block, only one target was illuminated in each trial andthey had to touch it with the lever, thus getting acquaintedwith the basic procedure and with operating the levers. Thesecond practice block was exactly the same as the experi-mental blocks for the respective group. Each trial startedwith an intertrial interval of 2,000 ms, during which partici-pants had to Wxate a cross on a small 8-inch monitor(15.6 cm £ 24.1 cm) between the two levers. In the groupwith symbolic cuing of the targets, a letter signaling the tar-get direction combination for the two hands appeared onthe monitor (e.g., left body-near target and right body-fartarget). In addition, for each lever either the two diodes nearthe handles (indicating a compatible transformation) or thetwo diodes near the lever’s distal end (indicating an incom-patible transformation) were illuminated (cf. Fig. 3, bottompanel).

In the group with symbolic cuing of the transformations,a letter signaling the transformation combination for thetwo hands appeared on the monitor between the levers(e.g., left compatible and right incompatible transforma-tion). In addition, for each lever either the two body-neardiodes or the two body-far diodes were illuminated (cf.Fig. 3, middle panel). These diodes directly indicatedwhether target directions were toward or away from theparticipant, without giving information about the levertransformations. In the group with direct cuing, only twotarget diodes (one for each lever) were turned on, thus spec-ifying both, the transformation and the target (cf. Fig. 3, toppanel). Simultaneously with the appearance of the stimuliin the three groups, the levers were unlocked. Participantswere instructed to initiate the movements of the two levers

Fig. 2 Illustration of the four basic experimental conditions.Transformations are either congruent (Wrst two rows) or incongru-ent (last two rows) for the two levers. In addition, target directionsare either congruent (Wrst and third row) or incongruent (secondand last row) for the two levers. The Wrst two rows show theexample of compatible transformations for both levers. The thirdand fourth row show a compatible transformation for the left andan incompatible one for the right hand and lever

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simultaneously. Reaction time for each hand was deWned asthe time from the lighting of the diodes to the levers’ leav-ing of the resting position. Movement time for each hand

was measured from the point in time when the lever left itsresting position until a target was touched. After two targetpoints had been touched (one with each lever), the partici-pant received auditory feedback whether both reactionswere correct and that the levers should be moved back tothe resting position. If participants had not reacted simulta-neously with both levers in the respective trial (i.e., thediVerence between both hands was larger than 200 ms),they received an additional feedback (stressing the impor-tance of reacting simultaneously) after the levers hadreached the resting position. Then, the next trial started.

Participants went through six experimental blocks of 64trials. Each of the 16 possible combinations of target direc-tion and tool transformation (four for each hand) appearedequally often and in a randomized order in each block. Thisresulted in four possible combinations of target (direction)congruency and transformation congruency (cf. Fig. 2).

Results

As dependent variables, reaction times (RT) and movementtimes (MT) for correct responses, as well as error rates,were analyzed. Errors were all reactions in which at leastone of the movements was initiated in the wrong movementdirection (irrespective of whether it was corrected or not).Trials were excluded from analysis when the lag betweenboth hands was larger than 200 ms (3.8% of the data). Inaddition, trials were excluded from RT and MT analysis if(a) RT of one of the movements was below 100 ms orabove 5,000 ms (0.3% of the data) and (b) MT of one of themovements was above 1,200 ms (1.8% of the data). RTs(and MTs) were averaged across hands. An alpha level of.05 was used for all statistical tests. We analyzed the datausing mixed model analyses of variance with group (group1: direct cuing, group 2: symbolic cuing of transformation,group 3: symbolic cuing of target direction) as between-subjects factor and transformation congruency (congruentvs. incongruent) and target congruency (congruent vs.incongruent) as within-subjects factors.

Reaction times

Reaction times are depicted in Fig. 4 (top panel).The analysis of variance revealed a signiWcant main

eVect of group (F(2, 57) = 37.2; P < .001; �p2 = .57). Post

hoc tests showed that the group with direct cuing had sig-niWcantly shorter reaction times (908 ms) than the groupwith symbolic cuing of the transformation (1,186 ms;P < .05), whereas this group had signiWcantly shorter reac-tion times than the group with symbolic cuing of targetdirection (1,705 ms; P < .001). Reaction times weregenerally faster with congruent (1,138 ms) as compared to

Fig. 3 Illustration of cuing stimuli in the three groups. In the Wrst group(top panel), two diodes (one for each hand and lever) directly speciWedthe targets (and transformations) for the action. In the second group(middle panel), a letter (e.g., G) indicated a combination of transforma-tions for the two levers (e.g., compatible/compatible), whereas targetdirections were indicated by two diodes in the respective directions. Inthe third group (bottom panel), a letter (e.g., G) indicated a combinationof targets for the two levers (e.g., near/near), whereas the transforma-tions were indicated by two diodes at the respective locations

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incongruent (1,395 ms) transformations and with congruent(1,189 ms) as compared to incongruent (1,344 ms) targets,resulting in signiWcant main eVects of transformation con-gruency (F(1, 57) = 169.0; P < .001; �p

2 = .75) and targetcongruency (F(1, 57) = 63.2; P < .001; �p

2 = .53). TheeVect of target congruency was larger for congruent (�216 ms) than for incongruent transformations (� 93 ms),resulting in a signiWcant interaction between transformationand target congruency (F(1, 57) = 30.3; P < .001; �p

2 =.35). There was also a signiWcant interaction between groupand transformation congruency (F(2, 57) = 3.6; P < .05;�p

2 = .11). Post hoc tests revealed that the eVect of transfor-mation congruency was signiWcantly smaller in the groupwith direct cuing (� 184 ms) than in the group with sym-bolic cuing of the transformation (� 308 ms; P < .05),whereas it did not diVer signiWcantly between the groupwith symbolic cuing of the transformation and the groupwith symbolic cuing of the target (� 280 ms; P > .05). Thethree-way interaction between group, transformation con-gruency and target congruency also reached statistical sig-niWcance (F(2, 57) = 5.1; P < .01; �p

2 = .15). Thisinteraction was due to a larger diVerence in target congru-ency for congruent and incongruent transformations in thegroup with symbolic cuing of the target (� 219 ms) as com-

pared to the group with symbolic cuing of the transforma-tion (� 48 ms; P < .05).

None of the other eVects reached statistical signiWcance.

Error rates

Error rates are depicted in Fig. 4 (bottom panel). TheANOVA revealed a signiWcant main eVect of group(F(2, 57) = 3.6; P < .05; �p

2 = .11). Post hoc compari-sons indicated a signiWcant diVerence between thegroups with symbolic cuing of the transformation (7.9%)and symbolic cuing of the target (14.8%) that was due toa higher error rate in the group with symbolic cuing ofthe target (P < .05). The diVerence between the groupwith direct cuing (12.0%) and the group with symboliccuing of the transformation (7.9%) was not signiWcant(P > .12). There were also signiWcant main eVects oftransformation congruency (F(1, 57) = 134.1; P < .001;�p

2 = .70) and target congruency (F(1, 57) = 67.2;P < .001; �p

2 = .54) that were due to generally lowererror rates with congruent (6.1%) as compared to incon-gruent (17.0%) transformations and congruent (7.8%) ascompared to incongruent (15.4%) target directions forthe two hands. The only other signiWcant eVect was theinteraction between group and transformation congru-ency (F(2, 57) = 14.2; P < .001; �p

2 = .33) that was dueto a smaller diVerence between congruent and incongru-ent transformations in the group with symbolic cuing ofthe transformation (�4.1%) as compared to the groupwith direct cuing (�12.5%; P < .01) or to the group withsymbolic cuing of the target (�16%; P < .01).

Movement times

Movement times are shown in Table 1.SigniWcant main eVects of transformation congruency

(F(1, 57) = 10.6; P < .01; �p2 = .16) and target congru-

ency (F(1, 57) = 4.5; P < .05; �p2 = .07) reXected shorter

movement times with congruent (357 ms) as compared toincongruent (364 ms) transformations and with congruent(358 ms) as compared to incongruent (364 ms) targetdirections. For congruent transformations, congruent tar-get directions resulted in shorter movement times(348 ms) than incongruent ones (366 ms), whereas forincongruent transformations, movement times werelonger with congruent (367 ms) than with incongruent(362 ms) target directions. This resulted in a signiWcantinteraction between transformation congruency and targetcongruency (F(1, 57) = 21.1; P < .001; �p

2 = .27). Neitherthe main eVect of group (F < 1) nor any of the interactionswith group reached statistical signiWcance (F(2, 57) = 1.4for the interaction with transformation congruency, allother F’s < 1).

Fig. 4 Mean RT (in ms, top panel) and Error Rate (in %, bottom pan-el) as a Function of Group, Transformation Congruency and TargetCongruency. Error bars indicate standard deviations. Note inc incon-gruent, c congruent

Group

0

500

1000

1500

2000

2500

direct cuing symbolic cuing oftransformation

symbolic cuing of target

Note. c.= congruent,inc.= incongruent

RT

(in

ms)

Transformations c.+targets c.

Transformations c.+targets inc.

Transformations inc.+targets c.

Transformations inc.+targets inc.

Group

0

5

10

15

20

25

30

35

40

45

direct cuing symbolic cuing oftransformation

symbolic cuing of target

Note. c.= congruent,inc.= incongruent

Err

or

rate

(in

%)

Transformations c.+targets c.

Transformations c.+targets inc.

Transformations inc.+targets c.

Transformations inc.+targets inc.

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Discussion

In the present study, we investigated whether diVerent waysof cuing bimanual tool-use actions would result in diVerentaction representations and aVect the eYciency of actionprogramming. In three groups, target directions and tooltransformations were either directly cued (group 1) orpartly symbolically cued with either symbolic cuing of thetransformations (group 2) or symbolic cuing of the targets(group 3). Results indicated only minor diVerences betweenthe groups with direct cuing and the group with symboliccuing of the transformation that seemed to be largely drivenby a speed-accuracy trade-oV. While the group with directcuing had faster overall reaction times, there was also ahigher error rate (although not signiWcant) in this groupwhen compared to the group with symbolic cuing of thetransformation. In addition, in the group with direct cuingthe eVect of transformation congruency was smaller inreaction times, but larger in error rates.

In contrast to the minor diVerences between these twogroups, overall performance in the group with symboliccuing of the targets was considerably worse. Participants inthis group exhibited both increased overall reaction timesand increased error rates when compared to the group withsymbolic cuing of the transformations. Furthermore, inerror rates, the main eVect of transformation congruencywas more pronounced when participants prepared for targetdirections (and not for the transformations) on the basis ofthe symbolic cue. Finally, the reduced performance in thegroup with symbolic cuing of the targets seemed to be lesspronounced in the easiest condition with congruent targetdirections and congruent transformations, leading to athree-way interaction in RT.

Apart from these group diVerences, the general patternof results was characterized by signiWcant main eVects oftransformation and target congruency. The target congru-ency eVect was smaller when lever transformations werediVerent for the two hands, and in movement times, it waseven reversed. A possible explanation for the latter eVectcould be that in the conditions with congruent tool transfor-mations, the directions in which the participants’ armsmove are congruent when target directions are also congru-ent, and incongruent when target directions are also incon-

gruent. Hence, the diVerence between these two conditionsreXects the combined eVects of target congruency and bodymovement congruency on performance. On the other hand,for incongruent tool transformations, congruent targetdirections go along with incongruent body movementdirections, whereas incongruent target directions result incongruent body movement directions. Thus, a diVerencebetween these two conditions reXects the eVect of targetcongruency minus a (potential) eVect of body movementcongruency on performance. A better performance withincongruent targets would reXect a larger body movementcongruency eVect. A more extensive discussion of theseeVects can be found in a related paper (Massen and Sattler2010).

The pattern of results obtained suggests that participantsadopted diVerent action representations depending onwhich component of the actions was cued symbolically.The results of other studies (e.g., Diedrichsen et al. 2003,2006; Weigelt et al. 2007; Spijkers et al. 1997; Heuer andKlein 2006) have shown that participants represent anaction in terms of those features that are explicitly (andsymbolically) cued. From this, it may be inferred that thegroup with symbolic cuing of the transformations in ourstudy represented the upcoming action in terms of the twotool transformations involved (e.g., “execute a compatiblelever action with the left hand and an incompatible one withthe right”), with target directions being derived from thedirect spatial cues presented. This seemed to be a muchmore eYcient representation than that of the group withsymbolic cuing of the targets. Presumably, this group repre-sented the action in terms of the two target directions (e.g.,“touch the distant target with the left lever and the near onewith the right lever”), whereas the tool transformationswere then derived from the direct spatial cues presented.

Another potential explanation for the results obtained isrelated to the processing speed of direct and symbolic cues.Normally, the information transmitted by direct cues isavailable faster than the information conveyed by symboliccues. If one further assumes that it takes longer to programone component (e.g., the target) of the tool-use action thanto program the other (e.g., the transformation), then accord-ing to a cognitive slack-logic (e.g., McCann and Johnston1992) the overall programming time might be shorter if the

Table 1 Movement times (MT, in ms, standard deviations in brackets) as a function of group and transformation/target congruency combination

Group Transformations congruent, targets congruent

Transformationscongruent, targets incongruent

Transformations incongruent, targets congruent

Transformations incongruent, targets incongruent

Direct cuing 330 (141) 348 (131) 348 (133) 344 (132)

Symbolic cuing of transformation 341 (158) 355 (141) 362 (150) 357 (148)

Symbolic cuing of target 374 (98) 395 (111) 390 (103) 384 (109)

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faster component (i.e., the transformation) was cued sym-bolically (because this component would have to wait forthe slower one anyway). However, in our case this explana-tion seems rather unlikely, because previous studies haveshown that it takes longer to program the transformationrather than the spatial target of a tool-use action. Forinstance, the study by Massen and Prinz (2007a) showedthat precuing of a tool transformation is very eVective,whereas precuing the target of a tool-use action is not. Iftool-use actions are represented as a kind of generalizedmotor program that contains the tool transformation as aninvariant and the spatial target as a situationally variableparameter value, then preparing for the motor programshould take longer than preparing for a parameter value.Hence, a precue for the transformation can be assumed tobe more eVective than a precue for the spatial target, a pat-tern that was conWrmed by the data.

The only possibility to explain the current pattern ofresults in terms of processing speed would be to assumethat a process that is slow and eVortful anyway (like settingup the motor program for a tool-use action) suVers lessfrom the additional translational eVort imposed by sym-bolic cues than a process that is fast (like programming thetarget of a tool-use action). Further research is needed todecide whether this explanation is valid.

Further evidence for the dominance of tool transforma-tions in cognitive representations of tool-use actions comesfrom the transformation congruency and target congruencyeVects. Whereas the main eVect of transformation congru-ency was large and occurred in a consistent way for diVer-ent dependent variables and across diVerent levels of thetarget congruency factor, the main eVect of target congru-ency was smaller and less consistent. This pattern of resultsalso points to the signiWcance of tool transformations in theprogramming and/or representation of tool-use actions.

The results obtained support the view of a dominance ofthe tool transformation in the cognitive representation oftool-use actions and show that this dominance is even pres-ent under conditions that usually favor goal- or target-basedcoding of actions, like in bimanual coordination (e.g.,Kunde and Weigelt 2005; Hughes and Franz 2008). Fur-thermore, they suggest a close relationship between the rep-resentation of arbitrary mappings between visual stimuliand associated motor responses often investigated in task-switching research and the representation of mappings (i.e.,transformations) between tool and hand positions in tooluse. For instance, it has long been known that it is muchmore eVective to give participants advance informationabout a stimulus–response mapping or rule that they haveto apply to a certain stimulus than to provide informationabout the stimulus in advance (ShaVer 1965, 1966; Bern-stein and Segal 1968). Similar results have been obtainedfor precuing cognitive operations like those applied in basic

arithmetics (Biederman 1973; Sohn and Carlson 1998;Sudevan and Taylor 1987).

Additional support for the notion that tool-use actionsare cognitively represented in terms of the tool transforma-tion implemented by the tool comes from studies on actionobservation in tool use. Massen and Prinz (2007b, 2009)and Massen (2009) had participants observe the tool-useaction of another person in one trial and perform a similaraction themselves in the subsequent trial. The resultsshowed that observing a tool-use action with the same tool(transformation), but with a diVerent target, was more bene-Wcial for the subsequent own action than observing a tool-use action with the same target, but with a diVerent tooltransformation. These results demonstrate observationalpriming of the tool transformation in the observation of tooluse and further support the view of a central role of the tooltransformation in the cognitive representation of tool use.

Acknowledgments We would like to thank Henrik Grunert forconstructing the lever device, and Luciana Bruel, Ramona Kaiser,Katharina Horstkotte and Julia Michael for their help with data acqui-sition. This work has been Wnancially supported by a grant from theGerman Research Foundation (MA 2584/2-1) to Cristina Massen.

References

Bernstein I, Segal EM (1968) Set and temporal integration. PerceptPsychophys 4:233–236

Biederman I (1973) Mental set and mental arithmetic. Mem Cogn1:383–386

Diedrichsen J, Hazeltine E, Kennerly S, Ivry RB (2001) Moving todirectly cued locations abolishes spatial interference duringbimanual actions. Psychol Sci 12:493–498

Diedrichsen J, Ivry RB, Hazeltine E, Kennerly S, Cohen A (2003)Bimanual interference associated with the selection of target loca-tions. J Exp Psychol Hum Percept Perform 29:64–77

Diedrichsen J, Grafton S, Albert N, Hazeltine E, Kennerly S, Cohen A(2006) Goal-selection and movement-related conXict duringbimanual reaching movements. Cereb Cortex 16:1729–1738

Goodman D, Kelso JAS (1980) Are movements prepared in parts? Notunder compatible (naturalized) conditions. J Exp Psychol Gen109:475–495

Greenwald AG (1970) A double stimulation test of ideomotor theorywith implications for selective attention. J Exp Psychol 84:392–398

Herbart JF (1825) Psychologie als Wissenschaft neu gegründet aufErfahrung, Metaphysik und Mathematik. August Wilhelm Unzer,Königsberg

Heuer H, Klein W (2006) The inXuence of movement cues onintermanual interactions. Psychol Res 70:229–244

HoVmann J (1993) Vorhersage und Erkenntnis. Die Funktion vonAntizipationen in der menschlichen Verhaltenssteuerung undWahrnehmung. Hogrefe, Göttingen

Hughes CML, Franz EA (2008) Goal-related planning constraints inbimanual grasping and placing of objects. Exp Brain Res 188:541–550

Kunde W, Weigelt M (2005) Goal congruency in bimanual objectmanipulation. J Exp Psychol Hum Percept Perform 31:145–156

Kunde W, Müsseler J, Heuer H (2007) Spatial compatibility eVectswith tool use. Hum Fact 49:661–670

123

Exp Brain Res (2012) 218:227–235 235

Larish DD (1986) InXuence of stimulus-response translations onresponse programming: examining the relationship of arm, direc-tion, and extent of movement. Acta Psychol 61:53–70

Massen C (2009) Observing human interaction with physical devices.Exp Brain Res 199:49–58

Massen C, Prinz W (2007a) Programming tool-use actions. J Exp Psy-chol Hum Percept Perform 33:692–704

Massen C, Prinz W (2007b) Activation of action rules in action obser-vation. J Exp Psychol Learn Mem Cogn 33:1118–1130

Massen C, Prinz W (2009) Movements, actions and tool-use actions:an ideomotor approach to imitation. Philos Trans R Soc B364:2349–2358

Massen C, Sattler C (2010) Bimanual interference with compatible andincompatible tool transformations. Acta Psychol 135:201–208

McCann RS, Johnston JC (1992) Locus of the single-channel bottle-neck in dual-task interference. J Exp Psychol Hum Percept Per-form 18:471–484

Mechsner F, Kerzel D, Knoblich G, Prinz W (2001) Perceptual basisof bimanual coordination. Nature 414:69–73

Müsseler J, Kunde W, Gausepohl D, Heuer H (2008) Does a tool elim-inate spatial compatibility eVects? Eur J Cogn Psychol 20:211–231

Prinz W (1997) Perception and action planning. Eur J Cogn Psychol9:129–154

Quinn JT, Sherwood DE (1983) Time requirements of changes in pro-gram and parameter variables in rapid ongoing movements. J MotBehav 15:163–178

Roth K (1988) Investigations on the basis of the generalized motorprogramme hypothesis. In: Meijer OG, Roth K (eds) The motor-action controversy. Elsevier Science, Amsterdam, pp 261–288

Schmidt RA (1975) A schema theory of discrete motor skill learning.Psychol Rev 82:225–260

Schmidt RA (1986) Motor control and learning, 2nd edn. HumanKinetics, Urbana-Champaign

ShaVer LH (1965) Choice reaction with variable S-R mapping. J ExpPsychol 70:284–288

ShaVer LH (1966) Some eVects of partial advance information onchoice reaction with Wxed or variable S-R mapping. J Exp Psy-chol 72:541–545

Sohn MH, Carlson RA (1998) Procedural frameworks for simple arith-metic skills. J Exp Psychol Learn Mem Cogn 24:1052–1067

Spijkers W, Heuer H, Kleinsorge T, van der Loo H (1997) Preparationof bimanual movements with same and diVerent amplitudes:speciWcation interference as revealed by reaction time. Acta Psy-chol 96:207–227

Spijkers W, Heuer H, Steglich C, Kleinsorge T (2000) SpeciWcation ofmovement amplitudes for the left and right hands: evidence fortransient parametric coupling from overlapping-task perfor-mance. J Exp Psychol Hum Percept Perform 26:1091–1105

Stelmach GE, Teulings HL (1983) Response characteristics of pre-pared and restructured handwriting. Acta Psychol 54:51–67

Sudevan P, Taylor DA (1987) The cuing and priming of cognitiveoperations. J Exp Psychol Hum Percept Perform 13:89–103

Weigelt M, Rieger M, Mechsner F, Prinz W (2007) Target-related cou-pling in bimanual reaching movements. Psychol Res 71:438–447

123