Acta Psychologica 151 (2014) 74–82

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Acta Psychologica

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Line-bisectioning and obstacle avoidance: Evidence forseparate strategies

Alasdair I. Ross a, Thomas Schenk b, Constanze Hesse a,⁎a School of Psychology, University of Aberdeen, United Kingdomb Neurology, University of Erlangen-Nuremberg, Germany

⁎ Corresponding author at: School of Psychology, UniveBuilding (Room T11), Aberdeen AB24 3FX, United Kingdo

E-mail address: c.hesse@abdn.ac.uk (C. Hesse).

http://dx.doi.org/10.1016/j.actpsy.2014.05.0190001-6918/© 2014 Elsevier B.V. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Article history:Received 16 December 2013Received in revised form 26 May 2014Accepted 27 May 2014Available online xxxx

PsycINFO classification:230023232330

Keywords:PerceptionActionObstacle avoidanceLine bisection taskReachingStart position

Previous studies have frequently applied a combination of line-bisection tasks (in which participants indicate themiddle of a line) and obstacle avoidance tasks (in which participants move their hand between two obstacles)with the aim of revealing perception–action dissociations in certain neurological disorders, such as visual formagnosia and optic ataxia. However, valid conclusions about the underlying processing pathways can only bedrawn if participants apply the same strategy in both tasks (i.e. finding the middle between the obstacles). Yet,this assumption has never been tested directly. In this experiment, we investigatedwhether participants performobstacle avoidance and line-bisectioning using similar strategies by manipulating the position of the obstaclesand the start position of the hand relative to the obstacles. Our results indicate that the lateral hand positionduring obstacle avoidance does not only vary as a function of obstacle location but also strongly depends onthe start position. Moreover, participants showed increased sensitivity to obstacle shifts occurring closer to thehand's start position. In contrast, during line-bisectioning the sensitivity to obstacles shifts was unaffected bythe hand's start position. The findings suggest that during obstacle-avoidance the need to keep a safe distancefrom the obstacles is balancedwith the requirement tominimise energetic demands. In contrast, themain inten-tion during line-bisectioning is to move to the perceived midpoint as accurately as possible. The fact that verydifferent constraints underlie trajectory planning in both tasks implies that caution has to be taken wheninterpreting differences in performance levels.

© 2014 Elsevier B.V. All rights reserved.

1. Introduction

Manual line-bisection tasks, in which patients are asked to indicatethe midpoint of lines varying in length, have been used for over acentury in the neuropsychological assessment of patients sufferingfrom unilateral cerebral lesions such as hemineglect and hemianopia(Axenfeld, 1894; Barton & Black, 1998; Best, 1917; Kerkhoff & Bucher,2008; Liepmann & Kalmus, 1900; Reuter-Lorenz & Posner, 1990;Schenkenberg, Bradford, & Ajax, 1980; Schuett, Dauner, & Zihl, 2011).Bymeasuring the size and direction of the bias patients showwhen iden-tifying the midpoint of a line, these common perceptual deficits can berevealed relatively reliably. In more recent neuropsychological studies,the classical line-bisection paradigm, usually applied as a paper–penciltask, was experimentally modified and used in combination with anobstacle-avoidance task in order to detect perception–action dissoci-ations in certain neurological disorders (McIntosh, McClements,Dijkerman, Birchall, & Milner, 2004; McIntosh et al., 2004; Riceet al., 2006; Schindler et al., 2004).

rsity of Aberdeen,WilliamGuildm. Tel.: +44 1224 273215.

In these tasks, the experimental setup consisted of a wooden boardthat was placed in front of the participant and on which two obstaclescould be mounted at varying positions. The obstacles were positionedto the left and right of the centre of the board, approximately halfwaybetween the start position of the hand and a target zone. The gapformed between the obstacles could either be symmetrical, meaningthat both obstacles were placed at the same distance from the midline,or asymmetrical, meaning that one of the obstacleswas shifted closer tothe midline. In the line-bisection task, participants were asked to pointto the midpoint of the gap formed between the two obstacles as accu-rately as possible (equivalent to a traditional paper–pencil task). In con-trast, in the obstacle avoidance task, participants were instructed toquickly move from the start position to the target zone behind the ob-stacles with their hand passing through the gap. The rationale for apply-ing these two tasks is straightforward: Both tasks, line-bisectioning andobstacle avoidance, are assumed to require a spatial response from theparticipant that takes into account obstacles positioned on either sideof the visual field (McIntosh, McClements, Dijkerman, et al., 2004).However, at the same time, both tasks are fundamentally differentwith regard to the question of where in the brain the visual informationis processed. According to the perception–actionmodel, visual informa-tion is processed in different areas of the brain depending onwhether a

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perceptual task (such as bisectioning) or a visuomotor task (such as ob-stacle avoidance) has to be performed (Goodale & Milner, 1992; Milner& Goodale, 1995). Specifically, the model suggests that vision forperception is processed within the ventral stream while vision for ac-tion is processed within the dorsal stream. Following this reasoning,contrasting participants' performance in a line-bisection task and anobstacle avoidance task therefore constitutes a suitable approach to re-veal potential perception–action dissociations.

Interestingly, selective deficits in obstacle avoidance and line-bisection tasks have indeed been observed in patients with certaincortical lesions. In line with the suggested specialisation of the dorsaland the ventral streams, it was found that patients who suffer fromdamage to ventral stream areas were able to perform well in the ob-stacle avoidance task but performed significantly less accurately thanhealthy control subjects in the perceptual line-bisection task (McIntosh,McClements, Dijkerman, et al., 2004; McIntosh, McClements, Schindler,et al., 2004; Rice et al., 2006). The complementary pattern of resultswas observed in the presence of dorsal streamdamage. Patientswith dor-sal stream damage performed normally in the line-bisection task butwere unable to adjust their handmovements to the position of the obsta-cles in the obstacle avoidance task (Schindler et al., 2004). At first glance,the discovery of an existing dissociation between bisectioning and obsta-cle avoidance performance in brain damaged patients seems to providevalid empirical support for the perception–action model. However, thisview is not without problems. Firstly, in order to claim dissociations be-tween action and perception, it has to be assumed that the obstacleavoidance task provides a visuomotor equivalent of line-bisectioningand that therefore, both tasks measure the same visual processes in twodifferent domains (perception and action). So far, the only evidencesupporting this claim comes from the observation that healthy partici-pants tend to pass their hand approximatelymidway between the obsta-cles, even if no goal-position is specified in the target area (McIntosh,McClements, Schindler, et al., 2004). Secondly, a valid comparison be-tween obstacle avoidance and line-bisection performance can only bemade if participants generally employ the same strategy in both tasks(i.e. finding the middle between the obstacles).

Given that participants obtain different instructions in the line-bisection (moving accurately to the perceived middle) and the obstacleavoidance tasks (moving quickly to any point within the target area), itstands to reason that participants may use different movement strate-gies to accomplish the two tasks respectively. Previous researchershave already acknowledged that the superficial resemblance of obstacleavoidance behaviour and bisectioning may depend on the “particularspatial parameters employed” (McIntosh, McClements, Dijkerman,et al., 2004, p. 1108). In other words, the finding that participants usual-ly select a trajectory that roughly passes through the middle of the gapformed by the obstacles may be partly attributed to the fact that thestart position of the hand was always centrally aligned to the obstacleconfiguration. In fact, the idea that the start position of the hand mayhave a crucial effect on the selected movement path is substantiatedby studies investigating and modelling human trajectory planning(Rosenbaum, Loukopoulos, Meulenbroek, Vaughan, & Engelbrecht,1995; Rosenbaum, Meulenbroek, & Vaughan, 2004; Rosenbaum,Meulenbroek, Vaughan, & Jansen, 2001; Vaughan, Rosenbaum, &Meulenbroek, 2001). According to this research, the key parametersfor trajectory planning are the start posture, the desired goal postureand the reduction of energetic requirements (Rosenbaum et al., 1995;Rosenbaum et al., 2001; Vaughan et al., 2001). The notion that a combi-nation of the hand's start position and the energetic task requirementsis taken into account when planning the trajectories in obstacle avoid-ance tasks fits nicely with the observation that the adjustments inmovement trajectories, in response to obstacle shifts, are generallymuch smaller in the obstacle avoidance task than in the correspondingbisection task. For example, McIntosh, McClements, Dijkerman, et al.(2004) found that in response to a 40 mm obstacle shift, participantsshifted their trajectory by about 20 mm in the bisection task (thus

successfully indicating the midpoint between the obstacles), but onlyby about 15 mm in the obstacle avoidance task (thus maintaining aslight lateral bias in the direction of the start position). These smallershifts in the movement trajectories may reflect the participants'tendency to selectmovements that are safe (i.e. sufficient safetymarginbetween hand and obstacle) and efficient (i.e. expending a minimumamount of energy during the movement by remaining close to thehand's start position, see also Soechting, Buneo, Herrmann, andFlanders (1995)) at the same time. However, while the hand's startposture and the energetic costs associated with the movement arelikely to affect trajectory planning in obstacle avoidance, it seems rel-atively self-evident that for line-bisectioning these parameters arelargely irrelevant.

In relation to themovement planningmodel suggested byRosenbaumet al. (Rosenbaum et al., 1995; Rosenbaum et al., 2004; Vaughan et al.,2001), the argument that safety is more important for obstacle avoidancethan for bisectioning can be interpreted as a difference in the constrainthierarchy of both tasks. Specifically, for successful line-bisectioning, theaccuracy constraint is greatest while the safety constraint is only ofminor importance. In contrast, for obstacle-avoidance, the accuracy con-straint is reduced compared to bisectioning while the safety constraints,aswell as themovement related energy expenditure, aremore importantfor trajectory planning. Furthermore, the model also suggests that in thepresence of obstacles, the preferably straight (and therefore most eco-nomical) movement path from the start position to the goal-positionneeds to be further constrained. This is assumed to be achieved by inte-grating a via-position into the movement program (Rosenbaum et al.,2001; Vaughan et al., 2001). As via-positions need to be consideredduringobstacle avoidance but not during line-bisectioning, profound differencesbetween the selectedmovement paths in the two taskswould be predict-ed. In summary, there is ample theoretical evidence that suggests that ob-stacle avoidance and line-bisectioning are dissimilar tasks that differ inmore general terms than just the underlying processing pathways.

In this study, we directly test the claim that participants use differentmovement strategies to accomplish line-bisectioning and obstacleavoidance tasks. We address this issue by varying the start position ofthe hand relative to the obstacles in both tasks. Even though it waspointed out that start postures play an important role when modellinghuman obstacle avoidance behaviour (Vaughan et al., 2001), no studyhas, up to now, systematically investigated the effects of different startpositions of the hand on trajectory planning. Therefore, our study willprovide insight into whether the previously reported tendency ofhumans to move through the middle of two obstacles can partly beattributed to the fact that the start position of the hand was alwayscentrally aligned to the obstacle configuration in previous paradigms.We predict that a variation of the start position of the hand relative tothe obstacle configuration will result in a systematic bias in obstacleavoidance performance but not in the corresponding perceptual bisec-tion task. In particular, we expect that during obstacle avoidance, themovement trajectories will remain biased in the lateral direction ofthe start position of the hand (reduced energy expenditure) and thatobstacles placed closer to the hand will cause larger deviations ofthe hand away from the obstacle (increased safety margin). Thisstudy will help to clarify under which conditions action (i.e. obstacleavoidance) and perception (i.e. line-bisectioning) tasks will result incomparable performance and if the paradigm can be used to draw con-clusions about the different properties of perceptual and visuomotorprocesses.

2. Methods

2.1. Participants

Twenty-four participants (17 female, 7 male, mean age = 25 years,range = 18–56 years) took part in the experiment. All participantshad normal or corrected-to-normal vision and were right-handed by

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self-report. The experimentwas approved by the local ethics committeeand participants provided written consent.

2.2. Procedure

All participants took part in twodifferent tasks: amotor task (obstacleavoidance) and a perceptual task (line-bisectioning).

The experimental setup for both tasks can be seen in Fig. 1a. Partic-ipants sat on a height-adjustable chair within a well-lit room. Through-out both tasks they were required to wear liquid-crystal shutter glasses(Plato System, Translucent Technologies, Toronto, Canada), which serveto rapidly block-out vision by shifting from a translucent to an opaquestate. A wooden board (650 × 800 mm) used for the presentation ofthe stimuli was placed on a table-top. A number of points were markedout on the board, including the start positions of the hand and the targetzone (Fig. 1). In total there were three start positions for the hand: onemarked in the middle of the board, which was aligned vertically to themidline of the body; one placed 50 mm to the left of the midline andone placed 50mm to the right of the midline. In the obstacle avoidancetask participants were asked to keep their hand upright with their ‘ring’(fourth) finger placed on top of the start position (see Fig. 1a–b). In theline-bisection task participantswere asked to place their indexfinger onthe start position and to point to where they thought the midpoint wasbetween the obstacles (see Fig. 1c).

The virtual horizontal line along which the obstacles were placedwas 250 mm in front of the virtual horizontal line along which thehands' starting position was varied (i.e. distance in y-direction) andthe straight-line distance from the mid start position to the middle ofthe target zone was 380 mm. The target zone was marked with a stripof green card (220 × 50 mm). The obstacles were black blocks (madeout of perspex), with a height of 150 mm and a base of 20 × 20 mm.They could be placed in four different positions forming either a gap of280 mm (with both obstacles at the outer most position) or a gap of240 mm (with one obstacle being moved 40 mm inward from the leftor right side while the other remained at the outer most position).Any visible holes marking different positions between the obstacleswere covered with strips of brown laminated card.

Hand trajectories were recorded using an infrared-based Optotrak3020 system (Northern Digital Incorporation, Waterloo, Ontario,Canada)with a sampling frequency of 200 Hz. In the obstacle avoidancetask three infrared light emitting diodes (IREDs) were attached tothe right hand: at the thumb (body of nail on the distal phalanx),wrist (anatomical-snuff-box) and index finger (radial border of thedistal phalanx) (see Fig. 1b). In the line-bisection task, only one

Fig. 1. (a) Image of the experimental setup used in the line-bisectioning and obstacle avoidancentre, right) and indicate the midpoint between the obstacles (bisectioning task) or to the tto perform the obstacle avoidance task. (b) In the obstacle avoidance task, the trajectory was dattached to the hand (at the thumb, wrist and index finger). The VM displayed in the image isone marker was attached to the index finger.

IRED was attached to the tip of the index finger (body of nail on thedistal phalanx) (see Fig. 1c). Prior to the experiment, the Cartesian(x, y, z) system used by the Optotrak was calibrated to the plane ofthe obstacle board (see Fig. 1a). The central start position, whichwas sagittally aligned with the horizontal midline of the board, wasset to the Cartesian origin of the coordinate system. The experimentwas programmed using MATLAB and the custom-built OptotrakToolbox (Franz, 2004).

Both the obstacle avoidance and the line-bisection tasks contained72 trials, with 24 trials for each of the three start positions of the handand each of the possible three obstacle positions presented 8 times foreach start position. The order of start positions was blocked andcounter-balanced across participants to prevent sequence effects. Theobstacle positions were allocated randomly within each block. Prior tothe start of each block, participants performed three practice trials.

All participants performed the obstacle avoidance task before theline-bisection task. This procedure was chosen after the results ofan initial pilot study (n = 5) revealed that performing the bisectiontask first biased participants to go through the middle in the obstacleavoidance task frequently prompting the question whether theyshould still do so.

2.3. Obstacle avoidance task

At the start of each trial participants positioned their right hand atthe start position and the shutter glasses became opaque. The experi-menter would then position each obstacle and manually start the trialwith a key press. Subsequently, the shutter glasses turned transparentand participants were given a 1.5 s free-viewing period. After the pre-view period, an auditory go-signal (1000 Hz, 100 ms) indicated for par-ticipants to begin their movement. Participants were instructed toquickly move their hand between the obstacles into the target zone.The shutter glasses remained transparent during the movement for3 s. Participants were given no instruction as to which area of the targetzone they should move toward. Note, that it was theoretically possibleto move the hand straight forward to the target zone without collidingwith the obstacles in all conditions.

2.4. Line-bisection task

The bisection task followed a similar procedure to the one outlinedabove. However, in this task participants were instructed to point withtheir index finger, as accurately as possible, at the perceived midpointbetween the two obstacles. As participants were required to be as

ce tasks. Participants had to move their right-hand from one of three start positions (left,arget area (avoidance task). This image shows a hand located at the centre start positionetermined by calculating the virtual midpoint (VM) between the three infrared markersfor illustrative purposes only and not an accurate depiction. (c) In the line-bisection task

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accurate as possible in this task, we did not instruct them to movequickly (as we did in the obstacle avoidance task).

2.5. Data analysis

No offline-filteringwas applied to themovement data. To determinethe hand position throughout the obstacle avoidance taskwe calculatedthe virtual midpoint (VM) between the three infrared markers in 3D(for a similar procedure see Hesse, Lane, Aimola, & Schenk, 2012). Forthe bisection task, only one marker was used (see Fig. 1c). The 3D posi-tion data of the VM (or the indexmarker in the bisection task) was thenused to compute the resultant movement velocity. Movement onsetwas defined when either the VM (in the obstacle avoidance task) orthe indexmarker (in the bisection task) had exceeded a velocity thresh-old of 0.025 m/s. The end of movement was defined using a combinedvelocity and position criterion, specifically the point at which themarkers reached their lowest velocity within 5 mm from the furthesty-position (distance in depth) recorded. Peak velocity was defined asthe maximum velocity of the VM (in the obstacle avoidance task) orthe index marker (in the bisection task) between movement onsetand the end of the movement. Time to peak velocity was calculated asrelative time (percentage of the totalmovement time). Across all partic-ipants in both the line-bisectioning and obstacle avoidance tasks anytrials with missing data and with RTs less than 100 ms (indicatingmovement initiation before the auditory go-signal) were excludedfrom analysis (a total of 10 trials).

Trajectories were normalised by dividing the data into 100 equaltime intervals (using linear interpolation) between movement onsetand end of movement. In the obstacle avoidance task the position ofthe hand (VM) at the moment the obstacles were passed was deter-mined for each trial and used as a comparison with the bisection re-sponse (end of movement) in the line-bisection task. The moment theobstacles were passed was defined as the first frame in which the VMpassed between the obstacles in y-direction.

Our preliminary analysis revealed no difference in results dependingon whether the point at which the obstacles were passed or the end ofmovement was used to calculate the lateral hand position in the ob-stacle avoidance task. The point at which the obstacles were passedwas chosen to make a direct comparison with the end of movementin the line-bisection task in order to remain consistent with previousstudies (McIntosh, McClements, Dijkerman, et al., 2004; McIntosh,McClements, Schindler, et al., 2004; Rice et al., 2006; Schindler et al.,2004). In the following sections, we will refer to this variable as the‘lateral hand position’ in both tasks.

Data was analysed using a 2 (task: obstacle avoidance vs.bisectioning) × 3 (start position: left, central, right) × 3 (obstacle po-sition: left in, both out, right in) repeated-measures ANOVA. AGreenhouse–Geisser correction was applied if the sphericity as-sumption was violated (Geisser & Greenhouse, 1958). Unadjusteddegrees of freedom and epsilon (ε) values are provided if Greenhouse–Geisser correction was applied. All other values are presented as means(or medians) ± SEM (between subjects). A significance level ofα = 0.05 was used for all analyses and all post-hoc tests wereBonferroni corrected.

3. Results

3.1. Lateral hand position

If participants use similar bisection strategies to complete both theavoidance and line-bisection tasks, we would anticipate no significantdifference in hand trajectories when comparing the two tasks. Further-more, each of the three start positions should have a similar effect on thelateral hand position in both tasks. Additionally, we predict a significanteffect of obstacle position on the lateral hand position in both tasks.Fig. 2a–b shows the normalised trajectories averaged across all

participants separately for all start positions, obstacle arrangementsand both tasks. Fig. 2c–d shows the average lateral distance (x-direc-tion) of the hand from the horizontal midpoint of the obstacle boardat themoment the obstacles were passed (obstacle avoidance) or themidpoint was indicated (line-bisectioning). Participants shifted theirtrajectory in response to the obstacles' location in both tasks. Addition-ally, the start position of the hand seems to strongly affect the trajecto-ries in the obstacle avoidance task with the hand position being biasedin lateral direction toward the start position. In contrast, there seems tobe very little influence of the hand's start position on the final lateralhand position in the line-bisection task.

In order to test these observations statistically, we analysed how ourexperimental variations affected the lateral position of the hand at theend of movement in the line-bisection task and at the moment theobstacle was passed in the obstacle avoidance task (see Fig. 2c–d). A 2(task: obstacle avoidance vs. bisectioning) × 3 (start position: left, cen-tral, right) × 3 (obstacle position: left in, both out, right in) repeated-measures ANOVA yielded significant main effects of task (F1,23 = 5.90,p = .024), start position (F2,46 = 30.57, ε = .55, p b .001) as well asobstacle position (F2,46 = 457.00, ε = .56, p b .001).

As all interaction effects were highly significant (and disordinal)these main effects cannot be meaningfully interpreted. Specifically,the analysis revealed highly significant interactions between task andstart position of the hand (F2,46 = 39.59, ε = .55, p b .001); betweentask and obstacle position (F2,46 = 54.91, ε = .58, p b .001); andbetween start position and obstacle position (F4,92 = 8.26, ε = .76,p b .001). The interactions indicate that the start position affectedthe lateral hand position differently in the line-bisectioning and theobstacle avoidance tasks, that the obstacles' position affected the lateralhand position differently in both tasks, and that the obstacle positions in-fluenced the lateral hand position depending on the start position of thehand. Finally, a significant three-way interactionwas found (F4,92= 6.45,ε= .70, p= .001) suggesting that the combinations of start position andobstacle position affected the hand's lateral position differently in line-bisectioning and obstacle avoidance.

In order to understand the three-way interaction effect, we conduct-ed a 3 (start position: left, central, right) × 3 (obstacle position: left in,both out, right in) repeated-measures ANOVA on each task separately(results were corrected for multiple comparisons using Bonferroni cor-rection). The analyses aim at investigating how the start position of thehand and the obstacles' position affected the lateral hand position inthe two tasks respectively. The results are presented in the followingparagraphs.

The results of the 3 (start position: left, central, right) × 3 (obstacleposition: left in, both out, right in) repeated-measures ANOVA on theobstacle avoidance data revealed a highly significant main effect ofstart position on the lateral hand position at the moment the obsta-cles were passed (F2,46 = 35.83, ε = .55, p b .001). The mean dis-tance from the midline for the left start position of the hand was−27.4 mm ± 3.3 mm to the left, for the central start position itwas −3.5 mm ± 2.1 mm to the left and for the right start positionof the hand it was +17.9 mm ± 4.6 mm to the right. Post-hoc testsindicated that all differences were significant (all p b .001). Thus,regardless of the obstacles' position participants stayed further tothe left of the midpoint when the start position of the hand was atthe left side, remained near to the midpoint when the movementwas started from the central start position, and remained further tothe right of the midpoint when the start position of the hand wasat the right side.

Furthermore, there was also a significant main effect of obstacles'position on trajectory (F2,46 = 125.55, ε = .55, p b .001). Note, thatthe midpoint between the obstacles is located at 0 mm when both ob-stacles are presented in the outermost position; if one of the obstaclesis shifted inward the midpoint is located at ±20 mm from the midline(positive values when the left obstacle is moved and negative valueswhen the right obstacle is moved). The mean lateral position of the

Fig. 2. Subplots a–b: Mean time-normalised trajectories for all twenty-four participants for the obstacle avoidance task (a) and line-bisection task (b). The light grey lines represent a rightobstacle shift, the black lines a left obstacle shift and thedark grey lines the trajectorieswhen both obstacleswere positioned at the outermost position. The trajectory starts negatively in y-direction for the obstacle avoidance task due to how the VMwas calculated (for details see methods section). Subplots c–d: Mean deviation in hand trajectory from the midline. In theobstacle avoidance task the lateral hand position was determined at the moment the obstacles were passed (c); and in the line-bisection task the lateral hand position was determinedat the end of the movement (d). A shift to the left of the midline results in a negative value and a shift to the right a positive value. Error bars depict ±1 SEM (between subjects).

78 A.I. Ross et al. / Acta Psychologica 151 (2014) 74–82

hand, when both obstacles were presented at the outermost position,was−3.7 mm± 1.6 mm to the left. When the left obstacle was shiftedinwards the average lateral position of the hand was +6.5 mm ±1.4 mm to the right and when the right obstacle was shifted inwardsthe average position of the hand was −15.8 mm ± 2.2 mm to the leftof themidline. Post-hoc test indicated that all differences between con-ditions are highly significant (all p b .001). This shows that even thoughparticipants shifted their hand laterally in response to the obstacle posi-tion in the expected direction, these shifts were not “perfect” (i.e. notgoing through the midpoint between obstacles). Furthermore, theANOVA also revealed a significant interaction effect between start posi-tion and obstacle position (F4,92 = 8.52, ε = .70, p b .001) indicatingthat the deviation in trajectory for each obstacle arrangement dependedon the start position of the hand (this interaction effect will be exploredin more detail in Section 3.2).

Regarding the line-bisection data, the 3 (start position: left, central,right) × 3 (obstacle position: left in, both out, right in) repeated-measures ANOVA revealed a significant main effect of start position onthe indicated midpoint (F2,46 = 8.45, ε = .71, p = .006). The meanlateral positions of the index finger indicate that the average distancefrom the midpoint for the left start position was +1.2 mm ± 1.1 mmto the right, for the central start position the mean deviation was−1.3mm±0.8mm to the left, and for the right start position the aver-age deviation was −2.1 mm ± 0.9 mm to the left. These values showthat participants selected an end point that was to the right of the realmidpoint when their hand started from the left position and an endpoint to the left of the real midpoint when starting from the right posi-tion. Post-hoc tests indicated that the end point was significantly

different when participants started their movements from the leftstart position as compared to the central or right start positions (bothp b .03). There was no significant difference between the end pointswhen participants started their movement either centrally or from theright start position (p = .60).

Furthermore, as expected, the ANOVA confirmed a highly signif-icant main effect of obstacle position on the indicated midpoint(F2,46 = 618.99, ε = .60, p b .001). For each of the three start posi-tions participants remained highly sensitive to the obstacles' posi-tion. If the left obstacle was shifted inward, the final lateral handposition was +18.3 mm ± 1.0 mm to the right, if both obstacleswere at the outermost position, the final lateral hand position was−0.4 mm ± 0.9 mm to the left, and if the right obstacle was shiftedinward, the final lateral hand position was−20.0 mm± 1.1 mm to theleft. Post-hoc tests indicated that all differences were highly significant(all p b .001). The interaction effect between start position and obstacleposition was not significant (F4,92 = 2.63, p = .092).

3.2. Sensitivity to obstacle shift

Previous studies comparing line-bisectioning and the obstacleavoidance have computed the sensitivity to obstacle shifts occurring atthe left or right side respectively (McIntosh, McClements, Dijkerman,et al., 2004; McIntosh, McClements, Schindler, et al., 2004; Rice et al.,2006; Schindler et al., 2004). These weightings measure the averagelateral shift in hand position in response to obstacle shifts from theleft or the right side. In other words, they represent how much thehand position shifted laterally when the obstacle was moved inwards

79A.I. Ross et al. / Acta Psychologica 151 (2014) 74–82

by 40mm from either side. In accordance with the previous studies wecalculated the sensitivity to obstacle shifts using the following equationsseparately for each start position of the hand:

Sensitivity to left obstacle shift¼ mean left obstacle in ‐ both obstacles outð Þ

Sensitivity to right obstacle shift¼ mean right obstacle in ‐ both obstacles outð Þ

Fig. 3a–b shows the mean lateral shift in hand position as a functionof start position and side of obstacle shift. A 2 (task: obstacle avoidancevs. bisectioning) × 3 (start position: left, central, right) × 2 (side ofobstacle shift: left, right) repeated measures ANOVA revealed a highlysignificant main effect of task (F1,23 = 59.17, p b .001). Post-hoc testsindicated that the sensitivity to obstacle shifts was significantly largerin the bisection task (19.2 mm± 0.7 mm) than in the obstacle avoid-ance task (11.2 mm ± 1.0 mm) (p b .001). There was also a signifi-cant main effect of the side of obstacle shift (F1,23 = 6.23, p = .02).Post-hoc tests indicated that the lateral hand position was more sen-sitive to obstacle shifts occurring at the right side of the workspace(15.9 mm ± 0.7 mm) than to obstacle shifts occurring at the leftside (14.4 mm ± 0.7 mm). This finding may be due to the fact thatall participants performed their movements with the right hand.There was no main effect of start position on the obstacle sensitivity(p = .81). Furthermore, a highly significant interaction effect wasfound between start position and obstacle position (F2,46 = 22.07,p b .001). This interaction effect cannot be meaningfully interpreted asthere was also a highly significant three-way interaction (F2,46 = 16.36,p b .001). The three-way interaction indicates that participants haddiffering sensitivities to shifts of the left or right obstacle depending onthe start position of the hand in the two tasks.

In order to understand how start position and side of obstacle shiftaffected the sensitivity to obstacle shifts in both task, we applied a 3(start position: left, central, right) × 2 (side of obstacle shift: left,right) repeated-measures ANOVA for each task separately. For the ob-stacle avoidance task, this analysis yielded a significant main effect ofside of obstacle shift (F1,23 = 7.29, p = .026). Post-hoc tests indicatedthat the lateral hand position was generally more sensitive to obstacleshifts occurring at the right side (12.2mm±1.0mm) than those occur-ring at the left side (10.2mm±1.1mm). There was no significantmaineffect of start position (p= .74). Interestingly, the ANOVA also revealeda highly significant interaction effect (F2,46= 24.08, p b .001). This find-ing indicates that the sensitivity to obstacle shifts from either sidestrongly depended on the start position of the hand. More specifically,obstacle shifts occurring closer to the hand's start position resulted in

Fig. 3. Sensitivity to obstacle shifts as a result of a 40 mm shift of the left or right obstacles pbars depict ±1 SEM (between subjects).

a stronger lateral deviation of the hand away from the obstacle at themoment the obstacles were passed (see Fig. 3a). Paired-samples t-tests (Bonferroni corrected for multiple comparisons) confirmed thatthe hand was more sensitive to obstacle shifts occurring at theleft side when the start position was toward the left (t23 = 3.93, p =.003) and more sensitive to obstacle shifts occurring at the right sidewhen the hand's start position was toward the right (t23 = 5.53,p b .001). When the handwas placed centrally there was no differencein sensitivity to obstacle shifts occurring at either side (p = .42).

The same analysis on obstacle weightings was conducted forthe line-bisectioning data. The 3 (start position: left, central, right) × 2(obstacle weighting: left, right) repeated-measures ANOVA revealedno significant main effect of start position (p = .13). That is, indepen-dent of the start position, participants shifted their hands similarly in re-sponse to obstacle shifts (see Fig. 3b). There was also no main effect ofside of obstacle shift (p= .58), indicating that participantswere equallysensitive to obstacle shifts occurring from the left and the right side. Nosignificant interaction effect was found (p = .24).

3.3. Reaction and movement times

Table 1 shows themedian reaction times (RT) andmedianmovementtimes (MT) averaged across all participants in the line-bisection and ob-stacle avoidance tasks. A 2 (task: obstacle avoidance vs. bisectioning) ×3 (start position: left, central, right) × 3 (obstacle position: left in, bothout, right in) repeated-measures ANOVA revealed no significant maineffect of task, start position or obstacle position on RT (all p N .07). Fur-thermore, no significant interaction effects were found (all p N .47).This shows that in both the line-bisection and obstacle avoidance tasks,regardless of start position and obstacles' position, participants neededa similar amount of time to initiate their movements.

Regarding MTs, the 2 (task: obstacle avoidance vs. bisectioning) × 3(start position: left, central, right) × 3 (obstacle position: left in, bothout, right in) repeated-measures ANOVA revealed a significant main ef-fect of task (F1,23 = 15.21, p = .001). Post hoc tests indicated that MTswere about 110 ms± 28ms longer in the obstacle avoidance task thanin the line-bisection task (p b .001). As participants had to reach furtherin the obstacle avoidance task than in the line-bisection task this resultis not surprising. No main effects of start position or obstacle positionwere found (both p N .38) and there were no significant interaction ef-fects (all p N .45).

3.4. Peak velocity and percentage of time to peak velocity

Table 2 shows the data for peak velocity (PV) and relative time topeak velocity (TPV; as percentage of MT) averaged across all participants

lotted separately for the obstacle avoidance task (a) and line-bisection task (b). Error

Table 1The mean (SEM) of the median reactions and movement times across all 24 participants in the line-bisectioning and obstacle avoidance tasks.

Start position Obstacle position RT (ms) MT (ms)

Line-bisectioning Obstacle avoidance Line-bisectioning Obstacle avoidance

Left Left in 341 (20) 319 (18) 852 (41) 969 (48)Both out 334 (18) 321 (19) 856 (43) 975 (49)Right in 330 (19) 312 (19) 844 (39) 964 (48)

Centre Left in 349 (18) 320 (17) 858 (44) 973 (50)Both out 340 (25) 319 (19) 865 (42) 972 (48)Right in 331 (18) 318 (19) 868 (43) 972 (48)

Right Left in 349 (27) 322 (15) 866 (40) 979 (44)Both out 349 (25) 317 (17) 868 (45) 976 (44)Right in 343 (19) 323 (19) 886 (51) 974 (48)

80 A.I. Ross et al. / Acta Psychologica 151 (2014) 74–82

for the different experimental conditions. A 2 (task: obstacle avoidancevs. bisectioning) × 3 (start position: left, central, right) × 3 (obstacle po-sition: left in, both out, right in) repeated-measuresANOVAof the PVdatarevealed a highly significant main effect of task (F1,23 = 45.16, p b .001).Post-hoc tests indicated that participants movedwith a higher peak ve-locity in the obstacle avoidance task (1.05 m/s ± 0.05 m/s) than in theline-bisection task (0.86m/s± 0.04 m/s), (p b .001). This finding is un-surprising as participants were instructed to move quickly in theobstacle-avoidance task but not in the line-bisection task inwhich accu-racy was stressed. There were no main effect of start position and nomain effect of obstacle position on PV (both p N .06). The only interac-tion effect that reached significance was between start position andobstacle position (F4,92 = 4.58, p = .002). It can be seen in Table 1that this interaction effect is caused by the fact that participants performslightly faster movements when the obstacle was positioned closer tothe start position of the hand than when the obstacle was positionedfurther away from the hand's start position. Therefore, the fact thatmovement times were similar in all conditions may be attributed tothe fact that participants moved at a higher velocity when producingmore curved trajectories.

Regarding TPV, the 2 (task: obstacle avoidance vs. bisectioning) × 3(start position: left, central, right) × 3 (obstacle position: left in, bothout, right in) repeated-measures ANOVA revealed a significantmain effect of task (F1,23 = 6.58, p = .017). Post-hoc tests indicatedthat participants reached PV significantly later in the obstacle avoid-ance task than in the line-bisectioning task (p = .017). Again, thisfinding can likely be attributed to the fact that participants tried tomove as accurately as possible in the line-bisection task. There wasno main effect of start position and no main effect of obstacle posi-tion (both p N .08). The only interaction effect that reached signifi-cance was between task and start position (F2,46 = 4.44, p = .017).Post-hoc tests indicated that there was no effect of start position onTPV in the obstacle avoidance task (p= .58), but therewas a significanteffect of start position on TPV in the bisectioning task (F2,46 = 6.00,p= .01). In this condition participants reached PV significantly laterwhen they started their movement from the right start position ascompared to the left start position (p = .038). All other comparisonswere not significant (both p N .32).

Table 2The mean (SEM) peak velocities and relative times to peak velocity across all 24 participants in

Start position Obstacle position Peak velocity (m/s)

Line-bisectioning

Left Left in 0.89 (0.04)Both out 0.88 (0.04)Right in 0.85 (0.04)

Centre Left in 0.85 (0.05)Both out 0.86 (0.04)Right in 0.84 (0.04)

Right Left in 0.85 (0.05)Both out 0.88 (0.05)Right in 0.87 (0.05)

4. Discussion

The purpose of this study was to investigate whether the previouslyreported tendency of humans to move approximately through themiddle of a gap formed between two obstacles can be partly attributedto the spatial layout of these paradigms (McIntosh, McClements,Dijkerman, et al., 2004; McIntosh, McClements, Schindler, et al., 2004;Rice et al., 2006; Schindler et al., 2004). To this end, we tested partici-pants using an obstacle avoidance task in which we manipulated theposition of two obstacles aswell as the start position of the hand relativeto the obstacles. The performance in the obstacle avoidance task wascomparedwith the performance in a line-bisection task inwhich partic-ipantswere explicitly instructed to accurately point to themiddle of thegap between the obstacles.

Similar to previous studies (e.g., McIntosh, McClements, Dijkerman,et al., 2004; Schindler et al., 2004), we observed a smaller sensitivity toobstacle shifts in the obstacle avoidance task than in the line-bisectiontask. Following a 40 mm obstacle shift in the line-bisection task partic-ipants adjusted their hand position on average by about 20 mm whenindicating the midpoint (thus accurately identifying the centre of thegap). In contrast, in the obstacle avoidance task, the position of thehand (when passing the obstacles) was on average altered by about11 mmwhen the obstacle was moved inward by 40 mm. Interestingly,the sensitivity to obstacle shifts strongly depended on the hand's startposition during obstacle avoidance. Obstacle shifts that occurred closerto the hand's start position resulted in larger deviations of thetrajectory away from that obstacle indicating a collision-avoidancestrategy. Furthermore, independent of the obstacle shifts taking place,the trajectories remained strongly biased in the direction of the start po-sition during obstacle avoidance. The latter finding is well in agreementwith the suggestion that biomechanical costs are taken into accountwhen planning trajectories in the obstacle-avoidance tasks (see also,Cohen, Biddle, & Rosenbaum, 2010). Interestingly, movement endpoints in the line-bisection task were not biased towards the hand'sstarting position. Instead, participants seemed to slightly over-shoottheirmovements resulting in endpoints to the right of the realmidpointwhen moving from a left start position and end points to the left of thereal midpoint when moving from a right start position. Furthermore,

the line-bisectioning and obstacle avoidance tasks.

Percentage of time to peak velocity (%)

Obstacle avoidance Line-bisectioning Obstacle avoidance

1.03 (0.05) 36.77 (1.36) 42.32 (1.18)1.03 (0.05) 36.75 (1.19) 41.53 (1.20)1.02 (0.05) 38.74 (1.42) 42.31 (1.14)1.07 (0.06) 38.39 (1.49) 41.22 (0.98)1.06 (0.05) 39.07 (1.79) 41.42 (1.00)1.06 (0.06) 38.71 (1.37) 41.75 (0.93)1.04 (0.06) 39.96 (1.36) 42.41 (1.10)1.06 (0.05) 39.09 (1.60) 41.30 (0.99)1.05 (0.05) 39.96 (1.55) 42.04 (1.22)

81A.I. Ross et al. / Acta Psychologica 151 (2014) 74–82

during line-bisectioning participants' sensitivity to obstacle shifts didnot vary with the start position of the hand.

As outlined in the introduction, line-bisectioning and obstacleavoidance have frequently been used in combination with the aimof revealing perception–action dissociations in certain neurologicaldisorders (McIntosh, McClements, Dijkerman, et al., 2004; McIntosh,McClements, Schindler, et al., 2004; Rice et al., 2006; Schindler et al.,2004). However, identifying dissociations in performance levels restson the assumption that both tasks measure participants' response tothe same visual attributes and that participants apply similar strategiesto accomplish both tasks. Yet, participants are usually given differentobjectives in both tasks, which are likely to be reflected in the strategiesthey select. While accuracy is crucial during line-bisectioning, there isno need to select a safe movement path in this task as the movementis finished at the moment the obstacles are reached. In contrast, oneof the main intentions during obstacle avoidance is to minimise therisk of potential collisions when passing through the obstacles andmoving the hand to the target zone. Previous studies on obstacle avoid-ance (which have primarily investigated the effect of the presence ofobstacles on graspingmovements) have consistently shown that partic-ipants increase the safetymargin between the reachinghand and anob-stacle that is placed in the workspace by maintaining a safe distancebetween hand and obstacle (Chapman & Goodale, 2008; Menger, Vander Stigchel, & Dijkerman, 2012; Mon-Williams, Tresilian, Coppard, &Carson, 2001; Tresilian, 1998). The results of our study further supportthis view. Specifically, the observation that the distance of the hand'sstart position from the obstacles critically determines the extent bywhich the trajectory is modified in the obstacle avoidance task providesevidence for the notion that collision avoidance is a central parameterin movement planning. Moreover, accuracy can be neglected whenselecting the movement end point, as no specific target position is de-fined in the obstacle avoidance task. The fact that the lateral hand posi-tion in the obstacle avoidance task strongly depends on the startposition of the hand demonstrates that the goal-position is selected rel-ative to the hand's start position. The selection of a trajectory in the ob-stacle avoidance task that is both safe (successfully avoiding theobstacles) and efficient (remaining relatively close to the hands initialstart position) is well in line with the model on movement planningsuggested by Rosenbaum et al. (Rosenbaum et al., 1995; Rosenbaumet al., 2004; Vaughan et al., 2001). According to this model, movementsare planned by calculating the most direct movement path (reducingthe energetic demands) that converts the start posture into the goalposture while successfully avoiding collisions with obstacles if present(Vaughan et al., 2001).

Furthermore, if collision avoidance was one of the main objectivesduring obstacle avoidance this would imply that the task requires infor-mation processing in egocentric spatial coordinates ensuring the selec-tion of a trajectory that accounts for the positions of the obstaclesrelative to the hand. In contrast, line-bisectioning requires the estima-tion of the distance between the obstacles (scene-based decision) inorder to make an accurate spatial judgment. Therefore, in addition tothe egocentric task of moving the finger to the perceived midpoint,the line-bisection task also contains an allocentric processing compo-nent. Previous studies have indicated that the task pairings used to elicitperception–action dissociations are often confounded with regard tohow spatial information is processed (Hesse, Franz, & Schenk, 2011;Schenk, 2006; Smeets, Brenner, de Grave, & Cuijpers, 2002). Whilemost perceptual tasks require spatial information processing in anobject-centred frame of reference (allocentric), most visuomotor tasksrequire spatial information processing in a hand-centred referenceframe (egocentric) (Schenk, 2006). Thus, differences in performancebetween line-bisectioning and obstacle avoidance may not necessarilydepend on whether a task is perceptual or motor but on the referenceframes needed to successfully complete the task. Interestingly, anumber of studies have highlighted that visual form agnosic patientDF, who shows normal obstacle avoidance behaviour but impaired

line-bisectioning performance, has serious difficulties performing tasksthat require allocentric information processing (Carey, Dijkerman, &Milner, 2009; Dijkerman, Milner, & Carey, 1998; Schenk, 2006). Hence,DF's impaired line-bisection performance may be a direct result of thefact that she is unable to make spatial judgments based on allocentricvisual information.

It has repeatedly been pointed out that matching task demands inperceptual and visuomotor tasks is not trivial and that many of the re-ported dissociations between action and perception can either be attrib-uted to inappropriately matched procedures and task requirements(e.g. Franz & Gegenfurtner, 2008; Franz, Gegenfurtner, Bülthoff, &Fahle, 2000; Franz, Hesse, & Kollath, 2009; Pavani, Boscagli, Benvenuti,Rabuffetti, & Farnè, 1999; Smeets & Brenner, 1995, 2006; Smeets et al.,2002; Vishton, Pea, Cutting, & Nunez, 1999) or to differences in thestrategies participants employ to perform perceptual and visuomotortasks respectively (e.g. Hesse et al., 2011; Schenk, 2010). Our findingssuggest that combining line-bisection and obstacle avoidance taskswith the aim to test for the existence of divergent processing pathwaysfor perception and action is also methodologically problematic. Thisconclusion has important implications as until now the combinationof both tasks has been generally accepted to constitute a sound par-adigm that is well suited to reveal perception–action dissociations(Milner & Goodale, 2008; Schenk & McIntosh, 2010). Instead our ob-servations further substantiate the suggestion that most of the psy-chophysical evidence, previously put forward in support of theperception–action model, can be more parsimoniously explainedwithout assuming the existence of two functionally different processingpathways (for review see, Schenk, Franz, & Bruno, 2011; Schenk &McIntosh, 2010).

5. Conclusion

In the present study we have found evidence to suggest that partic-ipants use differentmovement strategies in line-bisectioning and obsta-cle avoidance tasks. These different strategies correspond to distinctcomputational requirements. Line-bisectioning requires participants tolocate the point that is equidistant to both flanking objects. However,in obstacle avoidance, finding the equidistant point is neither re-quired nor typically achieved. Instead, participants will select areaching trajectory that incurs minimal movement costs while stillkeeping the hand at a safe distance to the obstacles. This latter strat-egy requires that participants take the relative distance betweentheir hand position and the obstacle position into account, but nei-ther the distance between the two obstacles nor the midpoint ofthat distance needs to be computed to guide the hand safely throughthe gap between the obstacles. This means that line-bisectioning andobstacle avoidance are two tasks that use different visual computa-tions and different visual parameters. Hence, it could be arguedthat both tasks are in fact action tasks that require different visualcomputations. Following this logic, we conclude that the neuropsycho-logical dissociations between bisectioning and obstacle avoidancemight be more parsimoniously described as a dissociation betweendifferent visuospatial mechanisms and task constraints and not a disso-ciation between perception and action.

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