Exp Brain Res (2009) 192:275–286 DOI 10.1007/s00221-008-1612-5

R ES EA R C H N O T E

Anti-pointing is mediated by a perceptual bias of target location in left and right visual space Matthew Heath · Anika Maraj · Ashlee Gradkowski · Gordon Binsted

Received: 8 July 2008 / Accepted: 6 October 2008 / Published online: 31 October 2008 © Springer-Verlag 2008

Abstract We sought to determine whether mirror-symmetrical limb movements (so-called anti-pointing) elicit a pattern of endpoint bias commensurate with perceptual judgments. In particular, we examined whether asymmetries related to the perceptual over- and under-estimation of target extent in respective left and right visual space impacts the trajectories of anti-pointing. In Experiment 1, participants completed direct (i.e. pro-pointing) and mirror-symmetrical (i.e. anti-pointing) responses to targets in left and right visual space with their right hand. In line with the anti-saccade literature, anti-pointing yielded longer reaction times than pro-pointing: a result suggesting increased top-down processing for the sensorimotor transformations underlying a mirror-symmetrical response. Most interestingly, pro-pointing yielded comparable endpoint accuracy in left and right visual space; however, anti-pointing produced an under- and overshooting bias in respective left and right visual space. In Experiment 2, we replicated the Wndings from Experiment 1 and further demonstrate that the endpoint bias of anti-pointing is independent of the reaching limb (i.e. left vs. right hand) and between-task diVerences in saccadic drive. We thus propose that the visual Weld-speciWc endpoint bias observed here is related to the cognitive (i.e. top-down)

M. Heath (&) · A. Maraj · A. Gradkowski School of Kinesiology, The University of Western Ontario, London, ON N6A 3K7, Canada e-mail: [email protected] G. Binsted Faculty of Health and Social Development, University of British Columbia, Kelowna, BC, Canada

nature of anti-pointing and the corollary use of visuoperceptual networks to support the sensorimotor transformations underlying such actions. Keywords Anti-pointing · Asymmetries · Memory · Perceptual · Visuomotor

Introduction The visuomotor system exhibits an innate tendency to respond in the direction of stimulation (Simon and Wolf 1963; for review see Lu and Proctor 1994). However, automatic mapping between stimulus and response can be suppressed via top-down executive control allowing motor resources to be allocated in a direction opposite the stimulus (so-called contraversive behaviour). Perhaps the most extensively studied contraversive behaviour is the antisaccade task (e.g. Hallett 1978; for review see Munoz and Everling 2004). Unlike the pro-saccade task wherein the performer “looks” in the direction of an exogenously or endogenously presented visual stimulus, the anti-saccade task requires the generation of a mirror-symmetrical response (i.e. “look away”). The behavioural consequences of anti-saccading include the commission of direction errors, and anti-saccades—when performed in the correct direction—exhibit longer response latencies than prosaccades (e.g. Doma and Hallett 1988; Fischer and Weber 1992; Hallett 1978; Koval et al. 2004). Evidence from primate electrophysiology indicates that the error-rate and the slowed onset of anti-saccades relate to initial engagement of the (wrong) saccade networks contralateral to the stimulus. Indeed, if the anti-saccade task is performed in the correct direction then early engagement of contralateral saccade networks must be suppressed and re-mapped to

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homologous networks on the opposite side of the brain (i.e. ipsilateral to the stimulus) (Everling et al. 1999). Moreover, the latency of anti-saccades can further be attributed to the top-down control of a “non-standard visual input pathway” (Zhang and Barash 2000, p. 974) and vector inversion of the sensorimotor transformations required to drive a mirrorsymmetrical response. Thus, the anti-saccade literature provides compelling evidence that contraversive actions rely on executive function and visual inputs that are distinct from pro-saccades. As noted above, ample work has examined the anti-saccade task; however, a dearth of studies have investigated the behavioural and neurophysiological properties of antipointing; that is, the production of a mirror-symmetrical limb response. Some work using the target perturbation paradigm has examined the latency and amplitude of online trajectory modiWcations directed toward (i.e. procorrection) or mirror-symmetrical (i.e. anti-correction) to a target jump (Day and Lyon 2000; Johnson et al. 2002). In this paradigm, participants are asked to complete fast and accurate reaches to a central target and on a percentage of trials (i.e. 33%) the target is perturbed leftward or rightward following movement onset (i.e. 25 ms after movement initiation). The anti-correction task has reliably shown that early (125–160 ms after response initiation) limb adjustments are stimulus-driven and automatically proceed toward the veridical change in target location regardless of the movement goal (i.e. pro- vs. anti-correction). It is only later in the response (>160 ms) that participants produce a corrective response in line with the intention of the anti-correction task (see Day and Lyon 2000; Johnson et al. 2002). Such results provide evidence of two classes of corrective processes: fast (automatic) stimulus-driven corrections and slower intention-driven corrections. In addition, work in this area indicates that a distinct visuomotor network underpins fast corrective processes (Pisella et al. 2000), whereas a separate visuoperceptual network mediates intention-driven corrections (Rossetti et al. 2005; for duplex model of visual processing see Milner and Goodale 1995). Although the anti-correction task provides insight into the latency by which intention-drive corrections can be incorporated into an unfolding limb trajectory, it does not provide a basis for examining actions wherein a mirrorsymmetrical response is intentionally planned (i.e. in advance of movement onset) and executed. In fact, we are aware of only two studies that have directly contrasted intentionally planned pro- and anti-pointing (Chua et al. 1992; Carey et al. 1996) with each reporting prolonged reaction times in the latter. Such Wndings are of interest because they suggest that contraversive manual responses are subject to a vector inversion problem similar to antisaccades. It is, however, important note that the just

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Exp Brain Res (2009) 192:275–286

mentioned research did not focus on the systematic nature of endpoint error for anti-pointing.1 This represents a seminal issue because fMRI work by Connolly et al. (2000) has shown that anti-pointing elicits ampliWed cortical activation relative to pro-pointing (average voxels active: antipointing = 387.1, pro-pointing = 291.6) with the increased activity related to distinct frontoparietal areas and engagement of distributed visual and motor networks required for a cognitively mediated action. Thus, the top-down nature of anti-pointing may render the endpoint parameters of such actions sensitive to perceptual bias’ in left and right visual space. In Experiment 1 of this investigation, we had participants complete pro- and anti-pointing responses in the horizontal visual Weld with their right hand to ascertain whether anti-pointing is susceptible to a cognitive (i.e. perceptual) bias of target information (i.e. extent) in left and right visual space. Indeed, and as established in the perceptual literature, an over- and underestimation of veridical target properties (i.e. brightness, numerosity, size and extent) characterise obligatory judgments in respective left and right visual space (e.g. Charles et al. 2007; Nicholls et al. 1999). As such, we sought to determine whether the cognitive nature of anti-pointing would engage extensive visuomotor and visuo-perceptual networks and thereby render such responses sensitive to target-based perceptual asymmetries. In particular, we hypothesised that a perceptual overestimation of target location in left visual space would give rise to corollary anti-pointing movements (i.e. reaches in right space) that reliably overshoot veridical target extent. In contrast, the perceptual underestimation of target location in right space would lead to anti-pointing responses (i.e. reaching in left visual space) that consistently undershoot veridical target extent. As a further test of our hypothesis, we included conditions wherein target stimuli were continuously visible during movement execution, occluded at movement initiation, or occluded at, or for some period of time in advance of response cuing (i.e. so-called memory-guided reaching). Our manipulation of target vision was predicated on a number of studies from the pictorial illusions literature indicating that memoryguided responses are mediated, in part, by an obligatory representation of target location laid down by visuo-perceptual networks (e.g. Bridgeman et al. 1997; Hu and Goodale 2000; Westwood et al. 2000; for review of this issue see Glover 2004). Therefore, a secondary goal of Experiment 1

1

The absolute unsigned error measure reported by Chua et al. (1992) is not sensitive to directional bias in reaching endpoints. In the Carey et al. (1996) study, the nature of the error metric (i.e. signed versus unsigned) is not speciWed. Further, Connolly et al’s (2000) imaging study does not supply data related to the behavioural characteristics of anti-pointing.

Exp Brain Res (2009) 192:275–286

was to determine whether a response implemented on the basis of memory-based target information ampliWes the weighting by which visuo-perceptual cues inXuence the sensorimotor transformations underlying anti-pointing.

Experiment 1 As described above, participants completed pro- and antipointing movements with their right hand to continuously visible and memory-based target locations in left and right visual space. Moreover, Experiment 1 did not provide participants with explicit instructions regarding their eye movements during trial performance. Methods Participants Eleven individuals (5 male, 6 female: age range = 19– 22 years) from the University of Western Ontario community volunteered for this study. Participants were right handed as determined by a modiWed version of the University of Waterloo Handedness Questionnaire (Bryden 1977) and had corrected or corrected-to-normal vision. This research was approved by the OYce of Research Ethics, University of Western Ontario, and was conducted in accord with the ethical standards laid down in the 1964 Declaration of Helsinki. Apparatus and procedure We used a custom aiming apparatus similar to that employed by Held and Gottlieb (1958). The apparatus contained three shelves allowing projection of “virtual” targets. The top shelf supported an inverted computer monitor (30inch, 14 ms response time; 60 Hz: Dell 3007WFP: Round Rock, TX, USA) that was used to project visual stimuli onto a one-way mirror (i.e. the middle shelf). The bottom shelf was a solid surface (96 cm wide by 65 cm deep) and was the area where participants completed reaching movements (for pictorial depiction of apparatus see Neely et al. 2008a). The distance between the top shelf and the middle shelf, and the middle shelf and the bottom shelf was constant at 34 cm. Thus, visual stimuli projected onto the mirror appeared to participants as being located on the bottom shelf (i.e. the reaching surface). A constant optical geometry was maintained using a head-chin rest (ASL6000, Bedford, MA, USA). All computer events and the projection of visual stimuli were controlled via MatLab (7.6: The MathWorks, Natick, MA, USA) and the PsychToolBox (ver. 3.0: see Brainard 1997). The lights in the experimental suite were darkened throughout data collection,

277

and in combination with the one-way mirror, occluded direct vision of the reaching limb. In the place of veridical limb vision, a splint complex containing dual light emitting diodes (LEDs) was aYxed to the nail of the pointing (i.e. right index) Wnger. The LEDs were illuminated throughout a trial thereby allowing continuous limb vision. Participants were seated for the duration of the experiment and completed reaches to targets located left and right of midline (i.e. left and right visual space). In advance of each trial, a midline Wxation (i.e. 1 cm by 1 cm cross) located 30 cm from the front edge of the aiming surface was presented for 1,000 ms after which one of six target stimuli (15 mm diameter circle) was presented concurrent with the Wxation cross for a variable preview period of 1,000–2,000 ms. Target stimuli were located at the same depth, and 15, 19, 23 cm left and right, of the Wxation cross. In advance of each pointing trial, participants placed their pointing Wnger on a home position microswitch located at the same position as the Wxation cross. Depressing the home position initiated a trial sequence. As mentioned above, the sequence resulted in the projection of the Wxation cross, followed by concurrent presentation of the Wxation cross and target image for a randomised preview period. After the preview period, an auditory tone signalled participants to initiate a pointing response as “quickly and as accurately as possible”. Thus, participants completed pointing responses to a position left or right of the home position. Pro- and anti-pointing reaches were completed in four target vision conditions (see below): in the former case participants reached directly to the location of the target stimuli, whereas in the latter case reaches were completed to the mirror-symmetrical target location. The target vision conditions used here included: target-visible (T-V), target open-loop (T-OL) and target memory delays of 0 (T-D0) and 1.000 (T-D1000) ms. For T-V trials, the target remained continuously visible throughout a response. For T-OL trials, the target was blanked coincident with release of pressure from the home position. For T-D0 and T-D1000 trials the target was blanked in time with response cuing (i.e. T-D0 trials) or 1,000 ms in advance of response cuing (i.e. T-D1000). The target delays used here were selected based on previous work by our group demonstrating that memory-guided responses following a brief (i.e. 0 ms) or prolonged delay (i.e. 5,000 ms) are supported by a perceptual representation of target location (Binsted and Heath 2004; Heath 2005; Heath and Binsted 2007; Heath et al. 2004b; Westwood et al. 2003; for review of this issue see Heath et al. 2008a). Previous work has shown that randomly interleaving diVerent visual conditions on a trial-by-trial basis (Jakobson and Goodale 1991; Heath et al. 2006; Zelaznik et al. 1983) or interleaving trials with diVerent levels of perceptual load (Heath 2005; Khan et al. 2002; Neely et al. 2008a)

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Exp Brain Res (2009) 192:275–286

inXuence the nature of the visual information and the movement strategies used to formulate reach trajectories. Thus, in order to determine the independent inXuence of the movement context and visual conditions used here, proand anti-pointing trials were completed in separate blocks and factorially combined with each target vision condition to produce eight blocks. Block order was randomised and within each block the location of a target (i.e. left or right visual space) and target eccentricity (15, 19, 23 cm) was randomised. Participants completed 10 trials in each of the experimental conditions for a total of 480. In addition to containing LEDs, the splint complex aYxed to the pointing Wnger contained an infra-red emitting diode (IRED). IRED position data were sampled at 200 Hz for 1 s following the auditory initiation tone via an OPTOTRAK Certus (Northern Digital Inc., Waterloo, ON, Canada). OZine IRED position data were Wltered via a second-order dual-pass Butterworth Wlter employing a lowpass cut-oV frequency of 15 Hz. Instantaneous velocities were computed via a three-point central Wnite diVerence algorithm. Movement onset was deWned by an analogue signal driven by release of pressure from the home position microswitch and movement oVset was deWned as the Wrst

frame wherein resultant limb velocity fell below 50 mm/s for ten consecutive frames (i.e. 50 ms).

Table 1 Experiment 1 means and between-participant standard deviations for reaction time (RT: ms), movement time (MT: ms) and constant (CE: mm) and variable (VE: mm) error in the primary and sec-

ondary movement directions as a function of pro- and anti-pointing movements in left and right visual space across each target vision condition

Dependent variables and statistical analyses We examined reaction time (RT: time from auditory initiation tone to movement onset), movement time (MT: time from movement onset to movement oVset), and constant error in the primary (CEP) and secondary (CES) movement directions and their associated variable error values (VEP, VES). Notably, CEP indexes error in the horizontal plane such that overshooting and undershooting bias are reXected by positive and negative valences respectively. In turn, negative and positive CES reXect respective proximal or distal bias in the depth plane. All dependent variables were evaluated using 2 (visual space: left, right) by 2 (movement context: pro-pointing, anti-pointing) by 4 (target vision: T-V, T-OL, T-D0, T-D1000) by 3 (target eccentricity: 15, 19, 23 cm) fully repeated measures ANOVA. SigniWcant main eVects/interactions were decomposed using simple eVects and/or power polynomials (p < 0.05). Tables 1 and 2 present means and standard deviations related to target vision and target eccentricity for each dependent variable.

Target vision T-V

T-OL

T-D0

T-D1000

Left space

Right space

Left space

Right space

Left space

Right space

Left space

Right space

Pro

204 (32)

220 (36)

205 (29)

211 (31)

204 (46)

196 (43)

222 (35)

222 (40)

Anti

226 (48)

232 (47)

237 (46)

240 (55)

199 (38)

198 (44)

235 (36)

236 (38)

Pro

355 (55)

302 (45)

348 (70)

292 (62)

355 (85)

304 (64)

358 (67)

312 (64)

Anti

360 (74)

314 (64)

348 (61)

307 (47)

350 (70)

309 (50)

371 (81)

325 (66)

Pro

2.7 (4.4)

2.0 (4.4)

0.2 (7.1)

3.6 (6.0)

1.7 (6.4)

3.3 (5.3)

¡0.2 (6.5)

0.5 (6.4)

Anti

¡34.2 (19.2)

19.1 (16.2)

¡35.6 (17.1)

18.9 (16.8)

¡33.1 (18.9)

24.2 (13.2)

¡30.4 (19.6)

19.6 (15.5)

Pro

6.4 (1.2)

7.6 (2.0)

7.7 (2.9)

8.5 (2.5)

7.4 (2.1)

7.4 (1.7)

7.2 (3.0)

8.5 (2.2)

Anti

12.6 (3.0)

14.1 (3.0)

13.5 (3.0)

15.6 (2.8)

13.2 (2.8)

14.4 (3.0)

13.7 (2.3)

14.3 (4.7)

Pro

18.3 (11.1)

18.7 (8.5)

17.1 (11.6)

18.0 (7.3)

17.7 (10.3)

18.9 (7.4)

17.6 (11.9)

18.6 (7.9)

Anti

24.1 (11.3)

25.9 (8.6)

20.1 (9.7)

24.2 (7.0)

19.0 (10.3)

23.0 (7.3)

18.5 (9.9)

23.0 (7.3)

RT

MT

CEP

VEP

CES

VES Pro

5.5 (1.4)

4.8 (1.2)

5.7 (1.1)

4.6 (1.0)

6.0 (1.8)

4.9 (1.2)

6.0 (1.3)

5.2 (1.1)

Anti

6.2 (1.8)

5.4 (1.3)

6.5 (1.0)

5.4 (1.3)

6.5 (1.2)

5.4 (1.0)

6.8 (1.7)

5.1 (1.5)

Post hoc contrasts for the eVect of target vision for RT revealed: T-V = T-OL (p > 0.05); T-OL > T-D0 (p < 0.001); T-D0 < T-D2000 (p < 0.001). Post hoc contrasts for the eVect of target vision for VES indicated: T-V < T-OL (p < 0.05), T-OL = T-D0 (p > 0.05); T-D0 = T-D1000 (p > 0.05)

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Exp Brain Res (2009) 192:275–286 Table 2 Experiment 1 means and between-participant standard deviations for reaction time (RT: ms), movement time (MT: ms) and constant (CE: mm) and variable (VE: mm) error in the primary and secondary movement directions as a function of pro- and anti-pointing movements in left and right visual space across each target eccentricity

279

Target eccentricity 15 cm Left space

19 cm Right space

Left space

23 cm Right space

Left space

Right space

RT Pro

206 (31)

206 (34)

204 (29)

211 (35)

216 (37)

213 (37)

Anti

217 (37)

227 (42)

226 (42)

226 (40)

230 (38)

227 (42)

MT Pro

329 (61)

285 (50)

354 (64)

300 (53)

379 (68)

323 (56)

Anti

337 (62)

295 (48)

357 (63)

312 (50)

377 (73)

334 (54)

Pro

2.7 (5.9)

4.8 (4.8)

1.0 (6.1)

1.8 (5.5)

¡0.4 (6.7)

0.5 (8.0)

Anti

¡22.3 (20.4)

20.3 (14.8)

¡36.3 (19.6)

19.0 (15.6)

¡41.4 (18.2)

22.1 (15.4)

CEP

VEP Pro

6.6 (1.5)

7.2 (1.6)

7.7 (2.2)

7.7 (2.2)

7.2 (2.1)

9.1 (2.0)

Anti

12.4 (2.7)

12.5 (2.7)

12.8 (2.2)

15.3 (2.9)

14.6 (3.2)

15.9 (3.5)

CES Pro

17.0 (10)

17.2 (7.5)

18.0 (11.1)

19.3 (7.8)

18.1 (11.9)

19.1 (7.9)

Anti

19.5 (9.0)

22.1 (7.0)

20.4 (10.5)

24.7 (8.0)

21.5 (10.7)

25.3 (7.9)

VES Pro

5.3 (1.4)

4.4 (0.7)

6.0 (1.2)

5.0 (1.1)

6.1 (1.4)

5.2 (1.1)

Anti

6.0 (1.1)

5.0 (1.0)

6.6 (1.3)

5.4 (1.5)

6.9 (1.4)

5.5 (1.1)

Results RTs for anti-pointing (225 ms SD33) were slower than pro-pointing (209 mm SD40), F(1,10) = 11.36, p < 0.01, and RTs for T-D0 trials were faster than T-V, T-OL and T-D1000 trials (which did not diVer), F(3,30) = 10.29, p < 0.001 (see Table 1 for post hoc details). Additionally, RTs increased with target eccentricity, F(2,20) = 21.53, p < 0.001 (only linear eVect signiWcant: F(1,10) = 36.95, p < 0.001). In terms of MT, left space reaches (356 ms SD64) were slower than right space ones (308 ms SD51), F(1,10) = 44.33, p < 0.001, and movement durations increased with target eccentricity, F(2,20) = 142.52, p < 0.001 (only linear eVect signiWcant: F(1,10) = 163.07, p < 0.001) (see Table 2). CEP yielded main eVects for visual space, F(1,10) = 57.62, p < 0.001, movement context, F(1,10) = 7.35, p < 0.03, and target eccentricity, F(2,20) = 3.70, p < 0.01, as well as interactions involving visual space by movement context, F(1,10) = 59.94, p < 0.001, and movement context by target eccentricity, F(2,20) = 3.73, p < 0.05. Figure 1 shows that left space anti-pointing movements (¡33.3 mm SD17.6) undershot target location more than pro-pointing counterparts (1.1 mm SD5.7) (t(10) = 7.58, p < 0.001) whereas right space anti-pointing movements (20.5 mm SD14.5) overshot target location more than pro-pointing counterparts (2.4 mm SD5.1) (t(10) = 4.38, p < 0.001). In

addition, CEP scaled to target eccentricity during anti-pointing (F(1,10) = 3.90, p < 0.04; only linear eVect signiWcant: F(1,10) = 23.01, p < 0.001), but not pro-pointing (F(1,10) = 2.87, p = 0.07). In terms of VEP, left space reaches (10.2 mm SD1.6) were less variable than right space counterparts (11.3 mm SD2.1), F(1,10) = 6.01, p < 0.04, and anti-pointing movements (14.0 mm SD1.9) were more variable than pro-pointing movements (7.6 mm SD1.7), F(1,10) = 337.98, p < 0.001. Further, variability increased with target eccentricity, F(2,20) = 26.39, p < 0.001 (only linear eVect signiWcant: F(1,10) = 35.19, p < 0.001) and showed increased variability across the target vision condition, F(3,30) = 4.05, p < 0.02 (see Table 1 for post hoc contrasts). CES indicated that pro-pointing movements (18.1 mm SD6.9) were more accurate than anti-pointing movements (22.2 mm SD6.7), F(1,10) = 65.79, p < 0.001, and depth plane error increased with target eccentricity, F(2,20) = 9.83, p < 0.001 (only linear eVect signiWcant: F(1,10) = 9.52, p < 0.02). For VES, left space trials (6.1 mm SD1.1) were more variable than right space ones (5.1 mm SD0.8), F(1,10) = 28.17, p < 0.001, and VES increased for antipointing movements (5.9 mm SD1.0) as compared to pro-pointing counterparts (5.4 mm SD0.9), F(1,10) = 15.50, p < 0.01. Last, VES increased with target eccentricity, F(2,20) = 10.16, p < 0.01 (only linear eVect signiWcant: F(1,10) = 19.51, p < 0.01).

123

280

Exp Brain Res (2009) 192:275–286 Left Space

Right Space

100

100

Direct Pointing Anti Pointing

80 60

60

40

40

20

20

0 -100

-60

-20 -20

Direct Pointing Anti Pointing

80

0

- 20

60

100

-100

-60

-20 -20

-40

-40

-60

-60

-80

-80

-100

-100

20

60

100

Fig. 1 Experiment 1 constant error (CE: mm) in primary and secondary movement directions for left and right space pro- and anti-pointing for all trials across each visual condition and target eccentricity. When looking at this Wgure envisage that the small cross separating the left and right Wgures represents the home position for any given response. Thus, for left space reaches the left half of the Wgure represents an overshooting bias, whereas the right half of the Wgure demonstrates an

undershooting bias. For right space reaches, the left half of the Wgure demonstrates an undershooting bias and the right half of the Wgure demonstrates an overshooting bias. This Wgure clearly demonstrates that anti-pointing in left space (which is based on a veridical target viewed in right space) produced a robust undershooting bias, whereas anti-pointing in right space (which is based on a veridical target viewed in left space) produced a robust overshooting bias

Experiment 1: discussion

Experiment 2 sought to control for possible diVerences in saccadic drive (or ocular proprioception) and/or retinal target location information accompanying pro- and anti-pointing movements (e.g. Gauthier et al. 1990). To that end, Experiment 2 introduced the constraint that participants maintain their visual gaze on a central Wxation cross throughout the time course of reaching responses.

A detailed outline of Experiment 1 Wndings is handled in the General Discussion as this section is intended to focus on systematic error in the primary movement direction. Importantly, we document equivalent endpoint accuracy for pro-pointing in left and right visual space and a visual WeldspeciWc pattern of endpoint error for anti-pointing movements. In particular, anti-pointing in left and right visual space produced respective under- and overshooting of veridical target location. Based on these results, we propose that the pattern of endpoint bias for anti-pointing reXects the mediation of such actions via a perception-based representation of target location.

Experiment 2 Our initial conclusion regarding the visual Weld-speciWc pattern of endpoint bias for anti-pointing requires that at least two issues be addressed. First, we sought to determine whether the endpoint bias observed in Experiment 1 is independent of the hand performing the task. More speciWcally, we examined whether the under- and overshooting associated with respective left and right space anti-pointing is related to biomechanical constraints and/or interhemispheric costs of reaching in contra- and ipsilateral space (e.g. Carey et al. 1996; Neely et al. 2005). To accomplish that objective, Experiment 2 entailed left and right hand pro- and anti-pointing movements to the same left and right visual space targets as used in Experiment 1. Second,

123

Methods Participants Ten participants (4 male, 6 female: age range = 20– 33 years) from the University of Western Ontario community volunteered for this study. All participants were right handed (Bryden 1977) and had corrected or corrected-tonormal vision. This research was approved by the OYce of Research Ethics, University of Western Ontario, and was conducted in accord with the ethical standards laid down in the 1964 Declaration of Helsinki. Apparatus and procedures The visual stimuli and timeline of experimental events used in Experiment 2 were identical to the T-V trials used in Experiment 1. Only T-V trials were used here because Experiment 1 showed a null eVect of target vision on the endpoint bias of anti-pointing movements. Notably, Experiment 2 involved left and right hand reaches and a splint complex (see Experiment 1 for details) was aYxed to the index Wnger (i.e. the pointing Wnger) of each. Participants

Exp Brain Res (2009) 192:275–286 Table 3 Experiment 2 means and between-participant standard deviations for reaction time (RT: ms), movement time (MT: ms) and constant (CE: mm) and variable (VE: mm) error in the primary and secondary movement directions as a function of pro- and antipointing movements for left and right hand reaches in left and right visual space and as a function of pro- and antipointing movements for target eccentricity

281

Left hand

Right hand

Target eccentricity

Left space

Right space Left space

Right space 15 cm

19 cm

23 cm

249 (46)

246 (49)

240 (41)

243 (42)

241 (44)

244 (44)

248 (42)

Anti- 252 (42)

258 (49)

248 (44)

260 (39)

257 (43)

255 (41)

250 (36)

320 (40)

370 (58)

366 (57)

316 (49)

322 (41)

346 (45)

360 (46)

Anti- 319 (56)

373 (67)

360 (78)

318 (53)

328 (59)

343 (58)

355 (63)

2.4 (6.5)

¡2.2 (8.8)

1.1 (7.5)

9.8 (3.6)

1.4 (6.3)

¡3.7 (11.7)

RT ProMT ProCEP Pro-

8.7 (9.7)

Anti- ¡21.9 (29.6) 14.8 (29.5)

¡37.9 (20.2) 27.1 (24.2)

13.5 (15.1) ¡5.0 (13.3) ¡21.9 (18.6)

VEP Pro-

13.1 (2.5)

10.3 (2.1)

11.3 (2.4)

9.5 (2.6)

9.9 (1.8)

11.4 (2.3)

11.7 (2.8)

Anti- 21.2 (5.1)

20.1 (9.9)

18.5 (5.8)

21.0 (7.7)

18.2 (4.1)

20.9 (7.2)

21.4 (5.5)

¡2.0 (11.8) 23.2 (17.5)

¡4.3 (10.3) 11.0 (9.3)

9.7 (10.2)

11.2 (10.3)

0.6 (7.4)

31.9 (14.7)

4.2 (10.2)

16.4 (7.7)

18.5 (7.0)

19.3 (8.6)

6.9 (1.8)

6.8 (1.8)

7.1 (2.0)

6.1 (1.3)

6.3 (1.6)

6.8 (1.5)

6.9 (1.3)

Anti- 7.2 (2.5)

7.4 (1.5)

8.1 (2.8)

6.4 (2.2)

7.1 (2.1)

7.0 (1.7)

7.7 (1.9)

CES Pro-

25.8 (11.0)

Anti- 35.8 (9.7) VEX Pro-

were instructed to complete “fast and accurate” reaches while maintaining visual gaze on the Wxation cross. Recall from Experiment 1 that the Wxation cross was presented coincident with the start of a trial (i.e. depressing the home position microswitch) and remained visible for the duration of a trial. Eye movements were monitored online for evidence of an overt saccade using an ASL-6000 sampling at 240 Hz (Bedford, MA, USA). If saccadic or pursuit eye movements were detected (see Binsted and Elliott 1999) the trial was deemed invalid and that trial was placed back into the randomised trial sequence. For this experiment, eye movement data were examined only for the purpose of determining whether an inappropriate eye movement occurred during a trial. Left and right hand reaches were performed in separate blocks as were the performance of pro- and anti-pointing trials (i.e. left hand/pro-pointing, left hand/anti-pointing, right hand/pro-pointing, right hand/anti-pointing). In line with Experiment 1 block order was randomised and target location (i.e. left or right visual space) and target eccentricity (15, 19, 23 cm) were presented randomly within each block. Participants completed eight trials in each of the experimental conditions for a total of 192.

right space) by 2 (movement context: pro-pointing, antipointing) by 3 (target eccentricity: 15, 19, 23 cm). Table 3 presents means and standard deviations for each dependent variable.2 Results

Dependent variables and statistical analyses

RTs for anti-pointing (254 ms SD39) were slower than propointing (244 ms SD42), F(1,9) = 8.71, p < 0.02. In addition, analysis of RT produced an interaction involving visual space by movement context, F(1,9) = 8.06, p < 0.02: pro-pointing movements in left (244 ms SD42) and right (245 ms SD45) space exhibited comparable RTs (t(9) = ¡0.03, p = 0.97); however, anti-pointing movements in left space (250 ms SD39) were faster than right-space counterparts (259 ms SD41) (t(9) = ¡2.71, p < 0.03). In terms of MT, movement durations increased with target eccentricity, F(2,18) = 49.64, p < 0.001 (only linear eVect signiWcant: F(1,9) = 73.62, p < 0.001). Moreover, MT produced a hand by visual space interaction, F(1,9) = 30.52, p < 0.001. Left and right hand reaches in ipsilateral space (left hand = 319 ms SD45, right hand = 317 SD49) were faster than contralateral space ones (left hand = 371 ms SD65, right hand = 363 ms SD62) (ts(9) = ¡3.02 and ¡4.06, respectively for left and right hands, ps < 0.02).

The same dependent variables as used in Experiment 1 were used here. Dependent variables were examined via 2 (hand: left hand, right hand) by 2 (visual space: left space,

2 Less than 2% of trials for any participant were re-collected due to missing IRED data and/or failure to maintain visual gaze

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Exp Brain Res (2009) 192:275–286

yielded a hand by visual space interaction, F(1,9) = 5.59, p < 0.05: left hand movements in left (7.0 SD1.8) and right (7.1 mm SD1.3) visual space exhibited comparable endpoint variability (t(9) = ¡0.12, p = 0.90). In contrast, right hand reaches in left space (7.6 mm SD2.1) were more variable than right space (6.2 mm SD1.2) counterparts (t(9) = 2.52, p < 0.04).

55 45

Constant Error (mm)

35 25 15 5 -5 -15 -25

Experiment 2: discussion

-35

Left Space Right Space

-45 -55

LH: Pro-pointing

LH: Anti-pointing

RH: Pro-pointing

RH: Anti-pointing

Hand and Movement Context

Fig. 2 Experiment 2 constant error (CE: mm) in the primary movement direction as a function of hand, visual space and movement context. Error bars represent between-participant standard deviations

CEP produced main eVects for visual space, F(1,9) = 19.15, p < 0.01, target eccentricity, F(2,18) = 41.76, p < 0.001, and interactions involving visual space by movement context, F(1,9) = 23.29, p < 0.001, and movement context by target eccentricity, F(2,18) = 9.04, p < 0.01. Figure 2 shows that left space anti-pointing movements (¡29.9 mm SD21.7) undershot target location relative to pro-pointing counterparts (3.2 mm SD8.1) (t(9) = 4.94, p < 0.01). In turn, right space anti-pointing movements (20.9 mm SD21.9) overshot target location more than propointing ones (1.7 mm SD6.1) (t(9) = ¡2.67, p < 0.03). Moreover, it is clear from Fig. 2 that the hand performing the task did not modulate the visual Weld-speciWc nature of endpoint bias (see also Table 3).3 Decomposition of the movement context by target eccentricity interaction indicated that pro- and anti-movements scaled in relation to target eccentricity (only linear eVect signiWcant: F(1,9) = 9.68, p < 0.02). As indicated in Table 3, the nature of the aforementioned interaction appears rooted in the magnitude by which the pro- and anti-pointing movements scaled to target eccentricity. In terms of VEP, anti-pointing movements (20.2 mm SD5.3) were more variable than pro-pointing ones (11.0 mm SD1.8), F(1,9) = 20.86, p < 0.001, and VEP scaled to target eccentricity, F(2,18) = 7.62, p < 0.01 (only linear eVect signiWcant: F(1,9) = 13.02, p < 0.01). CES indicated that depth plane error for left space reaches (29 mm SD11.0) was greater than right space (¡0.3 mm SD6.8), F(1,9) = 203.26, p < 0.001, and error in this movement direction was enhanced for anti-pointing (18.1 mm SD7.7) as opposed to pro-pointing movements (10.6 mm SD9.8), F(1,9) = 26.82, p < 0.01. Last, VES 3 As a matter of convention we do not report null eVects in the Results section; however, we thought it important to document the null interaction involving hand by visual space by movement context, F(1,9) = 1.12, p > 0.05.

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In this section, we focus on how reaching with the left and right hand in combination with maintaining static visual gaze inXuenced the speed and accuracy of reaching movements. Results showed that reaches in ipsilateral space produced faster movement times than contralateral space; that is, left hand reaches in left space were faster than in right space and right hand reaches in right space were faster than in left space.4 The increased movement times of contralateral reaches represents a well-documented Wnding and has been related to biomechanical constraints associated with crossing the body midline (e.g. Carey et al. 1996; Chua et al. 1992) and the costs associated with interhemispheric integration of sensory and motor information (e.g. Fisk and Goodale 1985; Barthélémy and Boulinguez 2002). In terms of response accuracy, left and right hand reaches in ipsiand contralateral space did not diVer in terms of systematic endpoint bias although right hand reaches in ipsilateral space elicited reduced endpoint variability (secondary movement direction) relative to the other hand and visual space combinations (for a review of this issue see Elliott and Chua 1996). Most notably, the results of Experiment 2 evidence the same endpoint parameters for pro- and antipointing movements as was documented in Experiment 1. Thus, anti-pointing in left and right visual space produced respective under- and overshooting of veridical target location and this result was independent of the hand associated with the reaching response. Moreover, the fact that participants maintained their visual gaze on a central Wxation cross throughout the time course of reaching trials indicates that between-task diVerences in retinal target location and/ or saccadic drive do not account for the visual Weld-speciWc endpoint bias of anti-pointing.

General discussion The goals of this investigation were to determine the behavioural properties of intentionally planned and executed antipointing responses and to ascertain whether such actions 4

We did not observe a reaction time advantage for the right hand: a result in line with Carey et al. (1996) but not Chua et al. (1992) (for review of asymmetries in reaction time see Carson 1996).

Exp Brain Res (2009) 192:275–286

are sensitive to perceptual asymmetries in the horizontal visual Weld. To that end, Experiments 1 and 2 demonstrate that anti-pointing movements produced longer reaction times than pro-pointing counterparts. Such a latency Wnding is entirely compatible with the anti-saccade (and antipointing) literature and the accompanying assertion that the computational load associated with vector inversion increases the movement planning time required for sensorimotor transformations (for anti-saccades see Doma and Hallett 1988; Fischer and Weber 1992; for anti-pointing see Carey et al. 1996; Chua et al. 1992). In terms of response execution, pro-pointing and anti-pointing demonstrated equivalent movement times; however, the latter condition was associated with greater endpoint variability (see discussion of endpoint accuracy in the following paragraph). Although it is diYcult to contrast the movement time and endpoint variability data reported here with the antisaccade literature (i.e. because anti-saccade work has not focused on similar metrics; see Evdokimidis et al. 2006) it is possible to draw a corollary to work examining coordinate transformations for reaching. Indeed, reaches (or grasps) performed in environments involving reduced target-related visual cues (e.g. Coull et al. 2000; Heath et al. 2008b) and/or environments wherein the matching of visual and proprioceptive information cannot be predicted in advance of movement onset (e.g. Elliott and Allard 1985; Heath 2005; Neely et al. 2008b; Zelaznik et al. 1983) frequently demonstrate movement times (and endpoint accuracy) parallel to conditions involving direct target vision and predictable visual and proprioceptive information. Interestingly, however, such actions reliably exhibit a wider distribution of movement endpoints. These results suggest that the coordinate transformations of a visual target are adequately remapped to body-centred coordinates (e.g. Henriques et al. 1998) but are susceptible to increased levels of sensorimotor noise (e.g. Schlicht and Schrater 2007; see also Sober and Sabes 2005). Hence, our results show that the trajectories of anti-pointing responses unfold along the same temporal domain as pro-pointing counterparts but at the cost of vector inversion and consequent sensorimotor transformations yielding increased endpoint variability. We next turn to the principal issue of the impact of visual space on anti-pointing. The constant error values in the primary movement direction (see Fig. 1, 2) demonstrate that left space anti-pointing responses robustly undershot target location whereas counterpart right space responses robustly overshot target location. Figures 1 and 2 also show that left and right space pro-pointing were considerably more accurate than anti-pointing ones with each demonstrating a comparable (and slight) overshooting bias (average pro-pointing error across Experiment 1 and 2 = 2.0 mm). We believe the equivalent nature of endpoint bias for left and right space pro-pointing represents an

283

important Wnding because such a result suggests that the visual Weld-speciWc endpoint bias of the anti-pointing condition cannot be directly attributed to mechanical variations in reaching direction (see also Heath and Binsted 2007). What is more, the results from Experiment 2 indicate that the endpoint bias of anti-pointing is independent of the hand used to perform the task (see Fig. 2). As such, our results cannot be explained in terms of diVerences in inertial limb properties (e.g. Gordon et al. 1994) and/or the interhemispheric costs (e.g. Barthélémy and Boulinguez 2002) associated with reaching in ipsi- or contralateral space. As a Wnal point, Experiment 2 included the caveat that visual gaze be maintained on a central Wxation cross throughout a reaching response. Thus, our results cannot be explained by diVerences in retinal target position and/or between-task (i.e. pro- vs. anti-pointing) diVerences in saccadic drive. We propose that the visual Weld-speciWc endpoint bias described just above is congruent with the contention that anti-pointing is cognitively driven (Connolly et al. 2000) and mediated by visuomotor and visuo-perceptual networks (Milner and Goodale 1995; for recent review see Goodale et al. 2004). In particular, the assertion that antipointing is mediated, in part, by visuo-perceptual networks is supported by the fact that endpoint error for left and right space anti-pointing matches documented horizontal Weld asymmetries related to obligatory judgments (i.e. perceptions). Indeed, a number of studies report a leftward visual Weld bias for judgments of brightness (Elias et al. 2002; Nicholls et al. 2004), stimulus numerosity (Elias et al. 2002; Luh 1995), object size (e.g. Charles et al. 2007; Nicholls et al. 1999), as well as the judgment of object extent (Luh 1995; Nicholls et al. 1999): Wndings thought to reXect an attentional imbalance between the left and right visual Welds (see Milner et al. 1992). Thus, our results indicate that a perceptual bias of veridical target extent inXuences the sensorimotor transformations of antipointing. For example, veridical target extent in left visual space is overestimated thus leading to right space antipointing movements that reliably overshoot target location. In turn, veridical target extent in right visual space is underestimated thereby resulting in left space anti-pointing movements that undershoot target location. Of course, that pro-pointing responses did not exhibit a visual WeldspeciWc endpoint bias represents an expected Wnding because such actions are stimulus-driven and do not require (cognitive) mediation via visuo-perceptual networks (Binsted et al. 2007; Westwood and Goodale 2003; see also Day and Lyon 2000; Johnson et al. 2002). In other words, pro-pointing is supported by Euclidean visual information mediated by dedicated visuomotor networks (e.g. Pisella et al. 2000) whereas anti-pointing is mediated by visuomotor and visuo-perceptual networks.

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A notable extension to our explanation of the visual Weld-speciWc endpoint bias is that the sensorimotor transformations underlying vector inversion for a mirror-symmetrical response are visual—as opposed to visuomotor— in nature. Indeed, Zhang and Barash’s (Zhang and Barash 2000; see also Zhang and Barash 2004) electrophysiology studies involving non-human primates report that vector inversion for anti-saccades is the result of ‘switched connections’ between visual cells in the posterior parietal cortex (i.e. the intraparietal sulcus) (see also Schlag-Rey et al. 1997). This visual switching entails that veridical target location is remapped (via non-standard input pathway or recurrent connections) to visual receptive cells that are normally sensitive to target presentation in the opposite visual Weld. Notably, Zhang and Barash’s Wndings are extended via human neuroimaging studies demonstrating that antisaccading elicits a shift of parietal-related visual activity contralateral to the target stimulus to homologous regions contralateral to the movement goal (i.e. the direction of the anti-saccade) (see Everling et al. 1998; Medendorp et al. 2005; Moon et al. 2007). Because the posterior parietal cortex also serves as the sensory to motor interface for limb movements (Chang and Ro 2007; Jeannerod et al. 1995; but see Connolly et al. 2000) it is possible that vector inversion for anti-pointing is mediated by a visual switching mechanism comparable to anti-saccades.5 Thus, we propose that the cognitive nature of the visual inversion of target coordinates necessary to drive anti-pointing introduces a perceptual bias into the sensorimotor transformation supporting such responses. Certainly such a hypothesis is not only consistent with the anti-saccade literature but also patient literature demonstrating a direct visuo-spatial transposition of stimuli from one side of the body to the opposite side (i.e. so-called allochiria; Grossi et al. 2004).6 One Wnal issue to be addressed is the impact of the target vision manipulation used in Experiment 1. Recall this manipulation was predicated on work from the pictorial illusions literature and the observation that occluding a stimulus at, or for some period of time prior to movement initiation, impacts the degree to which visuo-perceptual bias inXuences motor output (e.g. Hu and Goodale 2000; Heath et al. 2004a; Westwood et al. 2000). To that end, the present investigation required that participants complete reaches (with continuous limb vision) under conditions wherein the

target was continuously visible (T-V), occluded at movement onset (T-OL), occluded at (T-D0) or 1,000 ms in advance of response cuing (T-D1000). The target manipulation inXuenced reaction times such that T-D0 trials were faster than the other conditions: a Wnding our group has previously shown to be related to the double stimulus cue (i.e. target occluded and tone presented concurrently) of the T-D0 condition (Westwood et al. 2005). The manipulation of target vision did not impact movement time nor did it inXuence endpoint accuracy (primary and secondary movement directions) or endpoint variability in the secondary movement direction. We did, however, observe an increase in endpoint variability in the primary movement direction (i.e. T-V < T-OL), and this eVect generalised to pro- and anti-pointing. Such results require two issues to be addressed. First, the fact that our manipulation of target vision did not systematically inXuence each metric reported here is in line with a number of studies in the memoryguided reaching literature and the assertion that a reasonably accurate, albeit temporally unstable, perception-based target representation is available to support movement planning and control processes (e.g. Elliott and Madalena 1987; Heath 2005; Heath and Westwood 2003; Heath and Binsted 2007; Heath et al. 2004b; Westwood et al. 2001, 2003). Put another way, memory-based target information can support the spatial and temporal parameterization of a response but at the cost of increased movement variability (for recent review see Heath et al. 2008a). Second, the fact that our manipulation of target vision did not amplify the visual Weld-speciWc endpoint error of anti-pointing counters the pictorial illusion literature and the assertion that contextdependent target features become increasing salient over increasing delays. It is, however, important to note that our work matches that of Krappmann et al. (1998) wherein memory-based anti-saccading showed equivalent endpoint accuracy relative to visually guided counterparts. Furthermore, work has shown that non-illusory geometric structure does not diVerentially inXuence the perceptual loading of visually and memory-guided reaching movements (Krigolson and Heath 2004; Krigolson et al. 2007). Thus, we conclude that anti-pointing movements to a visible or remembered target are supported by a common perception-based representation of target location.

5

Conclusions

The posterior parietal region is thought to serve as an interface for top-down contextual cues related to the obligatory goal of an action (e.g. Johnson-Frey 2004). 6 Allochiria frequently accompanies neglect and manifests as a disorder wherein the completion of geographical maps, the verbal description of well-knows places, copying of drawing and the pointing to visual targets within the impaired visual Weld are transposed to the ipsilesional side of the body (e.g. Grossi et al. 2004; see Joanette and Brouchon 1984 for pointing responses).

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The present investigation sought to document the behavioural characteristics of anti-pointing. Notably, our results demonstrate a visual Weld-speciWc pattern of endpoint bias such that overshooting and undershooting characterised the respective performance of left and right space anti-pointing. These Wndings were true independent of the limb performing

Exp Brain Res (2009) 192:275–286

the task and accompanying saccadic drive. Based on such Wndings, we propose that the endpoint bias reXected in antipointing is attributed to the cognitive nature of the task and corollary sensorimotor transformations computed as a function of integrative visuomotor and visuo-perceptual networks. Acknowledgments Discovery Grants (MH and GB) and an Undergraduate Student Research Award (AM) from the Natural Sciences and Engineering Research Council of Canada supported this research. In addition, a Major Academic Development Fund from the University of Western Ontario (MH) supported the infrastructure for this work.

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