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Institut de Neurosciences Cognitives de la Méditerranée, Unité Mixte de Recherche 6193, Centre National de la Recherche Scientifique and Aix-Marseille Université, Marseille, France
Submitted 20 November 2007; accepted in final form 9 March 2008
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ABSTRACT |
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INTRODUCTION |
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). However, in daily life, activities requiring the hand and eye motor systems to work separately (driving, reading, typing, playing music, etc.) are as frequent, if not more. Also, we ceaselessly need to switch from one type of activity to the other. Such flexibility is unlikely to be achieved without each effector "knowing" where the other one is at all times, even if it is static and unneeded for the current task. There is some evidence that the static eye position affects hand movements (Blouin et al. 2002; Bridgeman and Stark 1991; Henriques et al. 1998). Here, we endeavor to provide behavioral evidence that this static effector influence is reciprocal.
The strongest support for a mutual influence of static effectors comes from recording studies in monkeys. In an early study, one of us showed that neuronal activity coding arm movements in the dorsal premotor area (Boussaoud et al. 1998; see also, e.g., Pesaran et al. 2006) varies according to the static eye position in the orbit. Recently (Thura et al. 2008), we addressed the converse issue by recording from the frontal eye field (FEF) of two monkeys performing delayed saccades while holding their hand either near or far from the eye target. Neurophysiological results were clear-cut: more than half of the saccadic neurons of this major oculomotor area integrate hand position signals to encode visually guided saccades. This was true irrespective of whether the animals could see their hand, indicating that FEF receives both visual and nonvisual information from the hand.
Behavioral data were less straightforward. Our prediction was that hand–target spatial congruency would reduce saccadic reaction times since 1) saccade latencies tend to decrease when a somatosensory stimulus is presented at the same spatial location as the visual target (Amlôt et al. 2003; Groh and Sparks 1996) and 2) the hand presence near a stimulus enhances visual processes (Brown et al. 2008; di Pellegrino and Frassinetti 2000; Reed et al. 2006; Schendel and Robertson 2004). Data collected in the course of FEF recordings only partly fulfilled this prediction because congruency reduced saccadic latencies for only one specific preparatory delay (500 ms for one animal, 1,000 ms for the other).
The present behavioral study was thus undertaken 1) to ascertain that hand position, whether visible or nonvisible, reliably affects saccadic reaction times and 2) to elucidate the influence of the delay duration on this modulation. The effects of hand position on saccadic latencies were measured for the experimentally delayed saccades typically used to dissociate stimulus- from motor-related activity in neurophysiology, as well as for natural, nondelayed saccades. The exact same protocol was applied to the two monkeys involved in FEF recordings and to a group of 11 human volunteers. Because an influence of the static hand on saccadic reaction times has never been reported before, this cross-species comparison was necessary to determine to what extent findings from recording studies in monkeys can shed light on the human brain implementation of eye–hand interactions.
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METHODS |
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Two monkeys and 11 humans participated to the study. The monkeys were the same two adult males as reported in Thura et al. (2008): a Macaca fascicularis (monkey A) and a Macaca mulatta (monkey S). The behavioral data collected earlier during FEF recordings were included in the present results. All procedures involving the monkeys were in accordance with the European Community's Council Directive for the Care and Use of Laboratory Animals (86/609/EEC). The humans were six female and five male adult volunteers, ranging in age from 24 to 54 yr (mean age 32.9 ± 10.5 yr). Ten were naïve with respect to the experiment. Nine were right-handed and two left-handed, as assessed by a French adaptation of the Edinburgh Handedness Scale (Oldfield 1971). Experiments were conducted in compliance with the French Law (Titer I and II du Code de la Santé Publique) and with the understanding and consent of each subject. Each of them was free from self-reported neurological impairments affecting ocular control and had normal or (for three of them) corrected-to-normal vision.
Experimental setup and data acquisition
Monkeys were trained and humans were instructed to perform visually guided saccades while holding their hand at one of two possible locations on a touch screen. All human subjects (whether right- or left-handed) and monkey A performed the task using their right hand, whereas monkey S used his left hand. Monkeys were trained and humans instructed to keep the other, nonacting hand at rest under the screen; during testing sessions, the actual behavior of the subject was monitored via a videocamera placed above his/her head. Monkeys were seated in a primate chair with the head fixed to the chair. Humans sat on a regular chair with head stabilized by use of a bite bar. Eye position was recorded at 250 Hz using an infrared camera (ISCAN). Subjects faced a resistive touch screen (36 x 27 cm) inclined at a 45° angle under a mirror onto which stimuli were projected from a computer monitor positioned above their heads (Fig. 1 A). The semireflective properties of the mirror made the visual stimuli appear as if located on the underneath touch screen together with the hand. In this condition ("hand visible"), saccades were made while hand position was provided through both vision and proprioception. Insertion of a black paper board under the mirror made it fully reflective. Under this condition ("hand invisible"), visual stimuli still appeared on the touch screen, but the hand was invisible to the subjects. Saccades were thus made whereas hand position was felt only through nonvisual signals. Stimulus presentation and behavioral data acquisition were controlled using CORTEX software (htpp://www.cortex.salk.edu).
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A trial began with the presentation of a white square (2 x 2°) at the bottom left or the bottom right part of the screen. This stimulus instructed the subject to put his/her hand on the touch screen at that location (Fig. 1B) and was turned off when the hand contacted the touch screen. A fixation point (FP, white circle, 0.25° diameter) then appeared immediately at the (apparent) screen center, which the subject had to fixate without moving his/her hand. After 500 ms of fixation, a peripherical target (a white square, 1 x 1°) appeared at one of two possible locations, immediately above the hand positions at 10.3° from the screen center (two other targets located in the upper part of the screen were used in monkeys to study the sensory and/or motor fields of FEF neurons but these data were excluded from the present comparative study). Extinction of the FP served as a Go signal for saccade execution. In the nondelayed saccade task, target onset coincided with the Go signal. In the delayed saccade task, a delay period was introduced between target onset and the Go signal (Fig. 1C). Monkeys were submitted to two delays, 500 and 1,000 ms; humans to only one, 1,000 ms. Likewise, the stringent criteria used to define correct saccades for the extensively trained monkeys (duration <75 ms and 300-ms fixation within ±1.5° around the target center) were softened for naïve humans (duration <100 ms and 300-ms fixation with a ±2° precision). The hand vision condition and delay length were kept stable within each block of trials, varying only across blocks, whereas the target and hand positions changed on a trial-to-trial basis, based on a pseudorandom order within each block.
Monkeys received a liquid reward for each correct response. Their daily testing sessions varied in length depending on their motivation and included several blocks of nondelayed or delayed saccades, with or without hand vision. Before testing, humans were instructed to "make a saccade toward the target promptly at the Go signal and then fixate it as precisely as possible"; they received no response feedback during testing. Each human subject participated in two sessions on two separate days, one for the nondelayed and one for the delayed saccade task. Each session lasted about 40 min and consisted of a total of 144 trials separated in two blocks of 72 trials, one for each hand vision condition. Within each block, 18 trials were presented per hand–target configuration in a pseudorandom order. The order of sessions and blocks was balanced between subjects.
Data analysis
The ISCAN analog output was recorded in a CORTEX file and analyzed off-line with the use of a MATLAB routine (MathWorks, Natick, MA). The detection of saccade onset, used to determine saccadic reaction times (SRTs), was performed by differentiating the eye position signals. The beginning of the saccade was defined as the first moment in time after the Go signal at which the eye velocity exceeded a fixed threshold, set at 50°/s for monkeys and as close as possible to 50°/s (generally 70°/s) for humans whose looser head fixation yielded a poorer signal-to-noise ratio. For both species, trials with SRTs <80 or >500 ms, i.e., early and late responses, respectively, were excluded from analysis.
For each target, two hand–target spatial configurations were possible: the "congruent" configuration, when the hand was near the target, and the "noncongruent" one, when the hand was far from it. ANOVAs were used to determine the effects of four factors on SRTs: hand vision (hand visible vs. hand invisible), delay duration (0, 500, 1,000 ms in monkeys; 0 vs. 1,000 ms in humans), target position (right vs. left), and hand–target spatial configuration (congruent vs. noncongruent). For humans, SRTs were averaged for each subject and each testing condition and analyzed using a four-way ANOVA with repeated measures for each factor, and paired t-test for within-condition comparisons. For monkeys, ANOVAs and t-tests were performed separately for each animal, without repeated measures, due to highly variable numbers of trials across conditions.
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RESULTS |
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Monkey A performed an average of 192 ± 20 trials per condition (range: 61–405), with the right hand, for a total of 4,599 trials. Mean SRTs for each condition are illustrated in Fig. 2. The 2 x 3 x 2 x 2 ANOVA showed that all main effects, except hand–target configuration, were significant. Monkey A was slower to respond as the delay increased [131.8 ± 1.2, 231.2 ± 1.2, and 317.4 ± 2.2 ms for 0, 500, and 1,000 ms, respectively; F(2,4575) = 2,299.8, P < 0.001], slower when he could not see his hand than when he could see it [253.7 ± 1.9 vs. 221.4 ± 1.8 ms, respectively; F(1,4575) = 43.6, P < 0.001] and, to a lesser extent, slower for the right target, ipsilateral to his acting hand, than for the left one [237.9 ± 1.6 vs. 231.4 ± 2.4 ms, respectively; F(1,4575) = 17.6, P < 0.001]. Consequently, monkey A's longest SRTs occurred for saccades made to the right target after a 1,000-ms delay while the hand was invisible (321.0 ± 4.5 ms).
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Separate t-tests were conducted for each delay and target on SRTs pooled across vision conditions to further specify hand–target configuration effects (Table 1). For the ipsilateral target, the congruent configuration produced a 13% increase in SRTs relative to the noncongruent one without delay and a 4% increase with 500-ms delay, whereas it yielded a 7% decrease with 1,000-ms delay. For the contralateral target, the same delay-dependent reversal occurred but the amplitude of the changes was reduced and only the 6% increase observed for nondelayed saccades reached significance.
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Monkey S performed an average of 219 ± 15 trials per condition (range: 96–359), with the left hand, for a total of 5,259 trials. The 2 x 3 x 2 x 2 ANOVA yielded the same three main effects (delay, hand vision, and target) as in monkey A. Like monkey A, monkey S was slower to respond as the delay increased [208.8 ± 1.0, 255.3 ± 1.0, and 286.9 ± 0.9 ms for 0, 500, and 1,000 ms, respectively; F(2,5235) = 1,420.4, P < 0.001] and somewhat slower for the target ipsilateral to his acting hand than for the contralateral target [248.0 ± 1.0 vs. 241.3 ± 1.0 ms, respectively; F(1,5235) = 38.1, P < 0.001]. Contrary to monkey A, though, monkey S responded faster when he could not see his hand than when he could see it [235.9 ± 1.2 vs. 250.1 ± 0.9 ms, respectively; F(1,5235) = 119.0, P < 0.001]. Importantly, monkey S confirmed that hand position modified SRTs in opposite directions depending on the delay length [configuration x delay: F(2,5235) = 3.9, P = 0.02] and that this delay-dependent effect concerns mostly the target located in the hemifield ipsilateral to the acting hand, i.e., the left one for this animal [configuration x delay x target: F(2,5235) = 10.0, P < 0.001] irrespective of hand vision conditions [configuration x vision: F(1,5235) = 0.05, n.s.; configuration x vision x target: F(1,5235) = 2.1, n.s.; and configuration x vision x target x delay: F(2,5235) = 0.5, n.s.]. In the case of monkey S (Table 1), the congruent configuration yielded a 4% increase in SRTs to the left target without delay and a 4% decrease with 500-ms delay; all other changes failed to reach significance. Thus although the specific delay length triggering the reversal of the hand position effect differed across the two animals (1,000 ms for monkey A vs. 500 ms for monkey S), both displayed the same reversal affecting predominantly the ipsilateral target.
Hand position effects on SRTs in humans
GROUP PERFORMANCE. In humans, incorrect responses amounted to 5% of the nondelayed saccades and 12.8% of the delayed saccades and were excluded from the analyses. SRTs recorded during correct trials were averaged for each subject and each testing condition. Group means are illustrated in Fig. 3 for each condition. The four-way ANOVA yielded no main effect of delay [F(1,10) = 0.4; n.s.], hand vision [F(1,10) = 3.5; n.s.], or target [F(1,10) = 0.05; n.s.] in naïve humans, suggesting that the global impact of these factors in monkeys reflects a species specificity and/or biases acquired through extensive training in the task. Also, unlike monkeys, humans showed a slight but significant main effect of the hand–target spatial configuration [F(1,10) = 5.7; P = 0.04] because they were slower, overall, to initiate saccades when their hand was near the target than when it was far from the target (263.4 ± 4.4 vs. 258.5 ± 4.2 ms, for congruent and noncongruent trials, respectively).
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INDIVIDUAL DATA. Figure 5 provides, for each subject, the changes in mean saccadic latency (averaged across hand vision conditions) observed in the congruent hand–target spatial configurations relative to the noncongruent ones. These individual data confirm the different impact of hand position across targets. The deleterious effect of hand–target proximity on initiation of nondelayed saccade occurred in 9/11 participants (82%) and could reach an amplitude of +69 ms, for the right target, compared with 8 participants (73%) and a maximum of +30 ms for the left target. Likewise, the reversal produced by the 1,000-ms delay reached significance in 6/11 subjects (55%) and could amount to a gain of –43 ms for the right target, whereas it concerned only 3 subjects (27%) with a maximum gain of –26 ms for the left target (two subjects even showed opposite changes). Interestingly, the two left-handed subjects of the group (who nevertheless performed the task with their right hand) showed the same predominant impact on the right target. This suggests that the acting hand, rather than handedness, explains differences observed across targets.
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Despite the differences not only in species, but also in expertise in the task, similarities emerged between monkeys and humans, which are summarized in Fig. 6. In each of the two expert monkeys, as well as in the group of naïve humans, changes in SRTs due to hand position concerned mostly the visual target ipsilateral to the subject's working arm and took opposite directions depending on the length of the delay. Nondelayed saccades were retarded by the congruent configuration. This deleterious effect of hand–target proximity was slightly attenuated when hand vision was prevented, but remained significant. When saccade initiation was delayed relative to target onset, the hand position effect was reversed in both species. Hand–target proximity then facilitated saccade initiation. This facilitation was also detectable when the hand was invisible, but this time the change observed in the absence of hand vision fell short of significance.
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DISCUSSION |
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Similar hand position effects in two expert monkeys and naïve humans
A major strength of the present study is the parallel testing of monkeys and humans using the same apparatus and quasi-identical procedures. Most of our knowledge about the neural underpinnings of eye–hand interactions rests on recordings obtained from macaque monkeys that have received extensive training on a single specific task. Thus potential pitfalls for neurophysiology are to study monkeys' species-specific behaviors or idiosyncratic biases induced by overtraining, neither of which would likely shed light on human natural behavior.
In the present behavioral study, SRTs varied significantly with the delay, target, and hand vision condition only in monkeys. Species specificity may account for these monkey peculiarities. Also, it may well be that acquisition of a task through instruction (in humans) versus operant conditioning (in monkeys) is responsible for some of these differences. However, biases acquired over extensive training seem a more probable explanation, at least for the hand vision effect, because the two animals showed opposite patterns (monkey A responding more quickly for the visible hand, monkey S for the invisible hand). Overtraining-induced biases also likely explain the other idiosyncrasies of monkey S, i.e., 1) a reversal of the hand position effect occurring with preparatory delays of 500 ms, rather than 1,000 ms in monkey A and humans; and 2) the nonsignificant hand position effect for the target contralateral to the acting arm, again differing from both monkey A and humans.
Nonetheless, each of the two expert monkeys displayed, like naïve humans, a delay-dependent hand position effect for saccades to the target ipsilateral to the acting arm that was detectable in both vision conditions. This similarity confirms that monkey neurophysiology can provide valid insights into the neural bases of human eye–hand interactions.
Visual and nonvisual signals from the static hand affect saccadic latencies
Saccades characteristics were found to change when accompanied by an arm movement, both in humans (e.g., Epelboïm et al. 1997; Lünenberger et al. 2000; Mather and Fisk 1985; Neggers and Bekkering 2000) and monkeys (Snyder et al. 2002). The present study is the first behavioral evidence that, as surmised by Tipper et al. (2001), even when the hand is not performing a response toward the target, its mere position influences eye movement parameters.
Efferent motor signals (hand/arm commands) and afferent sensory signals (vision, touch, and proprioception) both contribute to the influence of arm movements on the oculomotor system (e.g., Ariff et al. 2002; Nanayakkara et al. 2003; Neggers and Bekkering 2001; Ren et al. 2006; van Donkelaar et al. 2004; Vercher et al. 1996). Here, the hand was static during saccade execution, but its position changed on a trial-to-trial basis and it had to be actively maintained onto the screen during the trial. Efferent motor signals were therefore not nil, albeit less prominent than in the preceding studies combining arm movements with saccade execution. Among afferent sensory signals, vision predominated, the strongest influence being observed when subjects could see their hand. Yet, nonvisual signals, in particular perhaps proprioceptive inputs, also contributed since some changes in SRTs persisted when hand vision was prevented.
Delay-dependent hand–target configuration effects on SRTs: an eye–hand competition for attentional resources?
Direct interaction between oculo- and skeletomotor brain areas, as well as integration of sensory signals from the hand in oculomotor centers (see Fries 1984, 1985; Neggers and Bekkering 2002; Stuphorn et al. 2000; Werner 1993; Werner et al. 1997), surely contribute to the changes seen here, as evoked earlier. However, an additional mechanism is necessary to explain the delay-dependent reversal of the hand position effect. One possibility relates to the temporal dynamics of spatial attention orientation. The capture of a particular stimulus by attention is short-lived: it varies across tasks and species, but remains inferior to 500 ms (Posner and Cohen 1984). After that, attention is slower to return to the previously inspected location, favoring instead new locations (for a review see Klein 2000). This inhibition of return (IOR), classically described for visual stimuli (Posner and Cohen 1984), also exists for tactile cues (Spence et al. 2000; Tassinari and Campara 1996). In our case, hand position was determined anew at the start of each trial. Visual and/or somatosensory signals from the hand could thereby attract spatial attention toward the hand location for a short time after hand positioning. However, by the end of the 500-ms fixation separating hand positioning from target onset, the IOR phenomenon likely yielded a new spatial attention shift, this time away from hand location. Nondelayed saccades being initiated immediately at target onset would thus fall during this IOR to the hand location—thus the longer SRTs for the congruent hand–target configuration. By contrast, due to the additional (preparatory) 500- or 1,000-ms period, delayed saccades intervened about 1,000 or 1,500 ms after hand positioning. Such delay would at least release the IOR or even allow still another spatial attention shift, back to the hand position, and thus the SRTs that were either unchanged or shortened for delayed saccades in the congruent configuration.
Although speculative, this idea of a dynamic eye–hand competition for attentional resources is supported by the recent findings reported by Neggers and Bekkering (2000, 2001), showing that humans cannot initiate a saccade to a second target until their visible or invisible hand has reached a first one. This finding suggests that there exists a spatial attention enhancement around the hand movement target that precludes eye movements. The temporal dynamics of this competition could also explain the variability of arm movement effects on SRTs, some authors observing a decrease (Lünenburger et al. 2000), whereas others report no significant effect (Epelboïm et al. 1997; van Donkelaar et al. 2004), or an increase (in humans: Bekkering et al. 1994, 1995; Mather and Fisk 1985; in monkeys: Snyder et al. 2002). Finally, our proposal is not incompatible with the facilitation of visual processes (e.g., target detection) observed in the hand presence in both normal (Reed et al. 2006) and brain-damaged humans (Brown et al. 2008; di Pellegrino and Frassinetti 2000; Schendel and Robertson 2004). Indeed, in these experiments the hand was kept static both within and across trials; its presence thus may have acted as a steady spatial attention attractor, rather than triggering shifts of attention as in our paradigm.
Predilection of hand position effects for the target ipsilateral to the acting hand: a challenge for future studies
Hand position effects on saccadic latencies were more pronounced for the target ipsilateral to the acting hand in monkeys and humans alike. This difference was related to the hand involvement in the task, rather than to subjects' handedness because both right- and left-handed humans, performing the task with the right hand, all displayed more marked effects for the right target. A similar behavioral bias was noted in one earlier study (Lünenburger et al. 2000), but remains unexplained.
Because most of our subjects (12/13) performed the task with their right hand, the possibility that this bias reflects a right-hand peculiarity cannot be ruled out. However, in light of recent neurophysiological evidence obtained by Oristaglio et al. (2006), an effector-specific effect seems more likely. Neurons in the lateral intraparietal (LIP) area, known to be involved in attentional and oculomotor processes, were found to be modulated by the active limb, irrespective of its spatial location. Moreover, some neurons were most responsive for visual cues appearing in the hemifield ipsilateral to the active limb. These neural properties, together with the present unexpected behavioral finding, raise the interesting possibility that sensory stimuli close to the effector currently involved in a task are processed differently in the brain. It may be worthwhile to test this hypothesis in the future by comparing hand position effects in the same subjects depending on whether they perform the task with the right hand, the left hand, or both.
Neuronal implementation
Areas devoted to the planning of hand movements are known to contain neurons whose properties integrate signals from the eye, whether moving or static (e.g., Batista et al. 1999; Battaglia-Mayer et al. 2006; Boussaoud et al. 1993, 1998; Jouffrais and Boussaoud 1999; Mushiake et al. 1997; Pesaran et al. 2006; Snyder et al. 2000; Stuphorn et al. 2000). There is now growing evidence that, reciprocally, oculomotor areas, including the superior colliculus (Meredith and Stein 1986; Werner 1993; Werner et al. 1997), the supplementary eye field (Mushiake et al. 1996), and LIP (Oristaglio et al. 2006), integrate signals from the hand, at least when it is moving. We recently demonstrated that another oculomotor area, the FEF, does integrate signals from the hand, even when static. Hand position modulates saccadic activity within the FEF (Thura et al. 2008) and preliminary data indicate that this holds true as well for FEF visual responses (Thura et al. 2007). Taken together with the present behavioral data, these neurophysiological findings suggest that the mere position of the hand influences visually guided saccades not only during the late preparatory phase preceding movement execution but also, very early on, during the presentation and encoding of the visual target. Hand position signals thus appear to influence neuronal processes underlying target selection and ocular exploration of space.
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GRANTS |
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Address for reprint requests and other correspondence: M. Meunier, INCM, UMR 6193, CNRS, Université de la Méditerranée, 31 Chemin Joseph Aiguier, 13402 Marseille Cedex 20, France (E-mail: meunier{at}incm.cnrs-mrs.fr)
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