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REPORT
1Laboratoire de Neurobiologie de la Cognition, Centre National de la Recherche Scientifique and Aix Marseille Université, Marseille, and 2Unité Mixte de Recherche Mouvement and Perception, Centre National de la Recherche Scientifique and Aix Marseille Université, Marseille, France
Submitted 22 May 2007; accepted in final form 11 July 2007
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ABSTRACT |
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INTRODUCTION |
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; Bernier et al. 2006; Crawford et al. 2004; Ghilardi et al. 1995; Goodbody and Wolpert 1999; Sober and Sabes 2003).
Most of our daily interactions with the environment are visually driven, and accordingly, a substantial amount of research has been devoted to uncovering the planning stages that underlie these movements. Nonetheless, we can also direct movements toward body parts that are not necessarily visible, the spatial location of which being solely defined through proprioceptive cues. The mechanisms mediating movement planning toward such "proprioceptive targets" have received less attention and therefore remain misunderstood. At first, one may expect the neural computations underlying these reaches to differ, at least partly, from those mediating reaches to visual targets, because the estimates of target locations are derived from different sensory modalities. As such, Sarlegna and Sainburg (2007) and Sober and Sabes (2005) recently showed that the sensory modality of a target influenced the weighting between the visual and proprioceptive estimates of one's pointing limb position during movement planning. Nevertheless, this evidence for flexibility in multisensory integration does not necessarily imply that the mechanisms driving the reach per se, i.e., the transformation of the target spatial location into motor commands, differ as a function of target modality. In fact, recent evidence rather suggests that reaches to proprioceptive targets undergo the same planning stages and are mediated by the same networks as reaches to visual targets. This stems from the finding that both types of reaches would use a common representation to code the spatial location of the target (Darling et al. 2007; Pouget et al. 2002). As such, Pouget et al. (2002) found a significant effect of eye position on the direction of reaching movements aimed toward a proprioceptive target, namely the subjects’ left foot. They concluded that target locations for reaches are represented in a common extrinsic coordinate frame irrespective of the sensory modality by which they are defined. This view was substantiated by Darling et al. (2007), who used PET functional brain imaging to locate the cortical areas activated when planning and guiding a reach to a proprioceptively defined location. They found strong activation in the occipital lobe and in higher-order visual association areas, interpreting these results as reflecting the transformation of proprioceptive spatial information into a common visual and proprioceptive frame of reference.
Here we seek to extend the findings of Darling et al. (2007) and Pouget et al. (2002) by testing whether reaches to visual and proprioceptive targets also undergo common sensorimotor transformations. To do so, we exposed subjects to a visual shift through displacing prisms, leading to an adaptive modification in the transformations that convert the sensory information regarding target location into the required motor output (Baraduc and Wolpert 2002; Buneo and Andersen 2006; Kitazawa et al. 1997; Marotta et al. 2005; Morton and Bastian 2004). We had subjects reach toward their unseen contralateral index finger before and after an adaptation phase in which movements performed with visual feedback were directed to visual targets while wearing prismatic goggles that induced a 10.5° lateral visual shift. We hypothesized that if movement planning entails common sensorimotor transformations irrespective of the sensory modality of the target, the aftereffects that result from a change in these transformations should generalize from reaches to visual targets to reaches to proprioceptive targets.
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METHODS |
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Sixteen right-handed volunteers (22.4 ± 2.5 yr) with normal vision and no known neurological deficits took part in the experiment. They gave their informed consent before their participation in the study, in accordance with the ethical standards set out in the 1964 Declaration of Helsinki.
Apparatus
A schematic view of the apparatus is presented in Fig. 1. Subjects were seated on a height-adjustable chair with a headrest to prevent movement of the head. With their right hand, they held on to a pointer which was fixed on the upper end of a light quasi-frictionless steel rod (mass = 434 g; length = 1.22 m; diameter = 1 cm). At the base of the rod were two potentiometers used to measure the movement of the pointer in the X- and Y-directions at 500 Hz. Moving the pointer incurred a slight curvature of the hand in the sagittal plane (2.5 cm upward over the entire trajectory).
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1 mm). The starting position consisted of a wide v-shaped metal support located 20 cm in front of the sternum, in line with the subjects’ midline. Throughout the experiment, the room was kept in total darkness, such that subjects could not see their body or the apparatus except the lit LEDs. Procedure
Subjects were randomly divided into two groups, namely a vision and a proprioception group (n = 8 per group). They all performed reaching movements in three experimental phases: a pretest, an adaptation phase, and a posttest. The procedures used for the two groups differed only in the sensory modality defining the central target during the pre- and posttests. For the vision group, a LED represented the central target. For the proprioception group, the "felt" location of the unseen left index finger defined the central target. The finger was passively positioned by the experimenter while subjects kept their eyes closed. The finger was extended so as to point straight down and touch a small metal ring placed directly above the extinguished 0° target. In the pre- and posttests, subjects performed 15 trials toward the central target, as well as 7 trials toward each of the –18 and 18° targets, for a total of 29 trials. It should be noted that, for both groups, the two peripheral targets were visual and consisted of LEDs. Every odd trial was directed toward the central target, with movements directed toward the peripheral targets randomly distributed over the remaining trials. The pre- and posttests were performed without prisms, and subjects did not receive visual feedback of the pointer or knowledge of results regarding their accuracy at any point during these phases.
The adaptation phase was identical for both the vision and proprioception groups. It consisted of 90 pointing movements (30 toward each of the –7.5, 10.5, and 28.5° targets presented in random order) while wearing 18-diopter displacing prisms inducing a leftward visual shift of 10.5°. We used the visual targets located at –7.5, 10.5, and 28.5° to perfectly counteract the prismatic deviation. Hence the targets visually appeared at –18, 0, and 18°, consistent with the target locations of the pre- and posttests. Subjects of both groups had their left hand resting on their left thigh for that phase. The interruption of the electrical contact between the pointer and the starting position switched the pointer LED on to provide vision of the movement for every trial of the adaptation phase (the interruption of the electrical contact was also used to detect movement onset). The LED was extinguished when the pointer crossed the 35-cm radius subtended by the targets, and vision of the pointer was not available between the trials when bringing the pointer back to the starting position. The task had no amplitude requirement, such that subjects were instructed to move past the targets as accurately as possible without stopping underneath them. They were asked to perform straight uncorrected trajectories and to reach the targets in a movement time ranging from 225 to 375 ms in all conditions. Trials outside this bandwidth were re-run (<5% of the trials had to be re-run). Off-line analyses showed mean movement durations of 287 ms for the vision group and 293 ms for the proprioception group, which were not significantly affected by target modality (P > 0.05). Hence, for both types of reaches, similar time was available for subjects to control their movements during their execution.
Data reduction
For each trial, we computed hand direction 100 ms after movement onset (equivalent to approximately one-fourth of the target distance) by calculating the angle between the position of the pointer at the 100-ms time point and the objective straight-ahead (the line passing through the body midline and the 0° target). This measurement is thought to be a good reflection of movement planning, because on-line modulations are unlikely to have taken place this early in the movement (Sarlegna et al. 2004; Sober and Sabes 2005). In addition, we computed hand direction when crossing the 35 cm target radius. We assessed the presence of aftereffects by comparing hand direction at these landmarks between the pretest and the posttest using a 2 group (vision, proprioception) x 3 target (left, central, right) x 3 experimental phase (pretest, adaptation phase, posttest) ANOVA with repeated measures on the last factor. The same 2 group x 3 target x 3 experimental phase analysis was performed for the intraindividual variability data at the 100-ms time point and at the 35-cm radius. Because the initial movements performed with the prisms were naturally more variable, we used only the last 21 trials (7 per target) from the adaptation phase for analysis, which was consistent with the number of trials for the peripheral targets in the pre- and posttests. Tukey's test (P < 0.05) was used for post hoc comparisons.
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RESULTS |
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The same statistical analysis (2 group x 3 target x 3 experimental phase) was conducted for the hand direction data and the intra-individual variability data at the 35-cm radius, the results of which were very similar to those obtained at the 100-ms time point. In fact, the same contrasts were found to be significantly different. This confirms that subjects complied with the task requirement of producing straight trajectories.
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DISCUSSION |
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; Pouget et al. 2002). We used a prismatic adaptation paradigm to adaptively modify these sensorimotor transformations and hypothesized that if they were common to both types of reaches, the aftereffects witnessed for movements to visual targets would generalize to movements to a proprioceptive target. We found that exposure to displacing prisms produced large aftereffects when reaching to visual targets in the dark, but none toward a proprioceptive target. Most importantly, as seen for the proprioception group, these differential effects for visual and proprioceptive targets were observed within the same subjects and within the same experimental phase. Indeed, on consecutive trials in the posttest, subjects from that group were accurate when reaching toward their unseen left index finger, but showed large errors (i.e., aftereffects) when reaching toward visual targets.
Lack of generalization of adaptation after a period of prismatic exposure has been reported for various types of movements, and several task parameters are known to be at play. For example, generalization typically does not take place when movements are performed at different velocities (Kitazawa et al. 1997) or with different kinematics (Baily 1972; Freedman et al. 1965; Martin et al. 1996). Furthermore, modifications in initial arm configuration (Baraduc and Wolpert 2002) and changes in the type of visual feedback provided (Norris et al. 2001) have also been shown not to lead to generalization. Nevertheless, these factors were constant for both types of reaches in this study, and therefore cannot account for the lack of generalization observed here. In fact, the sole difference between both types of movements was the sensory modality defining the spatial location of the central target (i.e., vision or proprioception). Hence another possibility is that vision or proprioception were differentially influenced by the prisms (Hatada et al. 2006; Harris 1963), leading to a shift in the perceived location of the visual target but not the proprioceptive target, or vice versa. However, we believe this to be unlikely, because much prism literature (Clower et al. 1996; Harris 1963; Redding et al. 2005) has shown that the parameters of this experiment minimize the likelihood of producing a shift in the visual representation of the target. For example, we avoided asymmetric exercise of the eyes during exposure by using a different set of targets that perfectly counteracted the prismatic deviation. Gaze direction was thus constant throughout the experiment, preventing sensory information from extra-ocular muscles (as well as eye efferent information) to affect the perceived location of the target (Blouin et al. 1996; Gauthier et al. 1990; Henriques and Crawford 2002). Furthermore, it is also unlikely that the spatial location of the target defined by proprioception of the left limb was modified by the prisms, because prismatic adaptation does not alter the felt position of the unexposed limb (Beckett 1980; Choe and Welch 1974; Morton and Bastian 2004). In this regard, it is possible that the unaltered proprioceptive information from the left index finger, which was positioned within the workspace in the posttest, somehow contributed to recalibrate the visuomotor relationship toward its preadaptive level. This may account for the finding that the magnitude of the aftereffects showed by the proprioception group for the peripheral visual targets was slightly less than that observed for the vision group.
Taken together, if the perception of target location was unaffected by adaptation for both types of reaches, the differential aftereffects must result from distinctions in the way this sensory information was transformed into the required motor output. It should be noted that an arm movement that is adapted to a novel sensorimotor relationship (once the transient adaptation-specific mechanisms are complete; Krakauer et al. 2004; Seidler et al. 2006) undergoes the same planning stages as before adaptation. Therefore these results indicate that prismatic adaptation induces plastic modifications to a transformation stage that is independent for both types of movements. These new findings extend the current knowledge of goal-directed arm movements as they imply that separate, differentially adaptable sensorimotor transformations mediate reaches to visual and proprioceptive targets.
The paradigm used here does not allow us to make decisive claims regarding the frame of reference in which the visual and proprioceptive targets were coded. Nonetheless, the possibility remains that the separate sensorimotor transformations be the result of distinctions in the frame of reference in which the two types of targets were coded. While this interpretation may be counter to the conclusions of Darling et al. (2007) and Pouget et al. (2002), it is well documented that the coordinate frames used for reaching movements are highly context-dependent (Battaglia-Mayer et al. 2000; Blouin et al. 1993; Buneo and Andersen 2006; Desmurget et al. 1997; Lacquaniti et al. 1997; McIntyre et al. 1998). For instance, Pouget et al. (2002) provided subjects with vision of their limb's initial position, whereas we never provided such information to our subjects in the pre- and posttests. As such, it has been shown that the patterns of errors for reaches to remembered locations are consistent with an extrinsic coding when the initial hand position is visible (Flanders et al. 1992), but with an intrinsic coding when it is not visible (McIntyre et al. 1998). Moreover, Darling et al. (2007), as well as others (Baud-Bovy and Viviani 1998; Tillery et al. 1991), used paradigms in which reaches to proprioceptive targets were not directed toward one's own body part such as in this study, but rather consisted of reaching back to a spatial location previously adopted by the same limb. Such a task may have led subjects to use a visualization strategy to store the endpoint's spatial location and plan the subsequent reach similar to movements directed to remembered visual targets (Lacquaniti et al. 1997). This might explain why these authors found evidence for extrinsic trajectory coding in the absence of visual targets.
Taking this idea further, our results are consistent with the findings of Sarlegna and Sainburg (2007) and Sober and Sabes (2005), who assessed the relative weighting of vision and proprioception of the pointing limb before movement onset. They found that vision of the limb's initial position contributed to a greater extent to movement planning when reaching to visual targets and that limb proprioception contributed more when reaching to a proprioceptive target. This led Sober and Sabes (2005) to suggest that reaches to proprioceptive targets may be coded directly in intrinsic space. Within this framework, one tentative explanation for the differential aftereffects observed here after adaptation is that separate target representations may have been used for the two types of targets: an extrinsic frame of reference for the visual targets and an intrinsic frame of reference for the proprioceptive target. It follows that these different target representations would be independently transformed into the required motor output, thereby accounting for the lack of generalization of adaptation.
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FOOTNOTES |
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Address for reprint requests and other correspondence: J. Blouin, Lab. de Neurobiologie de la Cognition, CNRS and Aix Marseille Univ., 3, Place Victor Hugo, 13331 Marseille Cedex 3 France (E-mail: jean.blouin{at}univ-provence.fr)
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ABSTRACT
INTRODUCTION
