The Journal of Neurophysiology Vol. 78 No. 2 August 1997, pp. 1170-1174
Copyright ©1997 by the American Physiological Society

RAPID COMMUNICATION

Systematic Changes in Directional Tuning of Motor Cortex Cell Activity With Hand Location in the Workspace During Generation of Static Isometric Forces in Constant Spatial Directions

Lauren E. Sergio and John F. Kalaska

Centre de Recherche en Sciences Neurologiques, Département de Physiologie, Université de Montréal, Montreal, Quebec H3C 3J7, Canada

	ABSTRACT

Abstract Introduction Methods Results Discussion References

Sergio, Lauren E. and John F. Kalaska. Systematic changes in directional tuning of motor cortex cell activity with hand location in the workspace during generation of static isometric forces in constant spatial directions. J. Neurophysiol. 78: 1170-1174, 1997. We examined the activity of 46 proximal-arm-related cells in the primary motor cortex (MI) during a task in which a monkey uses the arm to exert isometric forces at the hand in constant spatial directions while the hand is in one of nine different spatial locations on a plane. The discharge rate of all 46 cells was significantly affected by both hand location and by the direction of static force during the final static-force phase of the task. In addition, all cells showed a significant interaction between force direction and hand location. That is, there was a significant modulation in the relationship between cell activity and the direction of exerted force as a function of hand location. For many cells, this modulation was expressed in part as a systematic arclike shift in the cell's directional tuning at the different hand locations, even though the direction of static force output at the hand remained constant. These effects of hand location in the workspace indicate that the discharge of single MI cells does not covary exclusively with the level and direction of force output at the hand. Sixteen proximal-arm-related muscles showed similar effects in the task, reflecting their dependence on various mechanical factors that varied with hand location. The parallel changes found for both MI cell activity and muscle activity for static force production at different hand locations are further evidence that MI contributes to the transformation between extrinsic and intrinsic representations of limb movement.

	INTRODUCTION

Abstract Introduction Methods Results Discussion References

The complex mechanics of multiarticular movement would appear to complicate the generation of the forces and muscle activity required to produce reaching movements (Flash and Mussa-Ivaldi 1990; Hollerbach and Flash 1982; Mussa-Ivaldi et al. 1985). For instance, it is well documented that electromyographic (EMG) patterns vary with limb posture owing to their dependence on such mechanical factors as joint-angle-dependent changes in moment arms, muscle pulling angles, and muscle length-tension properties (Buchanan et al. 1986; Buneo et al. 1996; Flanders and Soechting 1990; Karst and Hasan 1991; Van Zuylen et al. 1988). To generate the appropriate muscle activity patterns, many motor control models predict that central motor structures must have information about current limb posture and how to adjust EMG activity patterns as a function of posture. Psychophysical studies suggest that the motor system does contain an internal model of peripheral skeletomuscular mechanics (Gomi and Kawato 1996; Shadmehr and Mussa-Ivaldi 1994; Wolpert et al. 1995). A key question is: at what level does this internal model exist? Is the postural dependence of muscle output resolved exclusively at the spinal level (Feldman and Levin 1995; Giszter et al. 1993)? Alternatively, do more central structures, including the primary motor cortex (MI), also alter their output as a function of arm posture, thereby contributing to the posture-dependent adjustment of EMG activity?

Evidence suggests that motor cortical cell discharge is influenced by arm posture. Caminiti et al. (1990, 1991) found that cells in MI altered their directional tuning as a function of the starting arm position for reaching movements along parallel hand paths in different parts of the workspace. In a complementary study, Scott and Kalaska (1995, 1997) reported that the activity of many MI cells was altered when monkeys made reaching movements along similar handpaths while holding the arm in two different orientations. Both results are consistent with the hypothesis that MI could potentially contribute to the requisite posture-dependent alterations in EMG activity. However, these studies are difficult to interpret in part because of the complex dynamics of movement.

Alterations of MI activity as a function of peripheral skeletomuscular mechanics might be easier to demonstrate in an isometric task. Fromm (1983) reported that when monkeys exerted constant torques about the wrist at different angles of wrist flexion-extension, the discharge of some wrist-related MI pyramidal tract neurons changed in a manner that paralleled the changing length-tension properties of forearm muscles. In the present study, we have extended this to multiarticular behavior, using a task in which a monkey used the whole arm to exert isometric forces at the hand in constant spatial directions while the hand was in one of nine different spatial locations on a planar workspace. We examined whether single-cell activity in MI covaried only with the size and spatial directionality of the force output at the hand or was also modulated as a function of the arm posture in which the constant static output forces were generated. We present here a summary of the effect of arm posture on cell behavior during static force generation.

	METHODS

Abstract Introduction Methods Results Discussion References

A juvenile male rhesus monkey (Macaca mulatta; 5 kg) was trained to exert a force with the right arm against an isometric manipulandum. The manipulandum consisted of a 20-mm ball on the end of a rigid 65-mm vertical rod attached to a 6-degree-of-freedom force/torque transducer (Assurance Technologies, F3/T10 system). The transducer was housed inside a box that could be clamped into one of nine different locations in front of the animal. A monitor was positioned at eye level 60 cm in front of the monkey. A cursor displayed on the monitor gave continuous feedback corresponding to the current force level applied to the force transducer in the X-Y (horizontal) plane. At the start of each trial, a circle appeared at the center of the monitor screen. The diameter of the central force target corresponded to an acceptable force range of 0.20 N. A constant bias in the display of the cursor position on the monitor required the monkey to exert a force of +0.3 N along the Y-axis (away from the monkey) to position the cursor at the center of the central force target. The monkey maintained the cursor within the central force target for a variable period of time (ranging from 1 to 3 s). At the end of the central hold time (CHT), the central target disappeared and one of eight peripheral force targets (diameter: 0.28 N) arrayed in a circle around the central target appeared. The separation of the centers of the central and peripheral targets corresponded to a force of 1.5 N. The monkey generated the 1.5-N force in the indicated direction to displace the cursor into the peripheral target circle, and held it there for 2 s. To summarize, successful performance of the task involved three phases of force production. Initially, exertion of a small static bias force held the cursor in the center target. After target appearance and a reaction time delay, a dynamic force ramp displaced the cursor into the target window. Last, a static target force was required to hold the cursor at the peripheral target.

Target directions were spaced at 45° intervals, starting from 0° (directly to the right) and rotating counterclockwise to 315°, following standard trigonometric convention. Throughout the trial a deviation of force in the vertical (Z) direction of more than ±0.26 N resulted in an error and the trial would restart. In this way the animal was trained to produce force trajectories confined to a horizontal plane (±10°). The eight targets were repeated five times in a randomized block design. These 40 trials constituted one data file.

The monkey performed files of 40 trials with the manipulandum placed in one of nine different locations in the workspace in front of the monkey. A central location was at the midline, 20 cm in front of the sternum. The other eight locations were equally spaced every 45° on the circumference of an 8-cm-radius circle, starting at 0°. Locations around the circle were tested in a pseudorandom sequence for a total of nine files (360 trials) per complete data set. Thus the animal viewed the same display and produced identical output forces at the hand while holding the hand at a total of nine different spatial locations. For clarity, the term "target" will refer to the force targets displayed on the monitor, whereas the term "location" will refer to the placement of the manipulandum in the workspace in front of the monkey.

Conventional single-unit recording techniques were used to record the activity of single cells in MI during the tasks (Kalaska et al. 1989). An unbalanced repeated-measures analysis of variance (ANOVA; program 5V, BMDP Statistical Software) was used to determine whether force direction or hand location had a significant effect on the cell discharge rate in each epoch. The analyses reported here focused on time periods (epochs) during the two static force production phases of the task: 1) CHT, which ended on target appearance, and 2) peripheral target hold time (THT), while the target static force level was being maintained.

In addition, in separate recording sessions, task-related activity was recorded from pairs of shoulder and elbow muscles implanted percutaneously with Teflon-coated single-stranded stainless steel wires. EMG activity was amplified, rectified, and integrated (10-ms bins) to generate summed histograms of activity during the five trials in each of the eight directions. The area under the summed histograms during each behavioral epoch was determined and subjected to the same ANOVA as the cells. A total of 16 muscles was studied.

	RESULTS

Abstract Introduction Methods Results Discussion References

Activity was recorded from 112 cells located in the anterior bank of the central sulcus in the left motor cortex. The criteria for including a cell in the sample were 1) the cell had to respond to movements of the right shoulder and/or elbow and 2) the cell had to be directionally tuned during either the dynamic force ramp phase or during THT, in at least one of the nine locations. Complete data sets from all nine locations were collected from 46 neurons. Only the results of the analyses from these 46 cells are reported here. Results from cells with partial data sets (<9 locations) were consistent with the response properties described here.

Cell activity was broadly tuned for static force direction during the THT epoch (Fig. 1A), as described previously for static posture maintenance and static force generation (Georgopoulos et al. 1984; Kalaska and Hyde 1985; Kalaska et al. 1989; Taira et al. 1996). The discharge rate of all 46 cells was significantly affected by direction of static force during THT (Wald test, main effect of direction  < 0.001).

View larger version (32K): [in this window] [in a new window]   View larger version (26K): [in this window] [in a new window]   FIG. 1. A: discharge pattern of primary motor cortex cell during isometric force production while hand is in central location. The 8 rasters illustrate cell activity during 5 trials; position of each raster corresponds to direction of force production away from starting central force target. Data are oriented to onset of cursor movement [i.e., dynamic force onsetpoint at which force level was 2 SD above its mean center hold time (CHT) value] denoted by solid vertical line labeled M. For each trial, heavy tick mark to left of movement onset line shows time of peripheral target onset, whereas heavy tick mark to right shows time at which final static level of force within peripheral force target was attained. Eight rasters surround polar plot depiction of cell activity. Radius of circle in polar plot: mean cell discharge rate during center hold (CHT) epoch. Length of each axis: mean discharge rate over 5 trials of force production in that direction during peripheral target hold time (THT) epoch. Heavy arrow: preferred direction of cell during THT. B: polar plot representations of response of neuron depicted in A at all 9 hand locations. Position of each polar plot corresponds to relative location of hand on planar work surface, with top plot corresponding to most distal hand location. Note change in mean cell discharge rate during CHT at different hand locations (radius of circles).

The most salient finding was that the discharge rate of all 46 cells was also significantly affected by hand location during THT (Wald test, main effect of position  < 0.001). That is, all cells showed changes in their overall level of discharge during THT as a function of location. In addition, all 46 cells also showed an interaction between force direction and hand location (Wald test,  < 0.001), indicating that the covariation of discharge with force direction changed for all 46 cells as a function of the location of the hand in the workspace.

One cause of an interaction effect could be a change in a cell's directional tuning (Scott and Kalaska 1997). Many of the cells examined showed systematic shifts in their directional tuning when the hand was placed in the different locations. The polygons in Fig. 1B summarizing the activity of an individual cell at all nine locations during the THT epoch illustrate a typical example of the nature of the directional shifts observed. In the figure, an arclike pattern is evident, whereby the preferred directions tend to rotate clockwise for locations to the right in the workspace and counterclockwise for locations to the left. There is little rotation of this particular cell's preferred direction for locations along the 90-270° axis.

To quantify the pattern of directional shifts in the whole sample, the change in preferred direction relative to that recorded at the central location was calculated at each peripheral location for each cell. A systematic relationship was found, as illustrated by Fig. 2. The directional tuning tended to shift clockwise relative to the central location for hand locations to the right in the workspace (e.g., mean shift at 0° location: 15°), whereas the directional tuning tended to shift counterclockwise for locations in the left half of the workspace (e.g., mean shift at the 180° location: +20°). The difference in the distributions of directional tuning shifts at the eight peripheral hand locations was significantly different (ANOVA,  < 0.001).

View larger version (22K): [in this window] [in a new window]   FIG. 2. Histograms (10° bins) displaying shift in directional tuning between central and peripheral hand locations for each cell during THT. Position of histogram corresponds to peripheral hand location. CCW, counterclockwise; CW, clockwise.

Similar to that seen during the THT epoch, 44 of 46 cells (96%) showed a main effect of hand location during the CHT period (Wald test,  < 0.001). This indicates that there was a change in the overall level of tonic activity during the initial period of static bias force generation along the Y-axis while the hand was held at different spatial locations (Fig. 1B).

The variation in muscle activity for different force directions and different hand locations was similar to that observed for cell activity. During the THT epoch, EMG activity for all of the 16 muscles examined showed a significant main effect of both hand location and force direction, and a significant interaction effect between posture and direction (Wald test,  < 0.001). The activity of 14 of 16 muscles was also significantly affected by hand location during the CHT epoch. The activity of the anterior deltoid clearly showed all three effects (Fig. 3). There was a dramatic effect of location on the overall level of activity during the CHT epoch (indicated by the radius of the circles) and also on the overall level of activity during THT (indicated by the size of the polygons). Third, there was a highly significant interaction between force direction and hand location (Wald test,  < 0.001), including a systematic pattern of rotation of the preferred direction of EMG activity during static force generation in the THT epoch (Fig. 3). The directional tuning of the total sample of muscles shifted (relative to that in the central location) by an average of 17° (clockwise) for the 0° hand location and +11° (counterclockwise) for the 180° hand location.

View larger version (29K): [in this window] [in a new window]   FIG. 3. Mean activity of anterior deltoid muscle of right arm during directional isometric force production while hand is in 9 different locations. Data were collected while monkey performed same task as for cell recordings. Display format is similar to Fig. 1B. Length of each axis is proportional to mean area under amplified, rectified, and integrated electromyographic (EMG) historgram during THT.

	DISCUSSION

Abstract Introduction Methods Results Discussion References

Despite a constant static spatial force output at the hand, including both force level and direction, we observed a change in cell discharge with different hand locations, including changes both in the level of discharge and in directional tuning. Because the animal maintained a stable body position throughout the experiment, each hand location required a different arm posture. These results complement those of Scott and Kalaska (1995, 1997), who found changes in cell activity after movement while the monkey held the hand in constant spatial locations with two different arm orientations.

Scott and Kalaska (1997) found no systematic pattern of directional shifts between arm orientations. They argued that none should be expected because the arm orientation rotated about an axis parallel to the plane of limb movements. In contrast, Caminiti et al. (1990, 1991) found a systematic rotation of cell preferred directions about the vertical axis when monkeys made reaching movements in parallel directions in different parts of workspace. They suggested that these directional shifts paralleled the changes in the spatial direction of hand movement that would result from activation of a given cell's peripheral muscle field while the arm was in different postures (Burnod et al. 1992), and concluded that the coordinate system for this mapping process was centered on the shoulder. Similar to Caminiti et al. (1990, 1991), and in contrast to Scott and Kalaska (1997), the changes in arm posture in this study swept across the workspace about an axis out of the plane of the task. The arclike pattern of directional shifts from left to right across the workspace found in this study resembles those reported by Caminiti et al. (1990, 1991), and could reflect a similar process that maps the changes in the size and direction of forces generated at the hand resulting from the activation of a given MI cell while the arm is in different postures.

The results from Caminiti et al. (1990, 1991), Scott and Kalaska (1997), and the present study all support the hypothesis that MI could be contributing to transformations between extrinsic and intrinsic representations of limb motor behavior. The parallel changes in MI cell activity and EMG responses in the present task are also consistent with this interpretation, but do not necessarily indicate that single MI cells are explicitly signaling the precise activity patterns of a given muscle or muscle field. However, the similarity in the way in which both single-cell and single-muscle activity separately covary with hand location and arm posture implies that the output signal from MI during static force generation is expressed in terms that capture, to a first approximation, the manner in which EMG activity must change with arm posture to generate the spatially constant forces at the hand. This would appear to facilitate the ultimate transformation of MI activity into muscle-specific signals at the spinal level.

The arclike pattern of directional shifts is also reminiscent of the results of psychophysical studies that have examined the nonlinear stiffness properties of the limb as it was held in different postures across the workspace (Flash and Mussa-Ivaldi 1990; Mussa-Ivaldi et al. 1985). In a particular position, the variation in restoring forces generated by the limb in response to small displacements (i.e., its "stiffness field") was described by an ellipse. The long axis of the ellipse always tended to be oriented along the line from the hand location to the shoulder. As a result, the orientation of this ellipse rotated counterclockwise in an arclike fashion as the hand location changed from a rightward to a leftward position relative to the shoulder. This apparent parallel in the pattern of changes in orientation of stiffness ellipses and MI cell directional tuning could indicate that the motor cortex possesses information about the anisotropic mechanical properties of the limb and how those properties vary with arm posture. This is consistent with a hypothesis that MI contributes to a learned internal model of limb mechanics (Gomi and Kawato 1996; Wolpert et al. 1995). However, the causal link between limb mechanical properties and the posture-related cell activity changes in this task are speculative at this point.

These data demonstrate that the directional tuning of MI proximal-arm-related cell activity is not constant with the direction of force exerted at the hand. Previously, Shadmehr (1993) demonstrated that when the stiffness ellipses were calculated in a joint-centered rather than a hand-centered coordinate frame, they were relatively constant across the workspace. It is possible that the directionality of MI discharge would be more constant across the workspace if represented in a joint-centered coordinate frame. However, the data base at this point is too small to attempt a quantitative evaluation of alternative reference frames, if any such unitary coordinate system exists in MI (Scott and Kalaska 1997).

We have discussed MI function in terms of two roles, extrinsic-to-intrinsic transformations and, alternatively, as an internal model of the motor apparatus. Rather than being mutually exclusive, however, these functions are probably related. If the intrinsic representation incorporated information about limb biomechanics, furnished by proprioceptive feedback or acquired by adaptive learning mechanisms, MI could contribute to an internal model of limb mechanical properties that is necessary both to resolve sensorimotor transformations and to compensate for the mechanical properties of the limb.

	ACKNOWLEDGEMENTS

  We thank L. Girard for expert technical assistance, R. Albert for developing the data acquisition software, and G. Richard for constructing the task apparatus. We also thank A. P. Georgopoulos for invaluable consultation in statistical analyses.

  This work was supported by the Medical Research Council Group Grant in Neurological Sciences and by Postdoctoral Fellowships from Fonds de la Recherche en Santé du Québec and Groupe de Recherche sur le Système Nerveux Central to L. E. Sergio.

	FOOTNOTES

  Address for reprint requests: J. F. Kalaska, CRSN, Dépt. Physiologie, Université de Montréal, C.P. 6128, Succ. Centreville, Montreal, Quebec H3C 3J7, Canada.

  Received 28 February 1997; accepted in final form 22 April 1997.

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