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The Journal of Neurophysiology Vol. 81 No. 2 February 1999, pp. 875-894
Copyright ©1999 by the American Physiological Society
1 Departments of Neuroscience and Neurosurgery and 2 Department of Physiology, and the 3 Graduate Program in Neuroscience, University of Minnesota, Minneapolis, Minnesota 55455
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ABSTRACT |
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 Abstract
 Introduction
Methods
Results
Discussion
References
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Johnson, M.T.V., J. D. Coltz, M. C. Hagen, and T. J. Ebner. Visuomotor processing as reflected in the directional discharge of premotor and primary motor cortex neurons. J. Neurophysiol. 81: 875-894, 1999. Premotor and primary motor cortical neuronal firing was studied in two monkeys during an instructed delay, pursuit tracking task. The task included a premovement "cue period," during which the target was presented at the periphery of the workspace and moved to the center of the workspace along one of eight directions at one of four constant speeds. The "track period" consisted of a visually guided, error-constrained arm movement during which the animal tracked the target as it moved from the central start box along a line to the opposite periphery of the workspace. Behaviorally, the animals tracked the required directions and speeds with highly constrained trajectories. The eye movements consisted of saccades to the target at the onset of the cue period, followed by smooth pursuit intermingled with saccades throughout the cue and track periods. Initially, an analysis of variance (ANOVA) was used to test for direction and period effects in the firing. Subsequently, a linear regression analysis was used to fit the average firing from the cue and track periods to a cosine model. Directional tuning as determined by a significant fit to the cosine model was a prominent feature of the discharge during both the cue and track periods. However, the directional tuning of the firing of a single cell was not always constant across the cue and track periods. Approximately one-half of the neurons had differences in their preferred directions (PDs) of >45° between cue and track periods. The PD in the cue or track period was not dependent on the target speed. A second linear regression analysis based on calculation of the preferred direction in 20-ms bins (i.e., the PD trajectory) was used to examine on a finer time scale the temporal evolution of this change in directional tuning. The PD trajectories in the cue period were not straight but instead rotated over the workspace to align with the track period PD. Both clockwise and counterclockwise rotations occurred. The PD trajectories were relatively straight during most of the track period. The rotation and eventual convergence of the PD trajectories in the cue period to the preferred direction of the track period may reflect the transformation of visual information into motor commands. The widely dispersed PD trajectories in the cue period would allow targets to be detected over a wide spatial aperture. The convergence of the PD trajectories occurring at the cue-track transition may serve as a "Go" signal to move that was not explicitly supplied by the paradigm. Furthermore, the rotation and convergence of the PD trajectories may provide a mechanism for nonstandard mapping. Standard mapping refers to a sensorimotor transformation in which the stimulus is the object of the reach. Nonstandard mapping is the mapping of an arbitrary stimulus into an arbitrary movement. The shifts in the PD may allow relevant visual information from any direction to be transformed into an appropriate movement direction, providing a neural substrate for nonstandard stimulus-response mappings.
The dorsal premotor cortex (PMd) has a hypothesized role in the transformation of sensory stimuli into appropriate motor behaviors (Crammond and Kalaska 1996 Behavioral task
Experimentation was conducted according to the Guiding Principles for Research Involving Animals and Human Beings as endorsed by the American Physiological Society and was approved by the Institutional Animal Care and Use Committee of the University of Minnesota. Two female rhesus monkeys (Macaca mulatta, 4-6 kg) used a two-joint manipulandum to make visually guided arm tracking movements in the horizontal plane (Fu et al. 1993
Surgical, electrophysiological, and histological procedures
Once the monkeys had learned the tracking task, a chronic recording chamber (19 mm ID) was stereotaxically placed, and a head fixation halo was implanted (for details see Fu et al. 1993 Analysis
Neuronal spike trains and kinematic trajectories were aligned on the target onset at the start of the cue period, before averaging. Firing and kinematic data were then averaged over 10 repetitions for each of the 8 directions over the 4 target speeds. Neuronal firing frequency histograms with 20-ms bin increments were constructed from the averages. The firing was analyzed over three time intervals: the hold, cue, and track periods. The "hold" period represented the 500 ms before the appearance of the cue target, corresponding to the time in which the monkey held the cursor in the center start box. In addition to determining the mean firing from the trial averages, the standard deviation of the firing from the individual trial was calculated for the different periods.
Characteristics of the tracking task performance
Tangential velocity profiles and hand trajectories resulting from the tracking of the four constant speed targets are shown in Fig. 2. During the cue period, there were no systematic excursions in the hand velocity at any target speed. For the slowest 2-cm/s target speed trials, there were occasional increases in hand velocity while in the start box 100-200 ms before the onset of the track period. The hand velocity increased over the initial 200-400 ms of the track period to approach the target velocity. The initial rise in hand velocity was followed by an overshoot and several subsequent crossings of the target velocity. Small fluctuations in the hand velocity were present at all target speeds, but the paradigm limited these excursions to within the target area, otherwise the trial was aborted. The slight irregularities in the hand velocity reflect frequent feedback-dependent error corrections required for visually guided pursuit tracking. For the fastest 5-cm/s target speed trials, hand velocity could increase ~100-200 ms before the complete superposition of the start and target boxes. The hand velocity climbed to a value of 5 cm/s over the initial 300-400 ms of the track period and then fluctuated around the target velocity. Further examples of the tangential hand velocity are shown superimposed on the firing data in Figs. 6-8. The tracking trajectories for the eight directions were remarkably straight and similar for the four different target speeds. This was due to the fact that the paradigm constrained both speed and path.
Directional modulation of neural activity
Neuronal activity was recorded in two animals, CR and DN. Of the total 240 neurons, 57 were obtained from the right hemisphere of DN, 103 from the left hemisphere of CR, and 80 from the right hemisphere of CR. Of these 240 neurons, the discharge of 201 (84%) showed a significant period effect, and the discharge of 228 (95%) showed a significant direction effect based on the trial-by-trial ANOVA (P < 0.01). All 240 neurons were task related, that is their discharge exhibited either a significant period or direction effect. The ANOVA is a highly sensitive test of a directional effect (Crammond and Kalaska 1996
Differences in directional tuning as a function of the task sequence
Of the 132 neurons demonstrating significant directionality in both cue and track periods, many had PDs that differed between the cue and track periods (see Fig. 7). The distributions of the period PDs for the cue (Fig. 9A) and track (Fig. 9B) periods are shown in Fig. 9. Because both left and right hemispheres were used for recording, the PDs were normalized to a right hemisphere convention by mirror-reversing the PD of each left hemisphere neuron about the vertical meridian (Funahashi et al. 1989
Functional-anatomic correlations
Of the 212 neurons with significant directional tuning in either cue or track periods, 122 neurons were recorded in PMd and 84 were in MI. Five penetrations resulting in six directional neurons were located in the vicinity of the supplementary motor area (see Fig. 5A) and thus removed for the comparisons of PMd and MI. Most of the neurons with significant cosine tuning limited to the cue period were located in PMd (20 of a total of 26). For the 54 neurons with significant directional tuning only in the track period, 26 were located in PMd, whereas 28 were in MI. Neurons with directional tuning in both cue and track periods (n = 132) were also found in both PMd (n = 73) and MI (n = 54). The proportions of these three types of directional neurons showed significant differences between the PMd and MI (P < 0.001,
Temporal profiles of the preferred directions of individual neurons
To evaluate the directional tuning of individual cells with increased temporal resolution, the firing rate of these cells was fitted to the cosine model (Eq. 1) in sequential 20-ms bins. As described in METHODS, a significant fit (R2 > 0.7) to the cosine model was required for each bin and a minimum depth of modulation criterion within 1 SD of the average Idir from the cue and track periods was imposed. Thus the minimum Idir of a bin for the cue or track period was required to be larger than 0.13 or 0.36, respectively. The resulting significant PDs were used to map the temporal sequence of the PDs, or PD trajectory through the trial. The PD trajectory is referenced to the direction of the moving target for both the cue and track periods (see METHODS).
Temporal characteristics of the PD trajectories
From the slowest to fastest target speeds, the available time allowed for the transformation of directional visual information into directional motor commands ranged from 2.5 to 1 s. Because temporal constraints were found in the oculomotor behavior, the temporal profiles of the PD trajectories were also analyzed for similar constraints. The average latency of the directional discharge ranged from 299 to 388 ms for the fastest to slowest target speeds, respectively (Table 1). Linear regression analysis demonstrated that the average onset latencies significantly increased with decreasing target speed, with a slope of
Composite profiles of the PD trajectories
A composite of PD trajectories is shown for the extremes of target speed in Fig. 14A to illustrate the temporal evolution of directional tuning. These trajectories were obtained from 20 neurons selected from the sampled population on the basis of having the largest number of contiguously significant PD trajectories. The selected sample had a uniform distribution of PDs in both cue and track periods (Rayleigh test for uniformity, P > 0.3 in both cases) and was characteristic of the entire population of cells (Fig. 14B). The track period PD was first rotated to align on 0°, and the PD trajectories for the cue and track periods were rotated by an equal amount.
Directional coding during a visuomotor task
Three main findings emerged concerning the discharge of primary motor and premotor neurons during this instructed delay, pursuit tracking task. Both the instructed delay (cue) and the movement (track) periods differed from previously used center-out paradigms based on step movements. This task required visually guided, error-constrained arm tracking of a constant speed target, as opposed to fast steps of unconstrained trajectory and speed to a stationary target (Fu et al. 1993 PD trajectory and coordinate systems
The observed rotation in the PD trajectories may be a function of the coordinate system selected for the calculation of the PD, i.e., the workspace-centered system used in this report. It is acknowledged that the PD trajectories may differ in another, unidentified coordinate system. For example, it is not likely that a single system such as a joint or muscle based coordinate system can explain the rotations in the PD trajectories. First, the largest rotations in the PD trajectories occurred in the early cue period when there was no movement. It is highly unlikely that the discharge during the cue period is encoded in joint space when there is no joint movement, particularly given the extended duration of the cue period (1-2.5 s). Neurons in the PMd and MI are modulated by visuospatial aspects of moving to a target (di Pellegrino and Wise 1993 PD trajectory and multiplexed signal processing
Changes in the PD trajectory could be the result of multiplexing of other sensory or motor parameters within the neuronal discharge at specific times during the task. For example, changes in starting position or arm posture can alter the directional tuning of MI neurons (Caminiti et al. 1991 PD trajectory and visuomotor transformations
Initially in the cue period, all directions of the workspace are covered by a population of PD trajectories, an optimal situation for target detection (see Figs. 14 and 15). The shifts in the PD during the cue period may provide a wide aperture for single cells to detect targets moving at various directions. Once detected, the direction of the target and the direction of the upcoming movement can be processed. Along with direction, the speed of the target must also be identified. The onset of movement in this paradigm was not dictated by an explicit "GO" signal, rather it was governed by the speed of the target during the cue period. Preliminary analysis showed that the firing in the cue period was modulated by the speed of the target (Johnson et al. 1997 Implications for population vector rotation
The rotation of the PD during the long cue period in this paradigm may provide a mechanism for the rotation of the population vector that is initially tuned toward a visual target and eventually redirects toward the upcoming movement (Georgopoulos et al. 1989b
INTRODUCTION
Abstract
Introduction
Methods
Results
Discussion
References
; Godschalk et al. 1981; Johnson et al. 1996b; Mushiake et al. 1991; Weinrich and Wise 1982; Wise et al. 1992, 1997). Particular emphasis has been placed on visuomotor transformations, hypothesized to involve pathways from extrastriate visual areas to PMd and the primary motor cortex (MI) via the superior parietal lobule (for reviews see Johnson et al. 1996b; Milner and Goodale 1995; Wise et al. 1997). Neuronal populations in and surrounding the superior parietal lobule are directionally modulated before and during reaching movements (Johnson et al. 1996b; Kalaska et al. 1983), by visual and somatosensory stimulation (Albright 1984; Colby and Duhamel 1991; Steinmetz et al. 1987), and during conditional sensorimotor behavior (Mountcastle et al. 1975). Thus a variety of visuomotor signals reach the PMd.
; Wise et al. 1992). Similar premovement discharge has been described in MI (Alexander and Crutcher 1990; Crutcher and Alexander 1990; Georgopoulos et al. 1989a; Johnson et al. 1996b; Tanji and Evarts 1976). Premovement activity in the PMd is highly modulated by visuospatial information that is significant for upcoming motor acts (Crammond and Kalaska 1994; di Pellegrino and Wise 1993; Johnson et al. 1996b; Shen and Alexander 1997a,b; Zhang et al. 1997). In addition, gaze (Boussaoud 1995) and spatial attention (Boussaoud and Wise 1993; di Pellegrino and Wise 1993) modulate the discharge of PMd neurons, as does motor error (Flament et al. 1993). The discharge of PMd and MI neurons is also highly correlated with several parameters of movement including direction, position, amplitude, speed, and force (for reviews see Ashe 1997; Georgopoulos 1986; Wise et al. 1997).
; Johnson et al. 1996b). There is also a rostral-caudal gradient from PMd to MI reflecting the processing of visuospatial to motor information (Shen and Alexander 1997a,b). Evidence also points to a temporal sequencing of the visuomotor transformation in which the more visuospatial aspects of the task are processed earlier and the more motoric features later (Shen and Alexander 1997a,b; Zhang et al. 1997). For example, in tasks in which the visual information is dissociated from the actual movement, the discharge is characterized by an early phase reflecting the direction of the visual cue and a late phase reflecting the direction of the upcoming movement (Crammond and Kalaska 1994; Georgopoulos et al. 1989b; Lurito et al. 1991; Shen and Alexander 1997a,b; Wise et al. 1996; Zhang et al. 1997). The population vector has been shown to rotate from the direction of a visual cue to that of the upcoming movement (Georgopoulos et al. 1989b; Lurito et al. 1991). Also, there is sequential processing of information about the direction, position, and amplitude of a movement in the discharge of PMd and MI neurons (Fu et al. 1993, 1995). Therefore, in PMd and MI, both spatial gradients and temporal sequencing of information appear to contribute to the transformation of a visual stimulus into a limb movement.
). For reaching movements, standard mapping refers to a sensorimotor transformation in which the stimulus is the object of the reach. Nonstandard mapping is the mapping of an arbitrary stimulus onto an arbitrary movement. The results of imaging, lesioning, and electrophysiological studies support the hypothesis that the PMd plays an important role in nonstandard mapping (for review see Wise et al. 1996). How might nonstandard mapping be achieved? Evidence exists for the learning of complex stimulus-response relationships in the PMd (Boussaoud and Wise 1993; di Pellegrino and Wise 1993). However, learning of all possible stimulus-movement combinations may be computationally prohibitive, and it is possible that neural substrates exist for the more common types of nonstandard mappings. Furthermore, the brain may not distinguish between standard and nonstandard mapping and may use a common neural mechanism for both. For example, consider the processing of movement direction during a visually guided, instructed-delay reaching task. If standard mapping was operative, the prediction is that directional tuning would be constant throughout the task (Wise et al. 1996). Another possibility is that the directional tuning changes throughout the task, consistent with a nonstandard mapping process in which a visual stimulus from one direction can be transformed into movements of a different direction.
; Georgopoulos 1986; Wise et al. 1997). In this report a new paradigm based on two-dimensional pursuit tracking with the arm was used. The paradigm was designed to 1) provide a long instructed delay period that continuously presented visual information about the speed and direction of the upcoming movement, 2) elicit controlled movements of a specified speed and direction in which both parameters were controlled independently, and 3) require continual matching of visual input with motor output to maintain a straight trajectory within an error envelope. Analysis of the directional tuning of the discharge of these neurons (Caminiti et al. 1991; Fu et al. 1993; Georgopoulos et al. 1982; Schwartz 1992) was used to study the neuronal transformation of a dynamic sensory stimulus into a motor output. These results reveal that the directional tuning is not constant across the cue and track periods and that during the cue period the preferred direction gradually changes. A preliminary account of these findings has been presented (Johnson et al. 1996a).
METHODS
Abstract
Introduction
Methods
Results
Discussion
References
; Ojakangas and Ebner 1992). The task was performed on a workspace based on a modified center-out, eight target design (Georgopoulos et al. 1982), and its trial sequence is schematized in Fig. 1. The movements of the hand/manipulandum were displayed as a cross-shaped cursor on a computer monitor that was placed vertically, ~50 cm in front of the animal. The center of the monitor was aligned with the animal's sagittal plane, as was the center of the task workspace. The dimensions and size of the screen workspace and targets were identical to those of the actual physical workspace; however, horizontal movements were guided by visual cues mapped on a vertical plane. The task required the animal to track square targets that moved at constant speeds on the screen. The task sequence began by the animal positioning the center of the cursor (0.5 cm diam) in a square start box (1.44 cm2) at the center of the workspace for a random period ranging 1-2 s. After this hold period, a square target box of the same size appeared at the periphery of the workspace at one of eight target positions (0-315° in 45° increments) at a distance of 5 cm. This target then moved at one of four constant speeds (2, 3, 4, and 5 cm/s) along a straight line toward the start box. The time between target appearance and intersection with the start box is the "cue" period, and is analogous to the instructed delay period of other paradigms (for example, Crammond and Kalaska 1994; Georgopoulos et al. 1989a; Johnson et al. 1996b). During the cue period, the animal was required to maintain the center of the cursor within the start box. The animal could view its hand and manipulandum, but the tracking requirements of the task demanded that the animal concentrate on the screen.
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FIG. 1.
Schematic of the pursuit tracking task. Cue and track periods are shown. Arrow denotes the direction of the constant speed target. Plus sign shows the location of the cursor through the trial sequence. See METHODS for further details.
). The chamber was positioned to straddle the premotor and primary motor cortices. Anesthesia was induced and maintained with ketamine (20 mg·kg
1·h1 im) and xylazine (1-2 mg·kg1·h1 im) during the aseptic surgical procedure. Postoperatively, buprenorphine (0.05 mg/kg im) was administered for 5 days. Chambers were placed over three cortical hemispheres of the two monkeys (right and left in animal CR and left in DN).
) and conventional electrophysiological techniques (Fu et al. 1993). A neuron was recorded if its activity was audibly modulated during the performance of the task or related to active reaching movements. After isolation of a single unit, the action potentials were time-amplitude discriminated. The output of the discriminator was digitized and stored at 1-ms intervals. The digitized data were analyzed in bin sizes of 20 ms and averaged over the number of trials. These binned firing frequencies were used in the period regressions of cell discharge as a function of direction. For contour plots of cell activity and calculations of a cell's preferred direction trajectory (see Analysis), each bin was convolved with a Gaussian function with a standard deviation of 20 ms.
; Fu et al. 1993; Weinrich and Wise 1982). Specifically, the number of large pyramidal cells was averaged along the cortical surface of each slice in 3-mm increments. Density maps of the large pyramidal cells across the cortical surface were constructed, and the isodensity contour line of eight large pyramidal cells was taken as an estimate of the boundary between PMd and MI.
; Crammond and Kalaska 1996; di Pellegrino and Wise 1993; Georgopoulos et al. 1982; Shen and Alexander 1997a). The ANOVA was used to determine whether direction had a significant effect on the discharge in the cue or track periods and to detect significant changes in firing over the trial sequence from the hold, cue, to track periods. The criterion for either a direction or period effect was P < 0.01 (Tukey multiple comparisons). A neuron was considered task related if direction or period had a significant effect on its discharge.
; Mardia 1972). For each target speed, the mean firing rate (f) for each cue or track direction (
), was fitted to a cosine function
Alternatively, this can be expressed as
(1)
The peak of the cosine function, referred to as the preferred direction (PD), is given as
(2)
pd in Eq. 2 (for further details see Georgopoulos et al. 1982, 1984; Mardia 1972). Regression coefficients b0 and c1 denote the mean discharge over all directions and the modulation of the firing as a function of direction, respectively. Goodness-of-fit of the data to the cosine model (Eq. 1) was expressed as R2, with model significance (P < 0.05) requiring R2 > 0.7. The depth of directional modulation, Idir, was calculated by normalizing the slope of the regression, c1, to the averaged firing over all directions, b0 (Georgopoulos et al. 1982, 1988). Neurons whose discharge fit significantly to the cosine model will be referred to as "directionally tuned."
). This provided a nearly continuous estimate of the PD as a function of time and was referred to as the "PD trajectory." Here, discharge in each time bin was evaluated for a significant fit using a criterion of R2 > 0.7. An additional criterion was required of the PD trajectories to ensure that the determination of the PDs based on 20-ms bins reflected the directional tuning as a function of time. The depth of modulation (Idir) for each bin was required to be characteristic of the Idir obtained from the tuning curves based on the cue or track period averages. The Idir for each bin was required to be greater than the Idir -1 SD obtained from the entire cue or track period. The 5-95% confidence interval for the location of the PD for each 20-ms bin was also calculated based on the von Mises distribution (Batschelet 1981).
RESULTS
Abstract
Introduction
Methods
Results
Discussion
References
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FIG. 2.
Tangential velocities are shown (left) for 4 tracking directions (0, 90, 180, and 270°) and 4 target speeds (2, 3, 4, and 5 cm/s). Movement trajectories for all 8 directions and 4 target speeds are also shown (right). All traces are the averages of 10 trials. Dashed horizontal lines indicate the tangential target velocity during the cue and track periods (i.e., ideal tracking speed during the track period). All traces were aligned on the initiation of the cue period, which is marked by dashed vertical lines. The onset of the track period is denoted by solid vertical lines.
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FIG. 6.
Firing and speed profiles of a neuron with significant and congruent directional tuning in both cue and track periods. Histograms of average firing rates binned in 20-ms intervals are plotted over the trial sequence of hold, cue, and track periods for the 8 target directions and 4 target speeds (2, 3, 4, and 5 cm/s). Dashed vertical line denotes cue period onset, and solid vertical line denotes track period onset. Note that at the higher speeds the histograms appear less dense due to the smaller number of 20-ms bins being displayed. Averaged tangential hand velocity is superimposed on the firing rate. Below each set of histograms are plotted the cosine tuning curves ( 
) of the averaged firing (
) in the cue (left) and track (right) periods. The vertical bar above each averaged data point indicates 1 SD for the firing from the 10 trials.
). ANOVA demonstrated no significant direction effect for the cue period (P > 0.01) for all eight muscles sampled (n = 73 records). As expected, the EMG activity was highly modulated during the track period in all muscles (P < 0.01). The ANOVA was based on the EMG activity in the entire cue period and may have missed changes in EMG activity that occurred before the onset of movement. Therefore an additional binwise procedure was performed to detect the timing of any changes in EMG activity. A significant change was defined as that exceeding the mean hold period activity by ±3 SD. The times of significant change invariably occurred at the cue-track period transitions (Fig. 3). Over all directions and muscles, the binwise procedure detected significant EMG changes at an average of 37 ± 71 and 112 ± 124 ms before track onset for the 5- and 2-cm/s trials, respectively. There were no significant differences in the onset of the EMG changes across the eight muscles recorded (P > 0.1, ANOVA). Therefore, as shown previously (Turner et al. 1995), the EMG activity during the cue period was modulated at most for a brief period (~100 ms) before track onset.
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FIG. 3.
R e c t i f i e d e l e c t r o m y o g r a p h i c (EMG) activity from 4 muscles during the cue and track periods. Eight directions (0-315°, in 45° increments) of the slowest 2-cm/s target speed are shown. All traces result from averages of 10 trials aligned on cue signal onset and are shown for each muscle using the same scale. Dashed vertical lines denote the end of the hold period and cue onset; solid vertical lines divide the cue and track periods. Triangles above the traces indicate when the EMG activity differed by >3 SD from the mean activity during the hold period. Averaged epoch EMG activity as a function of direction is shown below the time course records.
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FIG. 4.
Horizontal (x) and vertical (y) components of the eye movements are shown over the temporal trial sequence and as trajectories over the workspace. Four of the 8 directions of the tracking task (0, 90, 180, and 270°) for the 2 extremes of target speeds, 2 cm/s (left) and 5 cm/s (right), are shown. An additional 1,000-ms period of eye movement data was included at the end of the tracking period. Leftmost dashed vertical lines mark the end of the hold period; solid vertical lines divide the cue and track periods. Rightmost dashed vertical lines mark the end of the track period. Single trials of unsmoothed eye movements are shown.
) but does not define the form of the directional modulation. Therefore to define the type of directional modulation, the average firing in the cue and track periods was fit to the cosine model (Eq. 1). Significant directional tuning as defined by the cosine model was found for 212/240 (88%) neurons. In 132, significant directional tuning was found for both the cue and track periods. In 26 neurons, significant directional tuning was present only during the cue period, and in another 54, the directional tuning was significant only in the track period. The majority of the analysis focused on the relationship of the directional tuning in the cue and track periods for cells in both PMd and MI.
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FIG. 5.
Locations of the penetrations corresponding to neurons with significant directional tuning for the 3 hemispheres studied. The left (A) and right (B) hemispheres from monkey CR and the right hemisphere from monkey DN (C) are shown. Electrode penetrations ( ) and marking lesions (
) are shown. The line drawn on the cortical surface is the estimate of the dorsal premotor cortex and primary motor cortex boundary.
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FIG. 7.
Neuron with significant but directionally noncongruent mean firing in the cue and track periods. Discharge histograms with superimposed tangential hand velocity traces and cosine tuning curves use the same conventions as Fig. 6.
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FIG. 10.
Distribution of the preferred directions, fractionated into early and late cue (cue 1 and cue 2) and track (track 1 and track 2) periods, for all neurons with significant directional tuning in 3 or 4 contiguous periods including the final track 2 (top row). Absolute differences between cue 1, cue 2, and track 1 relative to track 2 are shown (bottom row). The circular means ± SD are shown as a wedge superimposed on the absolute difference distributions.
; Johnson et al. 1996b). These neurons, like that illustrated in Fig. 8, may show directional tuning (di Pellegrino and Wise 1993; Johnson et al. 1996b). For the cell shown in Fig. 8, firing transiently increased for ~500 ms after the onset of the cue target. This signal-related firing was directionally tuned with a significant cosine fit for three target speeds and had an average PD of 145 ± 17°. Directionality of the firing was less pronounced relative to the "set neurons" shown in Figs. 6 and 7 as judged by the smaller proportion of the variance accounted for by the cosine model and the increased standard deviations of the averaged data points. Overall, firing decreased in the track period for all directions and was not significantly directionally tuned at any target speed. In the second half of the cue period and the whole track period, the neuronal discharge was lower than that during the initial baseline period. Of the 26 PMd neurons with directional tuning only in the cue period, all demonstrated initial firing transients (i.e., signal-related). In the 132 neurons directionally tuned over both cue and track periods, firing continued throughout the cue period. Thus the distinction made by Weinrich and Wise (1982) between signal-related and set-related activity has clear parallels in the present data.
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FIG. 8.
Neuron with increased firing confined to the cue period. Discharge histograms with superimposed tangential velocity traces and cosine tuning curves use the same conventions as Figs. 6 and 7. A solid line is drawn only through those data points with significant directional tuning (R2 > 0.7).
; Georgopoulos et al. 1982; Steinmetz et al. 1987). For the cue and track periods, the distributions of PDs were uniform about the workspace (Rayleigh test for uniformity, P > 0.1 in both cases). For a given neuron, the absolute difference in PDs (a range from 0 to 180°) between the cue and track period was calculated (Fig. 9C). A predominance of vectors was in the 0 to 90° range, with a mean of 45.2 ± 44.9°. Almost one-half (47%) of the neurons had an absolute PD difference of >45°. The PD distributions obtained from the cue and track periods were significantly different (P < 0.001, n = 132, Hotelling's paired test) (Batschelet 1981). Furthermore, the relative difference distribution (Fig. 9D) was significantly different from zero along the x-axis (P < 0.001), but not along the y-axis (P > 0.2, Student's t-test on the sine and cosine fractions with Bonferroni correction). This y-axis symmetry implies that clockwise or counterclockwise deviations of the cue PD relative to the track PD were equally probable. The relative difference plot (Fig. 9D) further demonstrates the equal probability of clockwise and counterclockwise differences between the cue and track PDs.
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FIG. 9.
Distribution of the preferred directions of all neurons with significant directional tuning (R2 > 0.7). Preferred directions were calculated from averaged firing of the cue or track periods relative to the direction of the moving target. A: distribution of the preferred direction (PD) vectors obtained from the cue period shown with the magnitude equal to the R2. B: distribution of the track period PD vectors with magnitude equal to R2. The outer circle in A and B denotes an R2 = 1. C: distribution of the absolute differences between cue and track PDs (range of distribution is 0-180°). D: distribution of the relative differences between the cue and track PDs.
2 3 × 2 table). Thus directional activity limited to the cue period was more frequently found in PMd cortex, consistent with previous observations (Alexander and Crutcher 1990; Johnson et al. 1996b; Weinrich et al. 1984).
2 4 × 4 table). A 4 × 4 table (4 directional tuning properties by 4 distance bins) was constructed by binning the data in 4-mm increments. A 4-mm binning was necessary so that all expected cell counts were >5, as required by the 2 statistic (Devore and Peck 1993).
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FIG. 11.
Locations relative to the central sulcus of 4 functional types of directional tuning. A: proportions of neurons with directional tuning only in the cue period (Cue) and directional tuning only in the track period (Track). B: proportions of neurons with PD differences between the cue and track periods of <45° and >45°. Although shown in 2 graphs, the proportions of the 4 groups add to 100% for each 2-mm distance.
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FIG. 12.
Sequence of tuning curves derived from sequential 20-ms bins are shown in A for the hold (green), cue (red), and track (blue) periods. All records are averages of 10 trials for the fastest 5-cm/s target speed. Solid sinusoidal tuning curves are shown for significant fits (R2 > 0.7 and Idir > period Idir 
1 SD), whereas dotted curves signify fits not satisfying both criteria. Data points from which the tuning curves were derived are superimposed. Shown below the sequence of binned tuning curves are the tuning curves and firing data averaged over the hold, cue, and track periods. The firing rate calibration bar applies to both binned and period tuning curves. The x-axis denotes the PD convention based on the direction of the moving target. In B, PD trajectories as a function of time are shown for averages based on the even (blue symbols) and odd trials (purple symbols) for the same neuron. The y-axis is time (the cue to track period sequence lasts 2 s for the 5-cm/s target speed), and the x-axis is the PD (ranging from 0 to 360°). The PD trajectories were referenced to the direction of the moving target (see METHODS). Therefore for this cell the PD trajectory pointed to 90° initially in the cue period and rotated clockwise to 270° at the start of the track period.
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FIG. 13.
Contour plots of the firing and PD trajectories for 4 neurons. The neurons are ordered in increasing difference between cue and track epoch based PDs (ranging from 33 to 123°). The x-axis is the trial sequence from cue to track (a total duration of 2 s, corresponding to a 10-cm target travel). The PD is mapped on the y-axis, ranging from 0 to 360°. The amplitude of firing relative to the hold period is coded by color (peak orange, minima purple). Significant preferred directions (by R2 and Idir criteria) calculated in 20-ms bins are marked by solid symbols. Confidence intervals (5-95%, based on the von Mises distribution) for the location of the PD are marked by smaller symbols on either side of the PD trajectory. All records are averages of 10 trials for the fastest 5-cm/s target speed.
, 1989a; Schwartz 1993). First, the criteria used to calculate the PD trajectory were more stringent than typically used for epoch-based determinations of a cell's PD (Caminiti et al. 1991; Fu et al. 1993; Georgopoulos et al. 1982; Schwartz 1992). In this report we required not only statistical significance (R2 > 0.7) but also a minimum depth of modulation. Therefore the directional tuning based on 20-ms bins is as rigorous and valid (if not more so) than the directional tuning defined over longer epochs. Second, as shown in Fig. 12, the individual tuning curves were nearly continuous and in complete agreement with the PD calculations. Third, the determinations based on odd and even trials yielded similar results. Over the 320 movement trials necessary to generate a complete data set in which the speed and direction of the trial were randomized, the similarity of the results from the odd and even trials reveals the reproducibility of the PD trajectory. Fourth, the fits based on the firing during the center hold period were invariably nonsignificant, demonstrating that the results from the cue and track period were not artifactual. Fifth, at least three reports from other investigators using steplike reaching tasks have documented similar rotations in the PD trajectory when calculated on a finer time scale (Baker et al. 1997; Mason et al. 1998; Scott and Kalaska 1996). Also, because these other reports were based on a steplike reach, the observed rotations in the PD trajectory were not simply a function of the moving targets employed in this paradigm.
33.3 ms per cm/s (F-ratio = 11.5, P < 0.001). Thus the detection of target directionality was delayed in the longer cue periods resulting from slower target speeds. Conversely, when the cue period was limited to 1 s by the 5-cm/s target, the onset of directional tuning occurred earlier. Directional tuning was maintained for a larger fraction of the trial duration as the target speed increased, resulting in a significant linear regression relationship (slope = 3.6% trial duration per cm/s, F-ratio = 15.3, P < 0.0001). Thus, when the cue period was limited by faster target speeds, directional tuning occurred 20% earlier and occupied 20% more of the time allotted before movement. These target speed-related changes in the onset and duration of directional tuning paralleled the changes seen in oculomotor behavior. As the cue period became longer, smooth pursuit was present for a smaller fraction of the cue period (Fig. 4).
View this table:
TABLE 1.
PD trajectory onset latency, duration, and rotational velocity as a function of target speed
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FIG. 14.
Temporal profiles of contiguously significant PD trajectories from 20 neurons. PD as a function of time throughout the trial sequence is shown in A for the fastest 5-cm/s and slowest 2-cm/s target speeds. Vertical line at time 0 denotes onset of the track period. The PD trajectories were rotated such that the track period PD trajectory was aligned with 0°. The distributions of the average PDs from the cue and track periods are shown in B using the convention of Figs. 9 and 10. Comparison of the PD trajectories from the 2- and 5-cm/s target speed trials is shown in C. The 2-cm/s speed trials were reduced to 100 bins, the same size as the 5-cm/s trials. Bins with significant directional tuning from the 2- and 5-cm/s trials were plotted as x-y pairs. The linear regression line and the 99% confidence intervals are shown. The R2 was 0.80. Axes are normalized as in A to 0 ± 180°.
). However, it should be stressed that the angular rotation of the cue period PD trajectories was not simply due to the eye movements because the saccadic eye movements in the earlier part of the cue covered the entire workspace (see Fig. 4). Furthermore, saccadic behavior was qualitatively similar during both the cue and track periods, yet the rotation of the PD trajectories occurred primarily in the cue period.
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FIG. 15.
Temporal profiles of the means ± SD for the PD trajectories of all 132 neurons with significant directional tuning in both the cue and track periods. The mean (central solid line) and ±SD (dotted lines) of the PD trajectories as a function of time through the trial sequence are shown for the fastest 5-cm/s (top) and slowest 2-cm/s (bottom) target speeds. Vertical line at time 0 denotes onset of the track period. PD trajectories were normalized by setting the average track period PD to 0°, the same convention used in Fig. 14. Thus the y-axes range from 0 ± 180°.
DISCUSSION
Abstract
Introduction
Methods
Results
Discussion
References
; Georgopoulos et al. 1982; Kalaska et al. 1983, 1989; Wise et al. 1992). Step movements first require detection of the onset and position of the target before a largely feed-forward and stereotyped movement is made. The movement is characterized by a bell-shaped tangential velocity profile, and there is little reliance on visual feedback until termination of the movement (see Georgopoulos 1986). In contrast, pursuit tracking requires continuous correction of error, resulting in a tangential velocity profile approximating that of the target. The duration of the tracking movements in this task was 1-2.5 s as opposed to 200-400 ms movement times typical of step movements over roughly equivalent distances (Fu et al. 1993; Georgopoulos et al. 1982; Kalaska et al. 1989; Ojakangas and Ebner 1992). Therefore in this task the observation time for neural and behavioral events was increased by a factor of 2-5. Because the directional tuning of the discharge occurred throughout the entire cue period for up to 2.5 s, more detailed observations on the temporal processing of visual information were possible. In addition, the pursuit tracking task allowed independent control of movement direction and speed. It should also be stressed that this task differs from "nonpursuit" tracking paradigms in which the animal is required to duplicate successively presented trajectory templates without a speed constraint (Schwartz 1992, 1993).
; Fu et al. 1993, 1995; Georgopoulos et al. 1982; Johnson et al. 1996b; Kalaska et al. 1983; Shen and Alexander 1997a,b). Second, a cell's PD during the cue period did not always point in the same direction of its PD during the track period. Over all cells, the mean cue period PDs differed significantly from those of the track period PDs, and approximately half of the sampled neurons had differences >45° between the PD of the cue and track periods. These differences in period PDs became more apparent when the cue and track periods were halved. The PDs obtained from the early cue period demonstrated a greater divergence relative to the tracking PDs than did the PDs from the later cue period. Thus a cell's PD was not constant across the trial. The third and somewhat unexpected finding was that sequential PDs calculated in 20-ms bins rotated from an initial direction in the cue period to align with the PD trajectory of the track period. During most of the track period, the PD trajectory was relatively constant. The global features of the PD trajectory, including its rotational velocity, varied little over different target speeds. Similar rotation in the PD trajectories of PMd neurons has been observed in an instructed delay reaching task (Mason et al. 1998). Furthermore, the detailed structure of the PD trajectory differed as a function of the trial sequence, revealing larger rotations and significantly higher rotational velocities in the cue relative to the track period. In the next section the implications of the PD trajectories in terms of coordinate systems, multiplexing of signals, visuomotor transformations, and population vector rotations are discussed.
; Johnson et al. 1996b; Weinrich et al. 1984). A similar gradient in which neurons encoding visuospatial aspects of movements are preferentially located in PMd and neurons encoding movement in MI has been described (Shen and Alexander 1997a,b). In this study the visuomotor properties of directional tuning exhibited a rostral-caudal gradient across PMd and MI. Directional tuning in the cue period was more prevalent in PMd than MI. Neurons with the greatest differences in their PDs between the cue and track periods were more common in PMd, and the difference decreased from PMd to MI. These findings are consistent with the hypothesized role for PMd in the mapping of complex visuomotor relationships (Boussaoud and Wise 1993; di Pellegrino and Wise 1993).
; Shen and Alexander 1997a,b; Zhang et al. 1997), and it is unlikely that these neurons encode this visuospatial information in joint space or muscle coordinates. Second, the PD trajectories were straightest in the track period when rotation of the joints and contraction of the muscles were occurring. One would anticipate that the PD trajectories would show the greatest rotations just before or in the track period if the neuronal discharge was encoded in a joint space coordinate frame.
; Shen and Alexander 1997a; Soechting and Flanders 1992). Recent evidence from single-unit recordings in the PMd and MI suggests that visuospatial information is processed first, possibly in an extrinsic coordinate frame, and that information about the actual limb movement is processed later, possibly in an intrinsic frame (di Pellegrino and Wise 1993; Shen and Alexander 1997a,b). The rotation of the PD in the cue period could reflect a gradual change in the coordinate frames in which the information is represented. The present findings are consistent with single neurons participating in such a process (Zhang et al. 1997), in addition to the participation of different neuronal populations (Lurito et al. 1991; Shen and Alexander 1997a,b).
; Scott and Kalaska 1995, 1997). In this task both target detection and speed identification are likely candidates, signaling the onset of the task and the onset of movement. Evidence for detection is the finding of transient neuronal discharge shortly after the visual cue presentation. This type of "signal" activity is well documented in the PMd (Crammond and Kalaska 1994; Johnson et al. 1996b; Wise et al. 1992), and several cells demonstrated this signal characteristic in this pursuit tracking paradigm. However, the transient nature of this firing is unlikely to account for the prolonged rotations in the PD trajectory. Preliminary evidence based on multiple regression analyses of speed and direction coding in these neurons suggests that speed is encoded jointly with direction during the cue period (Johnson et al. 1997). Therefore it is possible that the encoding of other parameters altered the directional tuning.
) and selective attention (di Pellegrino and Wise 1993). Eye movements followed a sequence through the trial of 1) initial randomly directed saccades, 2) saccades to target, 3) smooth pursuit of the cue target intermittently broken by randomly directed saccades, 4) smooth pursuit of the target during the initial half of the track period, and 5) saccades during the end of the track period. The eye movements were symmetrical in the cue and track periods. Selective attention would be expected to follow a similar symmetrical time course, initially directed over the entire workspace, then directed at the moving target, and finally drifting off at the end of the track period. However, the PD trajectories were not symmetrical, exhibiting substantial shifts in the PD during the cue period while the PD was relatively constant in the track period. Therefore oculomotor behavior and/or selective attention are unlikely to have contributed to the changes in the PD trajectory during the initial cue period. However, irrespective of the contributing factors, the net effect is to modify the directional tuning of these cells.
). The directional tuning of the discharge gradually constricted to align with the PD of the actual movement. This can be appreciated in the plot of the individual PD trajectories (Fig. 14) and in the plot of the standard deviation of the PD trajectories (Fig. 15). In either case, the directional tuning in the cue aligned within ±10° of the track PD over the cue-track transition. Over the extremes of target speeds, this convergence occurred from a period extending from 1 s before track onset until ~400 ms into the track period. Thus the convergence of the PD trajectories may provide an intrinsic "GO" signal. Another factor that may have contributed to the generation of the movement was the increased Idir found for the track period.
, Figs. 2 and 12 in Weinrich et al. (1984), and Figs. 1-4 in Shen and Alexander (1997b)]. The rotations in the PDs described in this report are completely consistent with these gradual directional changes in set-related activity.
).
; Fitts and Seeger 1953; Kornblum et al. 1990; Wise et al. 1996). One of the proposed roles of the PMd is the learning and computation of nonstandard sensorimotor transformations (Wise et al. 1996). A similar hypothesis has been advanced for the parietal cortex (Crammond and Kalaska 1994). Premovement firing in instructed delay tasks has been proposed to reflect the selection of an appropriate response relative to a stimulus (Crammond and Kalaska 1994; Wise et al. 1996). The prevalence of divergent cue and track PDs was greater for the PMd than for MI neurons. Consistent with the posited role for PMd in sensorimotor transformations, the differences in the PD in the cue and track periods may well reflect a neural substrate for such nonstandard mapping.
; Lurito et al. 1991). For an instructed redirection task, angular changes in the PD have been noted at a population level but have not been described for individual neurons (Lurito et al. 1991). The rotation of the PD trajectory in individual cells can be implicated as a mechanism underlying the rotation of the population vector. Similar rotational velocities for both the PD trajectory and population vector support this idea. Rotational velocities of 732 and 419°/s have been found for the rotations of the population vector for a 90° visuomotor transformation (Georgopoulos et al. 1989b; Lurito et al. 1991). Peak rotational velocity averaged over all cells was ~450°/s, with individual neurons having peak velocities as high as 1,100°/s (Table 1). The rotation of the PD trajectory in individual cells could also account for the relationship between the reaction time and the degree of rotation observed in psychophysical studies (Georgopoulos et al. 1989b; Lurito et al. 1991; Shepard and Cooper 1982). This monotonic relationship of reaction time and amount of rotation requires that the "mental" rotational velocity remain constant. The PD trajectory rotation fits this criterion, because it is constant relative to target speed and over marked differences in cue duration. Thus the rotations of PD trajectory in individual neurons may contribute to the rotation of the population vector (Georgopoulos et al. 1989b; Lurito et al. 1991).
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ACKNOWLEDGEMENTS |
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We thank M. McPhee for assistance with graphics and histology and J. Bailey and L. King for help with manuscript preparation. E. Ebner assisted in programming. Dr. Christopher Bingham was consulted on statistical methodology.
This work was supported by National Institutes of Health Grants 5R01-NS-31530 and a grant from the Human Frontier Science Program. M.T.V. Johnson was supported by T32-NS-07361 and J. D. Coltz by F31-MH-11430.
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FOOTNOTES |
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Address for reprint requests: T. J. Ebner, Dept. of Neurosurgery, University of Minnesota, Lions Research Building, 2001 Sixth St. SE, Minneapolis, MN 55455.
Received 10 April 1998; accepted in final form 31 August 1998.
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REFERENCES |
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Abstract
Introduction
Methods
Results
Discussion
References
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a model and taxonomy.
Psychol. Rev.
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