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The Journal of Neuroscience, March 1, 1999, 19(5):1782-1803
Cerebellar Purkinje Cell Simple Spike Discharge Encodes Movement
Velocity in Primates during Visuomotor Arm Tracking
J. D.
Coltz1,
M. T. V.
Johnson4, and
T. J.
Ebner1, 2, 3, 4
1 Graduate Program in Neuroscience and Departments of
2 Neuroscience, 3 Physiology, and
4 Neurosurgery, University of Minnesota, Minneapolis
Minnesota 55455
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ABSTRACT |
Pathophysiological, lesion, and electrophysiological studies
suggest that the cerebellar cortex is important for controlling the
direction and speed of movement. The relationship of cerebellar Purkinje cell discharge to the control of arm movement parameters, however, remains unclear. The goal of this study was to examine how
movement direction and speed and their interaction velocity modulate Purkinje cell simple spike discharge in an arm movement task in which
direction and speed were independently controlled. The simple spike
discharge of 154 Purkinje cells was recorded in two monkeys during the
performance of two visuomotor tasks that required the animals to track
targets that moved in one of eight directions and at one of four
speeds. Single-parameter regression analyses revealed that a large
proportion of cells had discharge modulation related to movement
direction and speed. Most cells with significant directional tuning,
however, were modulated at one speed, and most cells with speed-related
discharge were modulated along one direction; this suggested that the
patterns of simple spike discharge were not adequately described by
single-parameter models. Therefore, a regression surface was fitted to
the data, which showed that the discharge could be tuned to specific
direction-speed combinations (preferred velocities). The overall
variability in simple spike discharge was well described by the surface
model, and the velocities corresponding to maximal and minimal
discharge rates were distributed uniformly throughout the workspace.
Simple spike discharge therefore appears to integrate information about
both the direction and speed of arm movements, thereby encoding
movement velocity.
Key words:
cerebellum; simple spike; direction; speed; velocity; primate; arm; tracking
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INTRODUCTION |
The cerebellum's role in the
control of visually guided movements has been the subject of much
recent research (for review, see Stein and Glickstein, 1992 ; Ebner and
Fu, 1997 ). Humans with cerebellar pathology demonstrate poor
performance in measures of speed or velocity perception (Ivry and
Diener, 1991 ; Grill et al., 1994 ), hand-target mismatch in oculomanual
tracking (van Donkelaar and Lee, 1994 ), and inconsistent specification
of movement direction (Becker et al., 1991 ). Lesion and inactivation
experiments in animals support these observations, finding decreased
coordination of ocular and manual motor systems (Vercher and Gauthier,
1988 ) and increased error during hand tracking (Miall et al., 1987 ). Cerebellar lesions produce deficits in the control of movement speed or
velocity that include disruption of the normal bell-shaped velocity
profile (Holmes, 1939 ; Beppu et al., 1984 ; Miall et al., 1987 ; Hore et
al., 1991 ; Diener and Dichgans, 1992 ). These studies show that the
cerebellum plays an important role in the execution of visually guided
movements and suggest that cerebellar neurons may participate in the
specification of movement parameters such as direction, speed, and velocity.
Although the relationship of kinematic parameters to the discharge of
cerebellar neurons has been well characterized for eye tracking
movements (Suzuki and Keller, 1988 ; Stone and Lisberger, 1990 ; Shidara
et al., 1993 ; Krauzlis and Lisberger, 1994 ; Ohtsuka and Noda, 1995 ),
less is known with regard to reaching or tracking movements with the
arm (Ebner and Fu, 1997 ). Studies of Purkinje cell simple spike
discharge during ballistic wrist or arm movements have found
correlations with movement direction (Marple-Horvat and Stein, 1987 ;
Fortier et al., 1989 , 1993 ; Fu et al., 1997 ), distance (Fu et al.,
1997 ), target position (Fu et al., 1997 ), and velocity (Mano and
Yamamoto, 1980 ; Frysinger et al., 1984 ; Marple-Horvat and Stein, 1987 ).
Input elements to the intermediate cerebellum discharge phasically in
relation to arm movement direction and speed (van Kan et al., 1993b ),
and it has been hypothesized that the intermediate cerebellum generates
a velocity command signal (van Kan et al., 1993a ). Positron emission
tomography has shown that the ipsilateral cerebellum is activated in
relation to movement velocity during a visuomotor tracking task (Turner et al., 1998 ). In a recent study (Fu et al., 1997 ), simple spike discharge rate was correlated with movement direction, distance, and
target position; these parameters, however, accounted for only
one-third of the overall variability in simple spike rate. This finding
suggests that simple spike discharge may be correlated more strongly
with parameters other than those studied, such as speed or velocity.
The experiment described here correlated Purkinje cell simple spike
discharge in primates to movement direction and speed using two
visuomotor arm tracking tasks. Two main questions were addressed: (1)
What is the effect of movement direction and speed on simple spike
discharge before movement and during tracking? (2) To what extent are
direction-speed interactions (i.e., velocities) encoded in simple
spike discharge? It is shown that movement direction and speed are
important determinants of Purkinje cell simple spike discharge rate.
For a large number of cells, however, the simple spike discharge is
most strongly modulated at specific direction-speed combinations. That
is, when examined across the workspace, the discharge of these cells
was tuned to both movement direction and speed and therefore had a
preferred velocity.
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MATERIALS AND METHODS |
Tracking tasks. All experimental procedures were
conducted in accord with the National Institutes of Health Guide
for the Care and Use of Laboratory Animals. Two female rhesus
monkeys (Macaca mulatta, 4-6 kg) served as subjects in this
study. These were the same two animals (C and D) included in a study of
premotor and motor cortical discharge (Johnson et al., 1999 ). Each
animal used a two-joint manipulandum to make visually guided arm
tracking movements in the horizontal plane. The manipulandum controlled the position of a cross-hair cursor (0.8 cm diameter) that was displayed on a vertically positioned color monitor, located ~45 cm
from the animal's chest. Two tasks required the animal to track moving, square targets (1.44 cm2) that appeared on
the monitor. In the "bell" tracking task, the animal tracked
targets that moved with bell-shaped speed profiles (Fig.
1A,C). The animal first
superimposed and held the cursor [initial hold period (Hold1)] over a
centrally positioned start target (1.44 cm2) for a
randomized period (0.75-1.25 sec). The target then began to move in
one of eight equally spaced directions (0-315° in 45° intervals)
and at one of four speed profiles (peak speeds, 2, 3, 4, and 5 cm/sec). The animal was required to track the moving target,
maintaining the center of the cursor within the target's confines for
a distance of 5 cm. The speeds of the targets in this task were
generated using the equation for the normal curve: f(x) = (1/ 2 )
e (1/2)[(x µ)/ ]2.
The parameters µ and were adjusted such that the movement period,
or track period, had durations of 5.86, 4.54, 3.48, and 2.48 sec for
the peak target speeds of 2, 3, 4, and 5 cm/sec, respectively. A second
hold period (Hold2; 1-1.5 sec) followed the track period.

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Figure 1.
Tracking tasks. A, The bell
tracking task required the animals to track targets that moved with
bell-shaped speed profiles. The animal first superimposed a cross-hair
cursor over the central start target (Hold1); the target
then began to move in one of eight directions and at one of four speed
profiles. The animal tracked the target (Track) for a
distance of 5 cm to the end point (Hold2).
B, The constant speed tracking task required the animals
to track targets that moved at constant speeds. The animal first held
the cursor in the start target (Hold); a cue target
(Cue) then appeared 5 cm radial to the start target and
moved toward it at a constant speed. When the cue target intersected
the center hold target, the animal began to track the moving target
(Track) in the same direction and at the same speed as
the cue target for a distance of 5 cm. C, Schematic of
the target movement in the bell tracking task as a function of time and
period. First and second vertical dotted
lines mark the Hold1 period-Track period and Track
period-Hold2 period transitions, respectively. Height of dotted
lines indicates peak target speed. D, Schematic
of the target movement in the constant speed tracking task as a
function of time and period. Vertical dotted and
solid lines mark the Hold period-Cue period and Cue
period-Track period transitions, respectively. Height of
vertical lines indicates constant target speed.
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In the "constant speed" tracking task, the animal tracked targets
(1.44 cm2) that moved at constant speeds (Fig.
1B,D). A trial began when the animal positioned the
cursor in the central start target (1.44 cm2) for a
randomized interval (hold period; 0.75-1.25 sec). Then, a premovement
period (cue period) began during which the animal was required to
maintain the cursor's center in the start target. During the cue
period, another target (cue target) appeared at one of eight randomly
selected directions (0-315° in 45° intervals) and at a distance of
5 cm from the central start target. The cue target then moved toward
the start target at one of four constant speeds (2, 3, 4, and 5 cm/sec). The movement period (track period) began when the cue target
intersected and moved uninterrupted through the start target; the start
target was then extinguished, and the animal tracked the moving target
in the same direction and speed as the cue target for a distance of 5 cm. It should be emphasized that the movement of the cue target
signaled the direction and speed of the upcoming tracking movement.
This cue period has some similarities to the instructed delay periods
used in studies of dorsal premotor and primary motor cortex (Boussaoud and Wise, 1993 ; Crammond and Kalaska, 1994 ; Shen and Alexander, 1997 ).
For each target speed, the cue and track periods were equal in
duration: 2.5, 1.67, 1.25, and 1 sec for speeds of 2, 3, 4, and 5 cm/sec, respectively. No final hold period was required. In both tasks,
deviation of the center of the cursor from the start target or the
tracked target aborted the trial and started a new trial that was
randomized with respect to direction and speed. The dimensions and size
of the screen workspace and targets were identical to those of the
actual physical workspace. In addition, the animal could view its hand
and the manipulandum, but the tracking requirement of the task demanded
that the animal concentrate on the screen. Successful trials were
followed by a juice reward, and after an interval of 4-8 sec, a new
trial was initiated. Each of the 32 direction-speed combinations was
repeated 5-10 times, for a total of 160-320 trials per cell.
Surgery, electrophysiology, and histology. After a 6-9
month task training period, the animals underwent stereotaxic placement of a chronic stainless steel recording chamber (19 mm inner diameter) and implantation of a head fixation halo. The chambers were placed ipsilateral to the working arm, over right parietal cortex in animal C
and over left parietal cortex in D. Surgery was performed under aseptic
conditions and with full surgical anesthesia (ketamine, 20 mg · kg 1 · hr 1; and
xylazine, 1-2
mg · kg 1 · hr 1);
postoperative analgesics (buprenorphine, 0.05 mg/kg) and antibiotics (ampicillin, 250 mg · kg 1 · d 1) were administered.
After recovery, the simple and complex spike discharge of cerebellar
Purkinje cells was recorded extracellularly (Ojakangas and Ebner, 1992 )
using paralyene-coated tungsten microelectrodes (tip impedance, 6-10
M ). Signals were amplified, time-amplitude discriminated, and
converted to pulses before digitization and storage to computer at 1 kHz. These data were then compressed into bin widths of 20 msec and
averaged over the 5-10 movements for each direction-speed
combination. Because 160-320 movement trials were required for a
complete data set, the simple and complex spike discharge of each cell
was recorded only during the performance of one of the two tasks. Cells
were studied only if both simple and complex spikes were discriminable
and if discharge was task-related during active reaching or passive
manipulation of the shoulder, elbow, or wrist joints. The latter
included cutaneous stimuli delivered to the hand and wrist, arm and
elbow, and shoulder, as well as deeper somatosensory manipulation and
passive movements in different directions.
After completion of all cell recordings, electromyographic (EMG)
activity and eye position data were recorded in both animals during
performance of both tasks. The tracking movements of each animal were
determined by calculating the x and y positions
of the manipulandum from the output of two potentiometers placed at the
manipulandum's joints. The position data were sampled at 1 kHz and
drove the cursor in real time on the video monitor. Speed and velocity
were calculated by numerical differentiation of the position signal.
EMG activity was recorded from 10 different shoulder, elbow, and wrist
muscles [acromiodeltoid, spinodeltoid, latissimus dorsi, biceps (long
and short heads), triceps (long head), extensor carpi radialis and
ulnaris, and flexor carpi radialis and ulnaris] over several sessions,
using intramuscular, Teflon-coated wire electrodes. The EMG signals
were amplified, filtered (10-1000 Hz), sampled at 2 kHz, and digitally
rectified. Eye movements were recorded using an infrared oculometer
(Bouis Instruments). The vertical and horizontal eye position data were
sampled at 200 Hz and compressed into 20 msec bin widths. During both
the EMG and eye movement recordings, the animals made 5-10 movements at each of the direction-speed combinations for a total of 160-320 movements.
After all cell, muscle, and eye movement recordings, electrolytic
lesions were made, and pins were placed at selected recording sites and
chamber coordinates for histological analysis. The animals were given
an intraperitoneal injection of pentobarbital sodium (150 mg/kg),
exsanguinated, and perfused with saline containing heparin, followed by
Zamboni's fixative (4.3 gm of NaOH, 20 gm of paraformaldehyde, 18.8 gm
of NaH2PO4, and 150 ml of picric acid in
850 ml of H2O). After removal from the posterior fossa, the
cerebellum was post-fixed; at a later date, the cerebellum was
sectioned (50 µm) and stained with thionin to recover pin and
electrode tracks.
Data analysis. The neuronal data were aligned to the onset
of target movement in the bell tracking task and to the appearance of
the cue target in the constant speed task. One-way ANOVA was used to
compare the mean simple spike discharge rates across the initial hold,
track, and final hold periods in the bell tracking task and across the
hold, cue, and track periods in the constant speed task. Cells for
which the simple spike discharge was modulated significantly
(p < 0.05) were subject to further analysis. In addition, the latency of a significant change in simple spike discharge
for each task-modulated cell was determined. For the bell and constant
speed tasks, the latency was defined as the time at which the simple
spike discharge changed by ±3 SD from the mean discharge rate during
the hold period.
Two regression analyses were conducted (1) to determine the magnitude
and extent of linear relationships between simple spike discharge rate
and movement direction at each movement speed, and between discharge
and speed at each movement direction, and (2) to determine, using a
response surface approach, whether a model that allowed for linear as
well as nonlinear variation in simple spike discharge provided a better
description of this discharge in relation to movement direction, speed,
and their interaction, velocity. Both of these analyses were also
applied to the EMG data.
Before describing the regression analyses in detail, operational
definitions for speed and velocity are needed. As commonly defined,
speed is a scalar quantity that describes the rate of displacement
irrespective of direction. A neuron exhibiting "pure" speed
modulation would vary its discharge with speed regardless of the
direction of the movement. Velocity is a vector quantity that describes
the rate of displacement along a particular direction. A neuron
exhibiting pure velocity modulation would vary its discharge with both speed and direction.
Regression analyses were performed on the mean cell discharge rate
during the track period for the bell tracking task. For the constant
speed tracking task the regression analyses were performed using the
mean discharge during the cue and track periods separately. The first
analysis evaluated the linear relationships of simple spike discharge
rate to movement direction and speed by fitting the average simple
spike discharge rate (fi) at each target
movement direction ( ) to a cosine tuning model for each target speed
(Georgopoulos et al., 1982 ; Schwartz et al., 1988 ; Fu et al.,
1993 ):
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(1)
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This is expressed alternatively as
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(2)
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The peak of the cosine function corresponds to the direction in
which cell discharge rate was highest and is referred to as the
preferred direction (PD; PD in Eq. 2) of the cell
(Mardia, 1972 ; Georgopoulos et al., 1982 ; Fisher, 1993 ). The regression coefficients 0 and 1 (Eq. 2) represent
the mean discharge rate over all directions and the discharge
modulation as a function of direction, respectively; i
represents the statistical error. An index of the depth of cell
discharge modulation with direction
(Idir) was given as
Idir = 1/ 0
(Georgopoulos et al., 1982 ; Fu et al., 1993 ). The proportion of
variability in mean cell discharge rate accounted for by changes in
movement direction was given by the coefficient of determination
(R2); a statistically significant
relationship (p < 0.05) between discharge rate
and movement direction required an R2
value > 0.7 (Eq. 1).
The mean simple spike discharge rate (fi) for
each peak target speed (bell tracking task) or constant target speed (constant speed tracking task) was analyzed over each of the eight movement directions using a simple linear regression model:
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(3)
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Here, 1 represents the change in mean discharge
rate (spikes/sec per cm/sec) with unit increases in speed
(s) along a given direction. A statistically significant
relationship between speed and cell discharge rate required an
R2 value > 0.9 (p < 0.05). It needs to be stressed that the
results of this regression analysis can be interpreted as a linear
correlation with speed or velocity depending on whether the model
yields a significant fit along most directions (speed) or in limited
directions (velocity). A strict division between speed and velocity
here is difficult to define. In addition, this model assumes a
linear relationship between cell discharge and speed an
assumption that may or may not be correct (see Results).
As is shown in Results, the simple spike discharge of many Purkinje
cells was modulated most commonly by changes in direction at one speed
and by changes in speed along one direction. Furthermore, examination
of the discharge rates across the direction-speed space suggested that
reliance on a regression approach that did not allow for nonlinearity
in the response may not have captured some features of the simple spike
responses. The term "nonlinearity" is used here to describe
nonmonotonic relations to speed or direction. For example, a cell's
discharge could be highly modulated by a specific combination of
tracking direction and speed but not fit the single-parameter
regression models for direction (Eqs. 1, 2) or speed (Eq. 3). A model
was needed that accounted for variability in cell discharge over the
entire direction-speed space. Therefore, the second analysis used a
response surface methodology (Box and Draper, 1987 ) to assess the
linear, quadratic, and interaction effects of direction and speed on
simple spike discharge rate. The mean discharge rate at each level of
direction and speed was fitted to a quadratic polynomial model:
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(4)
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where [cos( PD)]i and
[cos( PD)]i2
represent the linear and quadratic predictors for movement direction, si and si2 are
the linear and quadratic predictors representing movement speed, and
[cos( PD) · s]i
denotes the direction-speed cross-product. This cross-product term is
related to velocity, that is, the linear interaction of direction and
speed. A statistically significant fit of this model to the data
required an R2 value > 0.33 (p < 0.05). Importantly, this response surface
approach enabled determination of the direction-speed combinations
(velocities) that resulted in both maximal and minimal discharge rates
(also see Khuri and Cornell, 1996 ). This technique was therefore
valuable in determining whether simple spike discharge was modulated
linearly and/or nonlinearly with direction and speed and was ultimately used to show whether simple spike discharge could be tuned to movement velocity.
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RESULTS |
Task-related kinematics
The movement trajectories produced by the animals were tightly
constrained by the tracking tasks and therefore highly stereotyped. The
average hand paths and speed profiles recorded during the track periods
of the bell and constant speed tasks are shown in Figure
2 for all movement directions and speeds.
It can be seen that the hand paths produced in both tasks are straight
and similar for each movement speed (Fig. 2A,B). In
addition, the speed profiles of the movements produced during the track
period in both tasks (Fig. 2C,D) closely follow the speed
profiles of the targets (Fig. 1C,D) and are similar for each
movement direction. In the bell tracking task, there were few
excursions in speed during the initial (Hold1) and final (Hold2) hold
periods. During the track period of the constant speed task, there was
often an early overshoot of the target, followed by an approximation to
the constant speed of the target. Therefore, the animals were able to
track the required speed profile within the accuracy constraints of the
task.

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Figure 2.
Hand paths and speed profiles. A,
B, Average hand paths from 10 movements at each
direction-speed combination (8 directions, 4 speeds) in the bell
(A) and constant speed (B)
tracking tasks. C, D, Average speed profiles from
movements at each direction-speed combination in the bell
(C) and constant speed
(D) tracking tasks. Hand paths and speed profiles
were recorded from animals D (A, C) and C (B,
D). Conventions are as in Figure 1.
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Neuronal database
Cerebellar Purkinje cell simple and complex spike discharge was
recorded in 154 cells in two monkeys (C and D) during the performance
of one of two tracking tasks (bell and constant speed tracking).
Because of the large number of trial repetitions required to study the
32 direction-speed movement combinations, a single Purkinje cell was
studied in only one of the two tasks. In monkey C, 14 Purkinje cells
were recorded during the bell tracking task, and 58 were recorded
during the constant speed tracking task. In monkey D, 50 Purkinje cells
were recorded during the bell tracking task, and 32 were recorded
during the constant speed tracking task. This paper focuses on the
relationship of the simple spike discharge to movement kinematics;
analysis of the complex spike discharge is the subject of a future
report. Of the 64 cells recorded in the bell tracking task, 53 (82.8%)
had task-related simple spike discharge (ANOVA, p < 0.05) including 13 of 14 cells recorded in animal C and 40 of 50 in
animal D. Of the 90 cells recorded in the constant speed task 79 (87.8%) had task-related discharge (50 of 58 cells in C and 29 of 32 cells in D). The remainder of the analysis focused on these 132 task-related cells (see Table 1 for a
complete summary of task- and parameter-related discharge).
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Table 1.
Summary of simple spike discharge modulation by task, task
period, model, movement parameter encoded, and depth of modulation
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The latencies at which a significant change in simple spike discharge
occurred (exceeded ±3 SD of mean discharge rate during hold period)
were calculated across all movement speeds for both the bell and
constant speed tasks. In the constant speed task, significant increases
occurred 52 ± 576 (mean ± SD) msec before the onset of the
track period. In the bell task, the mean latencies occurred well after
movement onset but before the peak of the bell-shaped speed profile by
104 ± 813 (mean ± SD) msec. The latencies of discharge
modulation in the bell task would be expected to be delayed because of
both the absence of a cue period and the very slow tracking speed at
the onset of the track period. Therefore, significant changes in cell
discharge are strongly coupled to arm tracking.
All cells were tested for responses to peripheral stimulation by
somatosensory testing and palpation and by passive movement of the arm,
as well as for discharge modulation in response to active reaching. Of
the 132 task-related Purkinje cells, the discharge of 41 (31.1%) was
related to passive manipulation of the shoulder only; 4 cells (3.0%)
were related to the forearm-elbow area only, and 5 cells (3.8%) were
modulated solely by palpation of the hand-wrist area. Thirty-two cells
(24.2%) had discharge that was modulated in response to a combination
of shoulder, wrist, and elbow manipulation. A large number of cells
(64, 48.5%) had discharge that was modulated in response to both
passive manipulation and active reaching; the discharge of 50 cells
(37.9%) was related to active reaching only.
Direction- and speed-related simple spike discharge modulation
The simple spike discharge of the 53 task-related cells recorded
during bell tracking and that of the 79 task-related cells recorded
during constant speed tracking was evaluated for direction- and
speed-related discharge modulation using linear regression analysis
(Eqs. 1-3). Qualitatively, cells recorded during performance of the
bell tracking task often had a temporal discharge profile that
resembled the bell-shaped speed profile of the movement, particularly
at the higher speeds. An example of a cell recorded during performance
of the bell tracking task is shown in Figure 3A. This cell's discharge was
modulated by passive manipulation of the shoulder. Overall, during the
initial hold period, the tonic discharge rate was constant; at the
beginning of the track period the discharge rate increased and reached
a maximum value approximately midway through the track period. The
discharge rate then decreased to baseline value during the final hold
period. Mean simple spike discharge rates during the track period for each of the eight directions and four speeds are shown in Figure 3B. This cell was significantly tuned to movement direction
at speeds of 4 and 5 cm/sec. The PDs at each of these speeds were 242 and 236°; the depths of directional modulation
(Idir) were 0.20 and 0.17, and the
proportions of variability (R2) accounted
for by direction were 0.94 and 0.95, respectively. The discharge rate
of this cell was also significantly modulated with movement speed, such
that increases in speed were accompanied by increases in
discharge rate for movements to the target at 315°
(R2 = 0.91; 1 = 2.66).
Therefore, both direction and speed modulated this cell's simple spike
discharge.

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Figure 3.
Cell discharge during the track period in the bell
tracking task. A, Each plot shows average Purkinje cell
simple spike discharge (top) from 10 movements at the
direction-speed combination indicated. Also shown are the
corresponding x (solid lines) and
y (dashed lines) position
(middle) and speed (bottom, solid lines).
Discharge ranges 0-100 spikes/sec. Position and speed span 5 to 5 cm
and 0-6 cm/sec, respectively. Discharge was recorded from animal C. B, Scatterplots of average simple spike discharge during
the track period as a function of movement direction
(left) and speed (right). Significant
directional tuning (R2 > 0.7) was
found at speeds of 4 and 5 cm/sec; significant speed-related modulation
was found for movements along 315°. Filled circles
denote discharge rates with statistically significant relations to
direction and speed.
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An example of a Purkinje cell for which the simple spike discharge was
significantly modulated during the track period of the constant speed
task is shown in Figure
4A. This cell's
discharge was modulated by passive manipulation of the shoulder and
elbow. During the cue period, the discharge rate was constant and not significantly modulated with direction or speed (Fig. 4B,
left). A substantial increase in discharge rate occurred during
the track period. Qualitatively, the simple spike discharge profile
strongly resembled the hand speed profiles: a rapid increase in
discharge rate occurred and was followed by a period of maintained
discharge. During the track period, the discharge of this cell was not
significantly tuned to movement direction at any of the four speeds
(Fig. 4B, right). The discharge was, however,
significantly modulated with movement speed at six of the eight
movement directions (0, 45, 90, 180, 270, and 315°). The
R2 values for speed at each of these
directions were 0.97, 0.99, 0.96, 0.93, 0.90, and 0.97, and the values
of 1 were 10.6, 11.0, 9.7, 6.1, 9.9, and 10.8, respectively. Therefore, this cell's simple spike discharge can be
characterized as being modulated predominantly by speed, irrespective
of direction.

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Figure 4.
Cell discharge during the track period in the
constant speed tracking task. A, Conventions are as in
Figure 3. Speed spans 0-7 cm/sec. Discharge rate ranges 0-190
spikes/sec; recorded from animal D. B, Scatterplots of
average simple spike discharge during the cue (left) and
track (right) periods as a function of movement
direction (top) and speed (bottom). No
significant directional tuning was found in either the cue or track
period; significant speed-related modulation was found only during the
track period for movements along 0, 45, 90, 180, 270, and 315°.
Filled circles denote discharge rates with statistically
significant relations to speed. See Results for details.
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Some cells recorded during performance of the constant speed task were
modulated with direction and speed during the premovement cue period as
well as during the track period; an example of the discharge of such a
cell is shown in Figure 5A.
The simple spike discharge of this cell was modulated by passive
manipulation of the shoulder joint. For all movement speeds, simple
spike discharge rate increased toward the end of the cue period, before
the beginning of the track period. During the cue period (Fig.
5B, left), significant discharge modulation with movement
direction was limited to the speed of 4 cm/sec (PD = 278°;
Idir = 0.17; R2 = 0.86). Significant modulation with speed occurred for movements to the
target at 225° (R2 = 0.93;
1 = 1.01). During the track period (Fig. 5B,
right), the simple spike discharge rate was tuned to direction for
movements at speeds of 4 and 5 cm/sec (PD = 288 and 284°;
Idir = 0.17 and 0.20;
R2 = 0.77 and 0.84, respectively) and to
speed for movements along 225, 270, and 315°
(R2 = 0.94, 0.98, and 0.98;
1 = 5.58, 6.57, and 6.08, respectively). Therefore,
although this cell exhibited some significant discharge modulation in
the cue period, the extent and degree of this modulation was much more
prominent in the track period. Furthermore, during both the cue and
track periods, and for directions ranging from 225 to 315°, this
cell's simple spike discharge was modulated by a combination of
direction and speed, that is, velocity.

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Figure 5.
Cell discharge during the cue and track periods in
the constant speed tracking task. A, B, Conventions are
as in Figures 3 and 4. Example of a cell with statistically significant
directional tuning (4 cm/sec) and speed-related modulation (225°)
during the cue period is shown. Discharge was also related to movement
direction (4 and 5 cm/sec) and speed (225, 270, and 315°) during the
track period. Simple spike discharge (A) spans
0-160 spikes/sec.
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Thirty-one of the 53 cells (58.5%) with significant simple spike
discharge modulation in the bell tracking task were modulated with
changes in movement direction during the track period (Table 1B). The distribution of directional tuning for the
bell task at each movement speed is given in Figure
6A. These spoke plots indicate the PDs of the discharge, as well as
R2 and Idir
values, for each cell. The number of cells with statistically significant directional tuning (R2 > 0.7) is given in the center of each plot. The extent of directional tuning was distributed almost equally across speeds. The length of the
spokes projecting inward from the center reference line gives the
R2 value from 0.7 to 1.0 (dotted
line, R2 = 0.9); the length of each
spoke projecting outward gives Idir for values
>0 (dotted line, Idir = 0.3). The
"total" plot shows PDs and R2 and
Idir values from all four peak speeds, as well
as an overlaid density plot, the magnitude of which indicates the
concentration of PDs within a given region. The number given in the
center of the total plot is not the sum of the PDs for each of the
speeds but, rather, the total number of cells with significant
directional tuning, because some cells had direction-related discharge
at more than one speed. For the bell tracking task the distribution of
PDs was uniform (Rayleigh test, p = 0.37).

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Figure 6.
Summary of movement direction-related cell
discharge at each movement speed. A-C, Distribution of
PDs and R2 and
Idir values for all cells with significant
direction-related discharge in the track period of the bell tracking
task (A) and in the cue (B)
and track (C) periods in the constant speed
tracking task. Numbers of cells with statistically
significant directional tuning (R2 > 0.7) at each speed are given in the center of each plot.
Each radially directed spoke indicates PD,
R2, and
Idir. Length of spokes
projecting inward from center reference line gives
R2 from 0.7 to 1.0 (dotted
line at 0.9); length of spokes projecting
outward gives Idir for values >0
(dotted line at 0.3). Total plots show
PDs, and R2, and
Idir values for all four peak and constant
speeds, with superimposed density estimates. Numbers in
centers of Total plots indicate the
numbers of cells with statistically significant directional tuning for
all speeds. D-F, Total numbers of cells with
direction-related discharge at each movement speed.
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In the constant speed task, the discharge of nearly one-half of the
cells (39 of 79, 49.4%) with significant task-related modulation was
tuned to movement direction during the cue period (Table
1B, Fig. 6B). The distribution of
cue period PDs taken from the total plot was uniform (Rayleigh test,
p = 0.48). During the track period (Fig.
6C), the discharge of more than two-thirds of the cells (54 of 79, 68.4%) with significant task-related modulation in the constant
speed task was modulated with changes in movement direction. Simple
spike discharge could be directionally tuned at any of the movement
speeds. In addition, a large cluster of PDs at ~270° (movements
toward the animal's body) can be seen for each of the four speeds; it
is best seen in the total plot. A smaller cluster of PDs is apparent at
~90°, that is, for movements away from the animal's body. Fewer
cells had PDs to the left (~180°) and right (~0°) for the track
period of the constant speed task. The null hypothesis of uniformity of
PDs was tested under the assumption of a bimodal PD distribution; the
distribution was judged to be nonuniform [equal spacings test (Mardia,
1972 ), p < 0.05]. This nonuniform distribution of
PDs, such that they tended to cluster in directions corresponding to
movements toward and away from the body, is similar to that found
previously (Fortier et al., 1989 ; Fu et al., 1997 ) for cerebellar
cortical cells. Therefore, the distribution of preferred directions was
nonuniform for the track period of the constant speed task.
Figure 6 reveals one important characteristic of this directional
tuning. For both bell (Fig. 6D) and constant speed
(Fig. 6E,F) tracking, significant directional
tuning occurred most commonly at only one speed. This finding suggests
that interactions between direction and speed may be an important
determinant of Purkinje cell simple spike discharge. This result is
similar to that of a previous study of Purkinje cell discharge (Fu et
al., 1997 ), in that significant directional tuning usually occurred at
only one movement distance.
In addition to directional tuning, the simple spike discharge of these
cells displayed statistically significant speed-related modulation in
both movement tasks. Thirty of the 53 cells (56.6%) in the bell
tracking task either increased or decreased discharge rate with speed
(Table 1B). Shown in Figure
7A is a spoke plot of the
distribution of positive and negative regression slopes for speed
( 1), obtained from fitting Equation 3. Because
six cells were modulated with speed at more than one movement
direction, the total number of spokes (n = 39) exceeds
the total number of cells with speed relations (n = 30). A slightly greater number of these speed slopes were positive
(n = 22) than negative (n = 17), and
there was a tendency for a greater number of speed relationships to
occur in the quadrant spanning 135-225°. Cells with significant
relationships to speed in this task were modulated most commonly in
only one movement direction (Fig. 7D). Twenty-four cells
were modulated with speed along one direction; six cells had
relationships to speed at two to four directions, and no cells were
modulated with speed at five or more directions.

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Figure 7.
Summary of movement speed-related discharge along
each direction. A-C, Distribution of positive and
negative speed slopes ( 1 values; Eq. 3) and
R2 values for cells with significant
speed-related modulation (R2 > 0.9)
in the track period of the bell tracking task (A)
and in the cue (B) and track
(C) periods of the constant speed tracking task.
Spokes projecting from the inner octagon
indicate 1 values; inward-directed spokes
indicate negative values from 14 (inner dotted line)
to 0; outward-directed spokes indicate positive
1 values, ranging from 0 to 14 (outer dotted
line). Spokes projecting from the outer
octagon indicate R2 values,
spanning 0.9 to 1.0. Height of outer histogram blocks gives proportion
of cells with speed-related modulation in the given hemiquadrant.
Numbers of cells with statistically significant
speed-related discharge modulation are given in the
center of each plot. D-F, Number of
cells with speed-related modulation at one or more directions during
the track period of the bell task (D) and in the
cue (E) and track (F)
periods of the constant speed task.
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In the constant speed task, the simple spike discharge of 34 cells (34 of 79, 43.0%) was modulated with movement speed during the cue period
(Table 1B, Fig. 7B). As in the bell
tracking task, a slightly greater number of speed slopes were positive
(n = 29) than negative (n = 20). Here,
there was a tendency for a greater number of significant speed
regressions to occur in the quadrant spanning 45-135°. In addition,
most cells were modulated with speed along only one direction (Fig.
7E; n = 24). Ten cells had speed
relationships at two to four directions, and no cells were related to
speed along five or more directions. In the track period, the discharge
of 47 cells (47 of 79, 59.5%) was significantly modulated with
movement speed (Fig. 7C). Forty-six of the regression slopes
were positive; 31 were negative. The distribution of these significant
regressions in the track period was more uniform than that for the cue
period. Again, simple spike discharge was modulated most commonly in
one direction (Fig. 7F; n = 29); 18 cells
had speed relations along two to six directions.
Simple spike modulation in the cue and track periods in the
constant speed task
As was shown in Figures 6 and 7, more cells had direction- and
speed-related discharge modulation in the track period (direction, n = 54; speed, n = 47) than in the cue
period (direction, n = 39; speed, n = 34) during constant speed tracking. Furthermore, the depths of
modulation for movement direction (Idir)
and the absolute values of the slopes for movement speed
( 1) were, on average, greater during the track
period than during the cue period (Table 1C). The means of
Idir were significantly different
(t = 2.72; p = 0.007), and there was a
trend toward a greater mean 1 during the track period
(t = 1.74; p = 0.08). What about cells that were directionally tuned at the same speed or speed-related for
movements along the same direction in both the cue and track periods?
Twenty of the 79 task-modulated cells were directionally tuned for
movements at the same speed in both the cue and track periods. For this
group of 20 cells, more cells had a greater depth of modulation
(Idir) in the track period than in the
cue period, and the average depth of modulation was greater in the track period (Table 1D; t = 4.29;
p = 0.0003). Only six of the 79 task-related cells had
speed-related modulation for movements in the same direction during
both the cue and track periods. In five of six cells the magnitudes of
the absolute values of the slopes ( 1; Eq. 3) were
greater during the track period, but the mean absolute values of these
slopes for the track and cue periods were similar (Table
1E). Therefore, across the cue and track periods, a
minority of cells were directionally tuned for movements at the same
speed, or speed-related for movements in the same direction, based on
the simple linear models (Eqs. 1-3). More cells had a greater depth of
modulation, and the average depth of modulation was increased for
simple spike discharge recorded during the track period compared with
the cue period.
Coincidence of directional tuning and speed-related modulation
As stated previously, the discharge of some cells was both tuned
to movement direction and modulated with movement speed (Eqs. 1-3). In
the track period of the bell task and in the cue and track periods of
the constant speed task, 15 of 53, 16 of 79, and 31 of 79 cells,
respectively, had statistically significant relationships to both
parameters based on the simple linear models (Eqs. 1-3). This
observation raises the question of whether the direction- and
speed-related modulation was coupled and, if so, whether the discharge
of the cells might be related to movement velocity. Velocity encoding
predicts that speed modulation would occur preferentially along a
cell's preferred direction. In Figure
8A-C, the distribution of directions along which speed-related modulation was found is shown
after rotation of the PDs of each of the cells to 0°. Overall, a
given Purkinje cell tended to have positive speed-related modulation (filled circles) in the same hemisphere as its PD.
Conversely, negative speed modulation (open circles)
occurred primarily in the opposite hemisphere. Over the population, the
cell discharge was greater for increasing speed along or near the PD
and linearly decreased for directions opposite to the PD. That is, cell
discharge increased with movement (or target) speed increases along or
near the direction along which cell discharge was highest. A similar finding was described for direction-speed modulation in the discharge of primary motor cortical cells (Schwartz, 1992 ). This coincidence of
direction- and speed-related modulation provides further evidence that
interactions between direction and speed (i.e., velocity) may be an
important determinant of simple spike discharge.

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Figure 8.
Cells with both directionally tuned and
speed-related discharge. Polar plots indicate the
coincidence of direction- and speed-related modulation in the track
period of the bell task (A) and in the cue
(B) and track (C) periods
of the constant speed task. Circles around plot
peripheries indicate directions along which cells had speed-related
discharge after rotation of cells' PDs to 0°. Filled
circles indicate positive speed slopes
( 1 > 0; Eq. 3); open
circles indicate negative speed slopes
( 1 < 0). Rose plots
indicate numbers of positive (filled) and
negative (open) speed slopes in each hemiquadrant
(dotted line, n = 11). Density
estimates show relative concentration of positive speed modulation in a
given directional region. Cells tended to have positive speed-related
modulation in the same hemisphere as the PD and negative speed-related
modulation in the opposite hemisphere.
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Response surface modeling of simple spike discharge
The findings presented in Figure 8 suggest that the simple spike
discharge of some Purkinje cells is modulated by movement velocity.
Most of the cells whose discharge was significantly tuned to movement
direction, however, were modulated at only one speed (Fig. 6), and most
cells with speed-related discharge were modulated along only one
direction (Fig. 7). This finding suggested that the patterns of simple
spike discharge observed across the direction-speed space may not have
been described adequately by relatively simple linear models (Eqs.
1-3). Therefore, a response surface modeling approach was used in
which the mean simple spike discharge rates for each period of interest
were evaluated over all 32 direction-speed combinations. Two
advantages of this approach are (1) it can capture any nonlinearities
in discharge rate over the direction-speed space, and (2) perhaps more
importantly, it can be used to identify the direction-speed
combinations corresponding to the maximal (and minimal) simple spike
discharge rates; that is, it can be used to identify a cell's
preferred velocity.
Figure 9 shows the results of this
response surface modeling for four different Purkinje cells, comparing
the actual discharge with the predicted discharge for the 32 direction-speed combinations. The discharge pattern of a cell recorded
during the bell task, and with no significant direction- or
speed-related discharge according to the single-parameter analyses
(Eqs. 1-3), is shown in polar form in Figure 9A. The
directional discharge pattern of this cell was bimodal, such that
maximal discharge occurred for movements along 0° and at speeds of
~4-5 cm/sec, with another, slightly lower peak at 180°, also at
4-5 cm/sec. This second maximum contributed to the inability of the
single-parameter models to fit the discharge. The majority of the
overall variability in this cell's discharge was accounted for by
direction and speed in the response surface model
(R2 = 0.74). The plot of the predicted
surface (Fig. 9B) captures the essential feature seen in the
raw data plot, that is, the bimodal distribution of discharge rates,
with a separation of ~180°. This cell's preferred velocity
(maximal discharge on the fitted surface) occurred at direction 23°
and speed 3.8 cm/sec. Minimal discharge on the fitted surface was found
for the velocity 270°, 2.1 cm/sec. Therefore, this cell's simple
spike discharge was not linearly related to direction or speed but
instead was modulated at a direction-speed combination.

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Figure 9.
Actual and predicted simple spike discharge from
fitting the response surface model. A-J, Color polar
contour plots of actual simple spike discharge rates
(left) and predicted discharge rates
(right) for five Purkinje cells as a function of
direction and speed. Speed is indicated on the radius
arm. For the actual discharge plots (A, C, E, G,
I) the average discharge is plotted for each of the 32 direction-speed combinations. The continuous surface was generated
using bicubic interpolation of the 32 points. The plots of predicted
discharge (B, D, F, H, J) were plotted using the
predicted surfaces from the polynomial model.
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The simple spike discharge of some cells could be tuned to velocity in
the premovement cue period. The actual and predicted discharge rates of
a cell recorded during the cue period in the constant speed task are
shown in Figure 9, C and D, respectively. Qualitatively, this cell had an area of peak discharge in the hemiquadrant spanning 135-180° and at speeds of 2-4 cm/sec. The discharge of this cell was not tuned to target direction at any of the
four speeds and was not modulated with speed along any direction using
the single-parameter regression models. This cell's discharge was,
however, well described by the response surface model
(R2 = 0.69). The preferred velocity
occurred at 135° and 2.9 cm/sec; the minimum discharge rate on the
surface was located at 305° and 4.9 cm/sec. The simple spike
discharge of a different cell recorded during the track period of the
constant speed task is shown in Figure 9E. Like the cells
shown in Figure 9, A and C, the discharge of this
cell was not found to be modulated with direction or speed in the
single-parameter analyses (Eqs. 1-3). Similar to the discharge pattern
shown in Figure 9A, this cell's discharge was distributed
in a bimodal manner across the workspace, with peak rates for movements
along 135° and 4-5 cm/sec. A second peak occurred at 315°. The
fitted model captured almost 80% of the variability in the discharge
pattern (R2 = 0.79); the predicted values
are shown in Figure 9F. The preferred velocity was at
coordinates 154° and 4.1 cm/sec; the minimum on the surface was at
275° and 2.2 cm/sec.
Some cells had similar patterns of simple spike discharge during both
the cue and track periods; the discharge of such a cell is shown in
Figure 9, G (cue) and I (track). Like the actual
discharge patterns of the cells shown in Figure 9, A and
C, this cell had a nonlinear relationship to speed, with
peak discharge at a speed of ~4 cm/sec for both the cue and track
periods. Direction-related discharge was also highly similar for the
cue and track periods; maximal discharge occurred in the 315 to
0° hemiquadrant. The fitted surfaces (Fig.
9H,J) strongly resemble the actual discharge profiles, reflecting the large proportions of variability in simple spike discharge rate accounted for by the surface model (cue
R2 = 0.62; track
R2 = 0.86). The preferred velocities on
the fitted surfaces were 352° and 3.9 cm/sec for the cue period and
321° and 4.1 cm/sec for the track period. Therefore, the preferred
velocity of this cell's discharge was very similar for both the cue
and track periods.
Some cells, such as those shown in Figure 9, A and
E, appeared to have bimodal discharge patterns, including a
velocity corresponding to maximal discharge the preferred velocity as
well as a second velocity at which the discharge rate was less than the
maximum. The cells that significantly fitted the surface model were
examined for this characteristic using arbitrarily set criteria. A
cell's discharge pattern was considered bimodal if (1) the discharge rate at the second velocity exceeded the midpoint between the mean and
maximum discharge rates, and (2) the second velocity was located
>90° from the preferred velocity. In the bell tracking task, 3 of 25 cells (12%) were bimodal; in the cue and track periods of the constant
speed task, 7 of 39 cells (18%) and 9 of 67 cells (13%),
respectively, were bimodal. Therefore, across both tasks, ~85% of
the cells with significant fits to the surface model had unique
preferred velocities.
Direction and speed, in the context of the response surface model,
accounted for a significant proportion of the variability in simple
spike discharge rate in a large number of cells. The distribution of
cells with statistically significant fits to this model is shown in
Figure 10. The actual velocities
corresponding to the maximum (filled circles) and
minimum (open circles) discharge rates from fitting the
response surface model are shown in Figure 10A-C;
these velocities appear to be distributed uniformly throughout the
direction-speed space. In Figure 10D-F, these
maxima and minima are shown after rotation of the maximum discharge
rate predicted by the surface model to the PD of the cell (Eq. 1, using
data from all 32 direction-speed combinations) and alignment to 0°. It can be seen that the maximum velocities coincide with the PDs and
that the minimum velocities are clustered in the opposite half of the
workspace. Twenty-five of 53 task-related cells (47.2%) in the bell
tracking task had significant fits to the surface model (Fig.
10A,D), and the average
R2 value was 0.59 ± 0.15 (mean ± SD). After rotation to 0°, these preferred velocities occurred in
a relatively well defined area, spanning 330-35° (mean = 2.91°; SD = 12.79°) and were distributed uniformly in the
speed range of 2-5 cm/sec. The minimal discharge rates occurred in the
opposite quadrant and were clustered along 180°. This latter finding
resembles what was observed for the interaction between direction and
speed shown in Figure 8, using the linear models.

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Figure 10.
Summary of movement velocity encoding in simple
spike discharge. A-C, Velocities at which maximal
(filled circles) and minimal (open
circles) discharge rates were found for all cells with
significant fits to the surface model during the track period of the
bell tracking task (A) and in the cue
(B) and track (C) periods
of the constant speed task. Dotted lines indicate speeds
of 2, 3, 4, and 5 cm/sec from the center. D-F,
Velocities corresponding to maximal and minimal discharge rates after
rotation of maximal velocities to the PD of the cell. Conventions are
as in A-C.
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In the constant speed task, 39 of 79 cells (49.4%) in the cue period
(Fig. 10B,E) and 67 of 79 cells (84.8%) in the track
period (Fig. 10C,F) significantly fitted the surface
model. Average R2 values for the cue and
track periods were 0.56 ± 0.13 and 0.62 ± 0.16 (mean ± SD), respectively. Similar to the results for the bell tracking
task, after rotation to 0°, the preferred velocities for both the cue
and track periods of the constant speed task were distributed
throughout the quadrant centered at 0° (cue period: mean = 2.57°; SD = 23.42°; track period: mean = 0.76°; SD = 16.05°), and predicted discharge rates were at a minimum at
~180°. These maximum and minimum velocities were distributed
uniformly along the speed axis.
The proportions of variability in simple spike rate were also
calculated for the linear ([cos( PD)],
(s)), quadratic ([cos( PD)]2, (s)2),
and cross-product ([cos( PD)] · (s)) predictors in the surface model. In the bell task, and
in the cue and track periods of the constant speed task, the linear
terms accounted for ~40% of the total proportion of variability
explained (Table 1G). On average, the quadratic terms
accounted for more of the variability in discharge rate than the linear
components. The cross-product term explained the least percentage of
the variability in discharge. The higher overall contribution of the
quadratic terms indicates that the relationship of simple spike
discharge rate to direction and speed was often nonlinear.
Recording sites and spatial properties of the discharge
The recording areas and surface electrode penetration sites are
shown relative to a dorsal view of the cerebellar cortex in Figure
11A. In both animals,
the anteroposterior loci of the recordings were near the primary
fissure; in animal C (right), the recordings were centered
~10 mm to the right of the midline, and in animal D
(left), they were centered 13 mm to the left of the midline. Most recordings were either anterior to the primary fissure in lobule V
or posterior in lobule VI, extending mediolaterally from the
intermediate region well into the hemisphere (HV and HVI). Some cells
(animal D) were located in lobule IV.

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Figure 11.
Recording sites. A, Regions and
penetration coordinates for the recordings in animal D (left cerebellar
hemisphere) and animal C (right hemisphere). PF, Primary
fissure. B, C, Expanded view of the
recording locations from animals D and C, respectively. At each
recording site the color of the circle
indicates whether a cell's discharge responded to passive manipulation
of the hand and wrist (red), arm and elbow
(green), or shoulder (blue).
Black dots indicate that the cell responded to active
movements but not passive manipulations. In some penetration tracks
more than one Purkinje cell was recorded.
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In both animals, the distribution of recording sites relative to the
dorsal surface of the cerebellum was examined for spatial differences
with respect to the locus of sensitivity to peripheral stimulation
(shoulder vs elbow vs wrist). The electrode penetrations illustrated in
Figure 11A are expanded in Figure 11, B
and C, indicating whether the cell(s) recorded in a given
track were sensitive to shoulder (red), elbow
(green), or wrist (blue) stimulation or to
a combination thereof. Hotelling's two-sample tests (Batschelet, 1981 )
with corrections for multiple comparisons (p < 0.05) showed no spatial differences in sensitivity in animals D (Fig.
11B) and C (Fig. 11C).
These distributions of recording sites in animals D and C were also
tested for spatial differences with respect to (1) correlations of
simple spike discharge to movement direction versus speed (Eqs. 1, 3),
(2) statistically significant simple spike discharge modulation during
the cue versus track periods in the constant speed task, (3) the
preferred directions of cells with significant directional tuning, and
(4) the preferred velocities of cells whose discharge significantly
fitted the surface model. Characteristics 1 and 2 above were
tested using Hotelling's two-sample tests; 3 and 4 were examined using
a modified sign test (Mardia, 1972 ). No spatial differences were found
among any of these measures (p < 0.05),
providing evidence that the simple spike discharge modulation described
here may relate more strongly to movement parameters than to muscle groups.
Task-related eye movements and muscle activity
Eye movements and muscle activity were recorded in both animals
during the performance of both movement tasks in experimental sessions
in which Purkinje cell discharge was not recorded. Single-trial records
of eye movements obtained during bell and constant speed tracking are
shown in Figure 12, A and
B, respectively. In Figure 12A, the eye
x and y positions from five movement trials are
illustrated as a function of time for the four peak speeds (2, 3, 4, and 5 cm/sec) and for four of the eight movement directions (0, 90, 180, and 270°). Although saccadic eye movements were predominant during the initial and final hold periods, smooth pursuit movements occurred throughout much of the track period. At the highest peak speed
(5 cm/sec), smooth pursuit eye movements were observed almost exclusively; at lower speeds (2, 3, and 4 cm/sec), the smooth pursuit
movements during the track period were occasionally interrupted by
periods of saccades, particularly as the animal approached the movement
end points.

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Figure 12.
Task-related eye movements. A,
Single-trial records of x and y eye
positions in time during bell tracking at each of the four peak speeds
(2, 3, 4, and 5 cm/sec) and at four of the eight movement directions
(0, 90, 180, and 270°) recorded in animal D. Data from five
overlapping trials are shown; first and second
vertical dotted lines mark the Hold1 period-Track period and
the Track period-Hold2 period transitions, respectively.
B, Single-trial records of x and
y eye positions during constant speed tracking at each
of the four constant speeds (2, 3, 4, and 5 cm/sec) and at four of the
eight movement directions (0, 90, 180, and 270°) from animal C. Five
overlapping trials are shown. Vertical dotted lines mark
the Hold period-Cue period transitions; vertical solid
lines mark the Cue period-Track period transitions. Scale bar,
x and y eye position excursions of
15°.
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Eye x and y positions in time are shown in Figure
12B for the four constant speeds (2, 3, 4, and 5 cm/sec) and for four movement directions (0, 90, 180, and 270°). At
all directions and speeds, saccadic eye movements characterized the
premovement hold period. At the three highest speeds (3, 4, and 5 cm/sec), smooth pursuit eye movements occurred throughout the cue and
track periods. At the lowest speed (2 cm/sec), the animals initially
engaged in a brief period of smooth pursuit movements after the
appearance of the cue target, which was in turn followed by a period of
saccades. During the next 500-750 msec before and after the cue
period-track period transition, smooth pursuit movements resumed.
Saccades commonly occurred in the latter half of the track period.
Task-related EMG activity was observed in all 10 muscles that were
recorded in both animals during the performance of both tracking tasks
(Fig. 13). In Figure 13A-C,
the average EMG activity of the biceps (long head), spinodeltoid, and
flexor carpi ulnaris muscles is shown. The activity of the biceps
muscle (Fig. 13A) is shown for movements in all eight
directions (0-315° in 45° increments) and at the slowest (2 cm/sec) and fastest (5 cm/sec) peak speeds during performance of the
bell tracking task. Note the increase in EMG activity during the track
period, which is apparent at both speeds in the directions ranging
180-270°, as well as the relative inactivity during the initial and
final hold periods. This direction-related modulation during the track
period can also be seen in the tuning curves obtained from fitting Eq. 2 in Figure 13D, top. The activity of this muscle
was tuned to movement direction at all four speeds (top) but
was not tuned to movement speed at any of the eight directions (Fig.
13D, bottom). The EMG activity of the spinodeltoid and
flexor carpi ulnaris muscles, which was recorded during the constant
speed task, is shown in Figure 13, B and C,
respectively. In both of these muscles, little or no EMG activity was
observed during the hold or premovement cue periods; along some
directions, however (e.g., 180°), there was an increase in activity
50-100 msec before the beginning of the track period, consistent with
previous observations (Georgopoulos et al., 1984 ; Turner et al., 1995 ).
Direction-related modulation was observed during the track period in
both muscles. In the spinodeltoid muscle (Fig. 13B),
movement direction-related activity increases were seen in the range
45-135°, and in the flexor carpi ulnaris muscle (Fig.
13C), increases in activity were apparent in the 180-270° quadrant (also see Fig. 13B). In both of these records, EMG
activity was tuned to movement direction at all four speeds (Fig.
13E,F, top) but was not modulated with changes in movement
speed (Fig. 13E,F, bottom).

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Figure 13.
Task-related EMG activity. A-C,
EMG activity of the biceps (long head), spinodeltoid, and flexor carpi
ulnaris muscles recorded in animals D, D, and C, respectively. Also
shown in each plot are x and y hand
position (solid and dashed lines, middle)
and speed (solid lines, bottom). Position and speed span
5 to 5 cm and 0-6 cm/sec, respectively. The biceps EMG was recorded
during performance of the bell task; the spinodeltoid and flexor carpi
ulnaris muscles were recorded during the constant speed task.
D-F, Average EMG activity in standardized units as a
function of direction (top) and speed
(bottom) corresponding to A-C above.
Each of these muscles was directionally tuned at all four speeds; no
speed-related activity was observed along any of the directions.
|
|
The EMG activity of these 10 muscles was recorded in both animals
during the performance of both tasks over three to six times each, for
a total of 135 EMG recordings. Direction-related modulation has been
well described in reaching tasks (Georgopoulos et al., 1984 ; Flanders,
1991 ; Turner et al., 1995 ) and was, in this study, a prominent feature
of EMG activity recorded during the track period in both tasks. For all
10 muscles recorded, statistically significant directional tuning (Eqs.
1, 2) of EMG activity at all movement speeds was observed in at least
one EMG recording in both animals and for both tasks (90 EMG recordings
total). Speed-related modulation (Eq. 3) was observed in five muscles [acromiodeltoid, biceps (long head), flexor carpi radialis,
spinodeltoid, and triceps (long head)], for a total of 12 recordings
for both animals and both tasks. Moreover, when present, directional
tuning tended to occur for a given muscle at all four speeds (61 recordings), whereas speed-related modulation occurred most commonly at
just one movement direction (7 recordings). The EMG activity obtained in these recordings was also fitted to the response surface model (Eq. 4). A far smaller percentage of EMG recordings significantly fitted the
model (61 of 135, 45.2%), and on average, these fits were poorer (mean
R2 = 0.45). These poorer fits of the
surface model were likely attributable to the failure of movement speed
to contribute strongly to the overall variability observed in EMG activity.
 |
DISCUSSION |
Task-related modulation of Purkinje cell simple
spike discharge
The simple spike discharge of most Purkinje cells was modulated
during both visually guided tracking tasks and therefore was invariant
with regard to the temporal profile of the tracking speed. In the most
directly comparable study (Fu et al., 1997 ), in which Purkinje cell
simple spike discharge was recorded during step movements, 179 of 231 (77.5%) cells were task-modulated, compared with 132 of 154 (85.7%)
cells in this study. Therefore, the simple spike discharge of Purkinje
cells is highly modulated during tracking tasks involving the arm.
Because the simple spike discharge of floccular and vermal Purkinje
cells is highly modulated during smooth pursuit eye tracking, a
behavior for which the cerebellum is critical (Miles and Fuller, 1975 ;
Lisberger and Fuchs, 1978 ; Kase et al., 1979 ), the present results
suggest cerebellar involvement in general in pursuit tracking.
Although the simple spike discharge of some Purkinje cells is strongly
modulated by smooth pursuit eye movements and saccades, it is unlikely
that the simple spike modulation described here is simply attributable
to eye movements or vision. Three findings support this. First, the
Purkinje cells recorded in this study were located in the intermediate
and lateral hemispheres, near the primary fissure; eye movement-related
cells have been found mainly in the flocculus and vermis. In one study
of eye movement-related Purkinje cell discharge recorded in the lateral
cerebellum, only 2 of 134 (1.5%) cells had discharge that was related
to a moving, visual target (Marple-Horvat and Stein, 1990 ). Two recent
studies (Mano et al., 1991 , 1996 ) found no modulation in Purkinje cell simple spike discharge during smooth pursuit eye movements but did find
saccade-related simple spike discharge; the recording sites, however,
were located much more posteriorly to those in this study, and no
saccade-related activity was found in the areas of cerebellar cortex in
which we recorded. Input and output neurons of the intermediate
cerebellum also exhibit very little visual or eye movement-related
discharge (van Kan et al., 1993a ,b ). Second, the number of cells with
cue period-related discharge modulation was considerably less than that
with track period-related modulation, and the depths of modulation
(Idir) and slopes
( 1) for the cue period were lower than those
found during arm tracking. Third, simple spike discharge in the
constant speed task significantly increased above baseline very close
in time to the onset of the track period, not early in the cue period.
The onset of significant discharge modulation occurred even later in
the bell task. Because the eye movements and visual input were
symmetric across the tasks, it is doubtful whether either played a
significant role in the simple spike discharge modulation observed
here. Therefore, neither eye movement nor visual input appears to have
been a major contributor to the simple spike discharge modulation.
Relationship of Purkinje cell simple spike discharge to movement
direction and speed
In this study, movement direction was an important determinant of
Purkinje cell simple spike discharge rate. The discharge of 85 of 132 (64.4%) task-modulated cells was tuned to movement direction during
arm tracking, based on the cosine model. This result complements the
findings of the few studies (Marple-Horvat and Stein, 1987 ; Fortier et
al., 1989 , 1993 ; Fu et al., 1997 ) of cerebellar encoding of movement
direction in primates during multijoint reaching. The percentage of
cells with direction-related simple spike discharge in this tracking
task (64.4%) was higher than that found in an earlier study (45.7%)
of simple spike discharge during ballistic reaching movements (Fu et
al., 1997 ). Therefore, in addition to the overall finding of a higher
percentage of task-modulated cells in this visuomotor tracking task, a
higher percentage of cells were directionally tuned during
feedback-dependent tracking compared with ballistic reaching.
Movement speed was also an important predictor of simple spike
discharge in the two tasks; 77 of 132 (58.3%) cells were modulated with movement speed during arm tracking. Two other studies have examined the speed-velocity sensitivity of Purkinje cell simple spike
discharge in single or multijoint movement tasks. In a bidirectional, wrist movement task in which speed was varied over two broad ranges, Mano and Yamamoto (1980) found 19 of 92 (20.7%) cells to be modulated with movement speed. In a more recent study of Purkinje cell discharge in a four-direction reaching task (Marple-Horvat and Stein, 1987 ), 37 of 52 (71.2%) cells were correlated with speed, based on
cross-correlation analyses. Speed was not systematically controlled,
however. The tasks used in the present investigation, which varied
speed over four levels and along eight movement directions, were
designed explicitly to capture maximal information about Purkinje cell discharge modulation with regard to both direction and speed.
Relationship of Purkinje cell simple spike discharge to
movement velocity
The results of the single-parameter analyses in this study were
remarkable in that the simple spike discharge modulation was most
commonly limited to directional tuning along one speed or to
speed-related modulation along one direction. This suggested that the
interaction between direction and speed may be the critical predictor
of simple spike discharge. Analysis of the cells with both significant
direction and speed modulation according to the single-parameter models
(Eqs. 1-3) supported this concept (Fig. 8). Positive speed modulation
tended to occur along a cell's preferred direction, and negative speed
modulation was found primarily in the opposite direction. The discharge
of this group of cells is consistent with a linear code for movement velocity.
Because these linear analyses might not have fully captured the
discharge properties of these cells across the 32-point
direction-speed workspace, a response surface modeling of simple spike
discharge rate was undertaken. This analysis, which was linear in the
regression parameters but allowed for nonlinearity in the response,
showed that the simple spike discharge of most Purkinje cells (92 of 132; 69.7%) was tuned to movement velocity during arm tracking. The
quadratic terms were responsible for explaining the majority of the
variability in simple spike discharge. Thus, those cells with strictly
linear correlations to both direction and speed may constitute just a
subset of the cells whose discharge is best described by both linear
and nonlinear variation with these parameters. Importantly, all
movement velocities were represented across the population of Purkinje
cells. Therefore, the neural substrate may exist for providing a
population code for velocity by summing the activity of these cells in
a manner analogous to the population code described for movement
direction in the primary motor cortex (Georgopoulos et al., 1988 ;
Schwartz, 1993 ).
One implication of this property of Purkinje cells a preferred
velocity is that the simple spike discharge is probably not best
described as signaling direction and speed but, rather, as integrating
their combination. In a single-joint movement study of mossy fibers,
which serve as inputs to cerebellar Purkinje cells via granule cells,
the phasic discharge was correlated to both movement direction and
speed (van Kan et al., 1993b ). Purkinje cells are known to play an
integrative role with regard to other control signals, for example, in
the combination of head and eye velocity signals to yield gaze velocity
(Lisberger and Fuchs, 1978 ; Stone and Lisberger, 1990 ). The
representation of movement velocity observed here in the simple spike
discharge of cerebellar Purkinje cells most likely reflects a role for
the cerebellum in the direct control of velocity. Patients and
experimental animals with cerebellar lesions are characterized by
abnormalities in the velocity of movements (Holmes, 1939 ; Beppu et al.,
1984 ; Miall et al., 1987 ; Diener and Dichgans, 1992 ). The encoding of
movement velocity in cerebellar neurons could be needed for predictive aspects of movements (Pellionisz and Llinas, 1979 ; Kettner et al.,
1997 ). The ability to make smooth pursuit movements requires a
prediction of the target's trajectory, and a velocity signal would be
useful in making such a prediction for both eye and limb movements.
Velocity encoding may also reflect a role for the cerebellum in the
specification of movement dynamics. Information about movement velocity
is required for the calculation of interaction torques, which are
disrupted in subjects with cerebellar pathology (Bastian et al., 1996 ).
Also, velocity may be used to compute forces related to viscosity as
needed for a model of inverse dynamics (Shidara et al., 1993 ; Gomi et
al., 1998 ). Nonetheless, the present finding of a velocity signal in
the simple spike discharge for pursuit tracking with the arm and the
known gaze velocity signal for the control of eye movements provides a
unifying role for Purkinje cells in motor control.
Relationship of EMG activity to movement direction, speed,
and velocity
A secondary aim of this study was to compare the magnitude and
extent of significant correlations between simple spike discharge rate
and direction, speed, and velocity with those of the correlations observed between EMG activity and each of these parameters. It has been
proposed recently that the discharge of cerebellar neurons encodes
movement commands in muscle-based coordinates (Miller and Houk, 1995 ).
If this is so, then the relationship of simple spike discharge to
movement direction and speed should be very similar to the relationship
of EMG activity to these parameters. Using the same analysis as applied
to the simple spike discharge, it was shown that significant
relationships between EMG activity and movement direction were observed
far more commonly than those between EMG activity and speed. In
addition, when compared with the simple spike discharge records, a far
smaller percentage of EMG activity recordings were well described by
the response surface model, and the values of
R2 were lower. This dissimilarity of
parameter relations between cell discharge and EMG activity suggests
that the simple spike discharge of Purkinje cells does not contribute
to limb movement simply by specifying patterns of muscle activation.
Rather, the simple spike discharge appears to incorporate information
about both direction and speed, signaling movement velocity.
 |
FOOTNOTES |
Received June 15, 1998; revised Dec. 11, 1998; accepted Dec. 11, 1998.
This work was supported by National Institutes of Health Grant NS18338
and the Human Frontier Science Program. J.D.C. was supported by
National Institutes of Health Grant MH11430, and M.T.V.J. was supported
by National Institutes of Health Grant NS07361. We thank E. C. Ebner for programming the movement paradigm and M. L. McPhee for
assistance with histology.
Correspondence should be addressed to Dr. Timothy J. Ebner, Department
of Neurosurgery, University of Minnesota, 2001 Sixth Street SE, Room
421, Minneapolis, MN 55455.
 |
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B. Greger, S. A. Norris, and W. T. Thach
Spike Firing in the Lateral Cerebellar Cortex Correlated With Movement and Motor Parameters Irrespective of the Effector Limb
J Neurophysiol,
January 1, 2004;
91(1):
576 - 582.
[Abstract]
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S. M. Lewis, T. A. Jerde, C. Tzagarakis, M.-A. Georgopoulos, N. Tsekos, B. Amirikian, S.-G. Kim, K. Ugurbil, and A. P. Georgopoulos
Cerebellar Activation During Copying Geometrical Shapes
J Neurophysiol,
December 1, 2003;
90(6):
3874 - 3887.
[Abstract]
[Full Text]
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R. S. Turner, M. Desmurget, J. Grethe, M. D. Crutcher, and S. T. Grafton
Motor Subcircuits Mediating the Control of Movement Extent and Speed
J Neurophysiol,
December 1, 2003;
90(6):
3958 - 3966.
[Abstract]
[Full Text]
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O. Donchin, J. T. Francis, and R. Shadmehr
Quantifying Generalization from Trial-by-Trial Behavior of Adaptive Systems that Learn with Basis Functions: Theory and Experiments in Human Motor Control
J. Neurosci.,
October 8, 2003;
23(27):
9032 - 9045.
[Abstract]
[Full Text]
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M. Ito
Cerebellar Long-Term Depression: Characterization, Signal Transduction, and Functional Roles
Physiol Rev,
July 1, 2001;
81(3):
1143 - 1195.
[Abstract]
[Full Text]
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K. C. Engel, J. H. Anderson, and J. F. Soechting
Similarity in the Response of Smooth Pursuit and Manual Tracking to a Change in the Direction of Target Motion
J Neurophysiol,
September 1, 2000;
84(3):
1149 - 1156.
[Abstract]
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K. C. Engel and J. F. Soechting
Manual Tracking in Two Dimensions
J Neurophysiol,
June 1, 2000;
83(6):
3483 - 3496.
[Abstract]
[Full Text]
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