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JOURNALOF NEUROPHYSIOLOGY
Vol. 64, No. 1, July 1990. Printed in U.S.A.
Movement-Related Neuronal Activity Selectively Coding Either
Direction or Muscle Pattern in Three Motor Areas of the Monkey
MICHAEL
D. CRUTCHER
Department
of Neurology, Johns Hopkins University School of Medicine, Baltimore,
AND
GARRETT
E. ALEXANDER
SUMMARY
AND
CONCLUSIONS
I. Movement-related neuronal activity in the supplementary
motor area (SMA), primary motor cortex (MC), and putamen
was studied in monkeys performing a visuomotor tracking task
designed to determine 1) the extent to which neuronal activity in
each of these areas represented the direction of visually guided
arm movements versus the pattern of muscle activity required to
achieve those movements and 2) the relative timing of different
types of movement-related activity in these three motor areas.
2. A total of 455 movement-related neurons in the three motor
areas were tested with a behavioral paradigm, which dissociated
the direction of visually guided elbow movements from the accompanying pattern of muscular activity by the application of
opposing and assisting torque loads. The movement-related activity described in this report was collected in the same animals
performing the same behavioral paradigm used to study preparatory activity described in the preceding paper. Of the total sample,
87 neurons were located within the arm region of the SMA, 150
within the arm region of the MC, and 2 18 within the arm region
of the putamen.
3. Movement-related cells were classified as “directional” if
they showed an increase in discharge rate predominantly or exclusively during movements in one direction and did not have significant static or dynamic load effects. A cell was classified as “muscle-like” if its directional movement-related activity was associated with static and/or dynamic load effects whose pattern was
similar to that of flexors or extensors of the forearm. Both directional and muscle-like cells were found in all three motor areas.
The largest proportion of directional cells was located in the putamen (52%), with significantly smaller proportions in the SMA
(38%) and MC (4 1%). Conversely, a smaller proportion of muscle-like cells was seen in the putamen (24%) than in the SMA
(41%) or MC (36%).
4. The time of onset of movement-related discharge relative to
the onset of movement (“lead time”) was computed for each cell.
On average, SMA neurons discharged significantly earlier (SMA
lead times 47 t 8 ms, mean t SE) than those in MC (23 k 6 ms),
which in turn were earlier than those in putamen (-33 ? 6 ms).
However, the degree of overlap of the distributions of lead times
for the three areas was extensive.
5. The directional neurons appeared to code for movement
direction per se, independent of the pattern of muscle activations
required. Thus, in all three areas, there was evidence of neural
processing related to “high-level” aspects of motor control that
are logically antecedent to the final specification of muscle activations. The evidence that movement-related neurons in the
SMA tend to discharge earlier than their counterparts in MC and
these in turn earlier than those in putamen suggeststhat there is
some degree of sequential processing from the SMA to the MC
and thence to the putamen. On the other hand, the existence of
both directional neurons and neurons with muscle-like activity
patterns in each of these areas and the significant overlap in the
timing of movement-related activity of these cells strongly suggest
0022-3077/90
$1 SO Copyright
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Maryland
21205
that multiple levels of motor processing proceed in parallel within
all three motor structures.
INTRODUCTION
Many investigations of single-cell activity in central
motor structures have described movement-related
discharge that was correlated with the direction of limb movement. In most of these studies, however, no attempt was
made to dissociate the direction of limb movement from
the accompanying
pattern of muscle activity. Consequently, the pattern of muscle activity covaried with the
direction of limb movement, because of the inherently directional nature of muscle activations. A few early studies
did dissociate these variables, however, by using opposing
and assisting loads (Conrad et al. 1977; Evarts 1967, 1968,
1969). Each of these studies stressed the relation of neuronal activity to force or muscle pattern. In fact, there have
been many studies of central motor structures that, although not addressing the issue of direction versus muscle
pattern directly, have described relations of single-cell activity to muscular force (Cheney and Fetz 1980; Evarts et
al. 1983; Fromm 1983b; Kalaska and Hyde 1985; Liles
1985; Schmidt et al. 1975; Smith 1979; Smith et al. 1975).
As a result, a widespread impression has emerged that certain motor structures, particularly the primary motor cortex, may be essentially concerned with controlling either
force or the pattern of activity of different muscle groups.
Recently, studies of single-cell activity in two components of the basal ganglia-thalamocortical
“motor circuit,”
the putamen (Crutcher and DeLong 1984a) and globus
pallidus (Mitchell et al. 1987), of primates have been carried out with the use of motor tasks that dissociated the
direction of limb movement from the pattern of muscle
activity. In both areas the activity of substantial proportions of movement-related
neurons was found to depend
on the direction of limb movement independent of the
associated pattern of muscle activity. In the present study
monkeys were trained to perform similar tasks in which
visually guided elbow movements were made with opposing and assisting loads that dissociated the direction of
elbow movement from the pattern of muscular activity
required to make the movement. Task-related neuronal
activity was recorded from the supplementary motor area
(SMA), primary motor cortex (MC), and putamen. As discussed in the preceding paper (Alexander and Crutcher
1990), all three areas are important components of the
basal ganglia-thalamocortical
motor circuit (Alexander et
al. 1986).
1990 The
American
Physiological
Society
151
M. D. CRUTCHER
152
AND G. E. ALEXANDER
The present study was designed to determine whether
representations of movement direction and/or muscle pattern were distributed evenly across these three motor areas
or whether there was evidence for functional specialization
within the different regions. Because this experiment involved recording in all three areas by the use of the same
paradigm and animals, it permitted a more direct comparison of movement-related activity in SMA, MC, and putamen than could be accomplished by comparing data obtained in different laboratories with different experimental
paradigms. This made it possible to address the additional
issue of whether there were significant differences in the
timing of movement-related
activity among these three
areas, as had been suggested by earlier comparisons of
physiological data from different laboratories (Anderson et
al. 1979; Crutcher and DeLong 1984a; Georgopoulos et al.
1982, 1989; Murphy et al. 1982; Tanji and Kurata 1982;
Thach 1978). Some of these results have been presented in
preliminary form (Crutcher and Alexander 1987, 1988).
ASSISTED
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VELOCITY
FLEXION
NO LOAD
OPPOSED
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VELOCITY
I
METHODS
The behavioral paradigms, recording techniques, and data collection procedures were described fully in the first paper of the
series (Alexander and Crutcher 1990). Additional details regarding the methods of data analysis are described below.
Analysis of variance
The principal data analysis was done with the use of a 3-way
analysis of variance (ANOVA) with repeated measures (because
of the repeated presentation of each trial type). The three factors
were epoch within the trial, direction of movement, and load. (In
some casesloads were not applied, in which casea 2-way ANOVA
was used.) Four epochs within each trial were analyzed: the
preinstruction hold period prior to the first lateral target presentation, the first movement period, the postinstruction hold period
prior to the presentation of both side targets, and the second
movement period. The movement periods were defined as the
time from 100 ms prior to the onset of movement to the end of
movement. However, if the change in activity of a movement-related cell began early in the reaction time and was relatively brief,
the reaction time rather than the movement period was used as
the epoch for measuring movement-related activity. The dependent variable was the average discharge rate during each of these
epochs for each trial. Two directions of movement (extension and
1. Sensorimotorfields of cells with
movement-reluted activity
TABLE
SMA’
Elbow
Shoulder
Distal
Active arm
Negative
Total tested
Not tested
Grand total
It
I
Il11
100 MS/DIV
25 (30)
17 (20)
6 (7)
28 (33)
8 (10)
84 (100)
67
151
MC
Putamen
69 (5 1)
14 (10)
16 (12)
29 (22)
7 (5)
90 (57)
9 (6)
4 (3
38 (24)
16 (10)
135 (100)
45
157 (100)
83
180
240
Numbers in parentheses are percentages of cells tested by examination
of the animal outside the task. SMA, supplementary motor area; MC,
primary motor cortex. *Includes cells with combined preparatory and
movement-related activity.
I
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Task-related EMG activity recorded from the biceps muscle.
Average EMG activity is shown for 10 trials of each class, and single-trial
velocity records are shown for 1 class. Trials are aligned on the onset of
movement. The activity pattern shows the typical static load effect (increased tonic activity with a constant flexor load) during the hold period
that preceded visually triggered elbow movements. There was also a dynamic load effect during the movement interval. Like other prime flexors
(or extensors) of the elbow, this muscle showed increased activity with
opposing loads and reduced activity with assisting loads. An upward deflection of the velocity trace represents extension. FL, flexor load; EL,
extensor load.
FIG.
1.
flexion) and three levels of load (0.1 Nm opposing extension, 0.1
Nm opposing flexion, and no load) were used.
Several other significance tests were carried out in conjunction
with the main ANOVA. Three orthogonal comparisons between
epoch means were performed to clarify the source of significant
epoch effects (Keppel 1973). These included comparisons between the hold and the movement epochs, between the preinstruction hold and postinstruction hold periods, and between the
first and second movement periods. In addition, the simple main
effects for direction and load were calculated if the main effect
(for direction or load) or the main effect X epoch interactions
were significant (Keppel 1973). This analysis permitted us to
identify the source of significant main effects and interactions.
For example, if the main effect for direction was significant in the
main 3-way ANOVA, it might be the result of significant relations
to direction in one or both of the two movement periods, or the
postinstruction period, or all three. By calculating the simple
main effects for direction for each of the four epochs, we were able
to determine which epochs of the task exhibited directional activity. We also calculated the simple main effects for load to determine whether there were significant static load effects in the
preinstruction hold period, dynamic load effects during the flexion or extension movement periods, or load effects during the
preparatory (postinstruction) period prior to extension or flexion
movements.
For all of the above tests, a significance level of P < 0.00 1 was
used. This rather conservative significance level was chosen for
the following reason. We carried out a seriesof preliminary analyses on data from 20 cells, using several different significance
levels: 0.05, 0.01, and 0.00 1. A 3-way ANOVA on 60 trials with
MOVEMENT-RELATED
ACTIVITY
four epochs per trial is extremely sensitive. We found that using
0.05 or 0.0 1 yielded “significant” results on responsesthat were so
subtle that they were difficult (and, in some cases,impossible) to
detect by eye. The significance level of 0.00 1 was therefore chosen
so that only relatively clear responses would be found significant,
and this level was then used for all cells.
Analysis of cross cIassijications
On the basisof the above analyses, each cell from each area was
classifiedaccording to whether it showed movement-related activity, preparatory activity, or both and whether the movement-related activity was “directional” or “muscle-like.” Each of the resulting contingency tables of the frequencies of cells of different
categories in the SMA, MC, and putamen was then analyzed by
the use of three X* tests of homogeneity: one comparing each pair
of structures. If any of the X* tests were significant, the contingency table was broken up into multiple 2 X 2 tables, and log odds
ratios were calculated (Reynolds 1977).
Latencies of task-related activity
The latencies of task-related changes in neural activity were
determined for each cell on a trial-by-trial basis, with the use of
the following techniques. Two different algorithms were used to
detect increases and decreases in cell activity. These same algorithms were also used to detect the onsets and offsets of preparatory activity reported in the preceding paper (Alexander and
Crutcher 1990).
IN THREE
MOTOR
AREAS
153
For excitations, each spike in the trial was assigned the value of
one and then decayed exponentially with a time constant of 50
ms. All of the decaying exponentials were then summed to produce a continuous spike function for that trial where bursts in
activity would be represented by a scalloped increase in the function. Next, the mean and the standard deviation of the value of
the spike function at 1-ms intervals were calculated for 1 s prior to
the target presentation. High (P < 0.00 1) and low (P < 0.1) thresholds for the spike function were calculated, and the period from
50 ms after the stimulus to the end of the movement was then
scanned for a significant increase in activity. If the function stayed
above the high threshold for at least 10 ms and above the low
threshold for at least 75 ms, the onset of the response was taken as
that point at which the function first exceeded the value of the low
threshold.
For inhibitions, the same basic procedure was used except that
the spike train was converted into an interspike interval function,
such that decreasesin cell activity were represented by an increase
in the spike function, and the mean and standard deviation of the
interspike intervals in the prestimulus period were used to determine the high and low thresholds.
For cells with movement-related activity, the “lead time” was
calculated on a trial-by-trial basis as the amount of time by which
the onset of neural activity preceded the onset of limb movement.
The median value for all trials in the preferred direction was used
as the time of the onset of the response for each cell.
The procedure for determining the time of the first change in
electromyographic (EMG) activity for the 39 muscles studied was
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FIG. 2. Raster displays of 2 cells with movement-related activity recorded within the motor cortex. Each small tick
indicates the occurrence of a single action potential, and each row represents the neuronal activity recorded during 1 trial.
Large ticks indicate the times of occurrence of the target shifts that triggered the elbow movements. Trials are aligned on the
onset of movement and sorted by reaction time. The rasters are sorted according to class, using the same conventions as in
Fig. 1. The directional cell on the Ze@showed increased discharge in relation to extension movements that was independent
of the loading conditions. The cell also showed a reciprocal reduction in activity during flexion movements. In contrast, the
muscle-like cell whose activity is presented on the right showed increased discharge during extension movements that was
characterized by a dynamic load effect (the movement-related activity was increased with loads that opposed extension and
decreased with loads that assisted extension). The cell also showed a comparable static load effect during the hold period
prior to the onset of movement. The overall pattern of activity in this cell was the mirror image of the activity of the biceps
muscle shown in Fig. 1.
154
M. D. CRUTCHER
AND G. E. ALEXANDER
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FIG. 3. Activity of 2 movement-related
cells in the SMA. Left: activity of a directional cell that showed a selective
increase in discharge in relation to flexion movements that was independent of the loading conditions. The cell also showed
a reciprocal reduction in activity in relation to extension movements. The muscle-like cell on the right showed dynamic and
static loading effects similar to those of the biceps muscle shown in Fig. 1. Conventions are the same as in Fig. 2.
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FIG. 4. Activity of 2 movement-related
putamen neurons. The directional cell whose activity is shown on the left
discharged selectively in relation to flexion movements, irrespective of the loading conditions. The muscle-like cell on the
right showed a pattern of dynamic and static loading effects that was similar to the EMG activity of the biceps muscle
illustrated in Fig. 1. The static load effect for this cell is more subtle than that of the muscle-like cells shown in Figs. 2 and 3,
but is still significant at the 0.00 1 level. Conventions are the same as in Fig. 2.
MOVEMENT-RELATED
ACTIVITY
the same as for neuronal excitations except for three differences.
First, the EMG activity was not smoothed with the exponential
decay procedure. Second, because of this the onset found by the
algorithm occasionally had to be manually corrected. Third, only
unloaded trials were used.
RESULTS
Locations of recorded cells
EMG activity
One of the goals of this study was to determine whether
there were cells in each of these motor structures whose
activity was related to the direction of limb movement
independent of the required muscle activations. To do this,
we applied constant loads (0.1 Nm) to the monkey’s arm
via the torqueable
manipulandum
(Alexander
and
Crutcher 1990). These loads either opposed or assisted the
2.
Categories of movement-related activity
SMA
MC
Putamen
Directional
Muscle-like
Other
33 (38)
36 (41)
18 (21)
61 (41)
55 (36)
34 (23)
114 (52)
52 (24)
52 (24)
Total
87 (100)
150 (100)
218 (100)
1
1
SMA vs. MC
Directional
Ratio
Confidence
interval
P value
TABLE
3.
AREAS
155
Load effects in muscle-like ceI1.s
SMA
MC
Putamen
Dynamic and static
Dynamic only
Static only
23 (64)
4 (11)
9 (25)
24 (43)
13 (24)
18 (33)
23 (44)
21 (41)
8 (15)
Total
36 (100)
55 (100)
52 (100)
NS
1
Cells with movement-related
activity were recorded
throughout the respective “arm” areas of the SMA, MC,
and putamen. The locations of all cells with movement-related activity for each of the three structures were shown in
the first paper of this series (Alexander and Crutcher 1990).
The location of each cell within an area of arm representation was confirmed by the somatotopic features of I) local
neuronal responses to a sensorimotor examination and/or
2) the movements evoked by microstimulation
(Alexander
and Crutcher 1990). The sensorimotor fields of cells with
movement-related activity are shown in Table 1. Cells were
classified on the basis of their responses to a sensorimotor
examination of the animal outside the task (see Alexander
and Crutcher 1990). The majority of cells were related to
elbow movements. Significantly fewer cells were related to
movements of the distal arm or shoulder. Cells were classified as active arm only if their activity was related to active
arm movements outside the task and that activity could
not be attributed confidently to a specific joint. Cells were
classified as negative if their activity was not modulated
during the sensorimotor examination.
TABLE
IN THREE MOTOR
1 [
NS
P <
SMA vs. Putamen
vs. muscle-like
1
1
P < 0.05
0.01
MC vs. Putamen
odds ratios
0.8 1
2.42
0.5 1
1.48, 0.45
NS
4.19, 1.36
0.003
0.83, 0.31
0.007
Numbers in parentheses are percentages. NS, not significant. Other
abbreviations, see Table 1.
1
1
Both vs. Dynamic
SMA
Ratio
Confidence
interval
P value
1
NS
1
P < 0.05
Both vs. Static
vs. putamen
odds
1
Dynamic vs. Static
ratios
5.25
0.89
0.17
17.70, 1.56
0.008
2.71, .29
NS
0.71, 0.04
0.015
Numbers in parentheses are percentages. Abbreviations,
and 2.
see Tables 1
movement. An example of EMG activity in the task for
one of the prime movers is shown in Fig. 1. This biceps
muscle was active during unloaded flexion movements and
was more active when the static load opposed the flexion
movement (flexor load) but was almost inactive during
assisted flexion movements (extensor load). We refer to
this modulation of movement-related activity with loads as
a dynamic load efict. This muscle also had a pronounced
static load e@ct; that is, it was tonically active when the
constant load opposed movements in the preferred direction. The biceps was inactive during extension movements.
This was the characteristic pattern of activity for most
muscles that were active in the task.
There was no basis for suspecting that any significant
portion of the directional neuronal responses observed in
this study (see below) could be accounted for by “muscleassociated” neurons that happened to code for activations
of directional muscles. Of the 39 muscles examined in this
study (Alexander and Crutcher 1990), only one, the cervical rhomboid, showed task-related activity that was directional in nature (that is, directional activity that was independent of loading conditions).
Neuronal activity related to movement direction
versus muscle pattern
Cells with a pattern of activity like that of muscles were
found in all three motor areas. An example of such a cell
from the MC is shown on the right of Fig. 2. This cell’s
activity was related to extension movements, and it showed
both dynamic and static load effects. We categorized cells
of this type as muscle-like cells. However, we also recorded
cells whose movement-related activity was directional but
which did not have either static or dynamic load effects. An
example of such a cell from the MC is shown on the left of
Fig. 2. This cell was equally related to extension movements whether the constant load assisted or opposed the
movement. These cells were designated as directional cells.
Examples of directional and muscle-like cells from the
SMA and putamen are shown in Figs. 3 and 4, respectively.
M. D. CRUTCHER
156
TORQUE
RESPONSE
AND G. E. ALEXANDER
MOVEMENT
RESPONSE
PRE-INSTRUCTION
INTERVAL
EXTENSION
FLEXOR
LOAD
ASSISTED
EXTENSOR
LOAD
OPPOSED
0
0
0
FLEXION
I
“I I
0
0 ,
0
,
0
0
0
0
I
0
0
EXTENSOR
LOAD
0
I
0°1
ASSISTED
O -
FLEXOR
LOAD
WPOSED
I-100 MS/ON
/
A
/
FP
f&&j,
TORQUE
A
TARGET
MOVEMENT
FIG. 5. Active directional activity in motor cortex. Right haZ$ activity of the cell during the active elbow movements to
capture the side targets. This neuron discharged selectively in relation to extension movements irrespective of the loading
conditions and was therefore classified as directional. Left haI& activity of the cell during the application of the torque load.
The cell was judged to be of the active variety because there was no evidence of short-latency (~60 ms) proprioceptive input
to this cell as the load was applied. Thus there was no increase in activity (short-latency or otherwise) when the elbow was
passively extended during the application of the flexor load. (The weak response after the application of extensor loads was
because of the active extension required for the animal to reposition the cursor when the forelimb was passively displaced in
the direction of flexion.) An upward deflection of the velocity trace represents extension.
TORQUE
RESPONSE
PRE-INSTRUCTION
INTERVAL
MOVEMENT
RESPONSE
EXTENSION
I , I ,
I II,,
,,
,
I’
FLEXOR
LOAD
,oo,:,,
I
l ,,
, ,o
1,101
’ , ‘Y
I I
‘
I
,
, ,'I
Ill,,
I :o ,I,,,.d
I
0 I
; ’ O
,‘:I 1 I
o:, I@ 'I '
,
,
.oo.o,o
00
IO 00,.
,,a
0
I, 00 ,o,, ,I, mom l l OD , , ,
:I',,
, 0 ,a 7 ;;f,oeo
I ; I 00000 l m IO I 0’. l om I I
, I l100l0,
,
0
* IO 00’ IO I
I
,...‘@’
I I
, ,DlO,8,,
II0 I DO 0 ,lOO,rn
8,
‘: O”’
0 ’
0,,,I0#~l~lI
001,
I I
,
,
I
I
,I,
*000,001
om
aa
8
0
* ,I I
0
I, ‘0.0000
Ioo.#o,o
:
I
,‘I,
,‘I’,
,
,o
I,
I
I Il~.~.
I
,o','e
EXTENSOR
LOAD
eeoeo
0
0
*,0.:.*:,
y;*;m
,
88
0 0:’
0 'I@
0
,
:
,
II
,I,
0 I
,I I. , :o 0 : '('
II
, IO' ' "I
' '0 ' "I
,I
I
I I I IO,
0 I
,
,:
0:’
I ,*
IO,
I 4
I' ,
"I
I
I
: 0
,, I I:.:
0,
1
,,I
I
,a0
, ,,I
I)
0 0
‘I ‘de : ‘,’ ’ ,
I, I I ‘pl,
;;
I J
I
I ; ‘e@y
I, I,,
,’ I
I I I lb’
I ,’
I” t ,**mm
I ‘11l1
0
I
,+
0
ASSISTED
~,';,l)~,;#e",(;i;;yl
I
I
IO ,‘I
***a
,I
I ,I
,
,
, ,
OPPOSED
FLEXION
EXTENSOR
LOAD
ASSISTED
FLEXOR
LOAD
OPPOSED
lOOMS/DlV
/
/
A
TOWE
TARGET
MOVEMENT
FIG. 6. Passive directional activity in motor cortex. This cell showed a directionally selective increase in discharge with
active flexion movements irrespective of the loading conditions, but also showed evidence of passive proprioceptive inputs
of similar directionality. Thus part or all of the response apparently related to active movement could potentially be
explained by movement-induced proprioceptive inputs. Conventions are the same as in Fig. 5.
MOVEMENT-RELATED
TABLE 4.
ACTIVITY
IN THREE
MOTOR
AREAS
157
Categories of directional cells
posed flexion. Some cells showed the greatest (or the least)
activity in the unloaded condition. A few cells were bidirecSMA
MC
Putamen
tional; they were movement related but they were equally
active
for both directions of movement. (The total number
Active
31 (94)
48 (79)
97 (85)
of cells shown in Table 2 is less than the number of cells
Passive
2 (6)
13 (21)
17 (15)
with movement-related activity in Table 1 because a small
Total
33 (100)
61 (100)
114 (100)
number of cells were not tested with loads and, thus, could
not be categorized as directional or muscle-like.)
[
[
NS
1
NS
1
x2 analyses were performed to determine whether the
NS
1
1
proportions of directional, muscle-like, and other cells
Numbers in parentheses are percentages. Abbreviations, see Tables 1 were different in the three areas (Table 2). In this respect,
and 2.
the putamen was significantly different than both the MC
(P < 0.05) and the SMA (P < O.Ol), but the two cortical
The proportions of cells with different categories of moveareas did not differ significantly. The log odds ratio analysis
ment-related activity are shown in Table 2. There were provided further information. For example, the “odds” of
more than twice as many directional as muscle-like cells in a cell in the MC being directional rather than muscle-like
the putamen, whereas for the two cortical areas these two were 6 1 to 55 or 1.11 to 1. For the putamen, the odds were
types of cells occurred with about equal frequency. Move114 to 52 or 2.19 to 1. The ratio of these odds was 0.5 1. If
ment-related activity was categorized as directional if there the relative frequency of directional and muscle-like cells
was a significant (P < 0.001) direction effect for one or both was the same for these areas, then the ratio would be 1.
of the movement epochs and there were no significant
Because the ratio was significantly different than 1 (P <
static or dynamic load effects (see METHODS). Muscle-like
0.007), we can conclude that there were relatively more
cells had significant direction effects (because muscles are directional than muscle-like cells in the putamen cominherently directional), but they also had significant (P < pared to the MC. This was also true in comparing the
0.001) static load effects, dynamic load effects, or both, that
putamen to the SMA (P < 0.003). The two cortical areas
were “appropriate”
for their preferred direction of movedid not differ significantly.
Because there were almost
ment. For example, the MC muscle-like cell shown in Fig. identical proportions in the “other” category for the three
2 was related to extension movements and had increased areas, the odds ratio analysis was not done for this category.
movement-related
activity when the load opposed extenCells were categorized as muscle-like if they had a signifision and decreased activity when the load assisted exten- cant dynamic load effect, static load effect, or both. The
sion. Cells were classified as “other” if they did not fit frequencies of different types of muscle-like cells are shown
either of the above patterns of activity. This could happen
in Table 3. Overall, only one-half of the cells categorized as
in one of several different ways. The most common type of muscle-like had both static and dynamic load effects,
cell in this category had a static or dynamic load effect in whereas approximately one-fourth had dynamic load efthe “wrong” direction. For example, the cell was related to fects only, and one-fourth had static load effects only. The
flexion movements but showed greater activity when the only significant x2 was that comparing the putamen and
load assisted flexion and less activity when the load op- SMA. The log odds ratios indicate that this was because I)
DlRECT/ONAL
MOTOR CORTEX CELLS WITH
OR MUSCLE - LIKE ACTIVITY
/
No. Cells:
V-2) (34)
L4
xi
/
Cl
1 mm
A
A
Directlonrl
A
A
MUSCk
-Uke
FIG. 7. Locations of MC cells with directional or muscle-like activity in 3 hemispheres. The solid triangles represent the locations of the active directional cells. The open
triangles show the locations of muscle-like cells with dynamic load effects. The central sulcus is indicated, and rostral is to the left (regardless of whether data are from the
right or left hemisphere). Locations of the recording areas
relative to other surface landmarks are shown in Fig. 5 of the
preceding paper (Alexander and Crutcher 1990). The fourth
MC hemisphere is not shown in the present figure because
most cells in that hemisphere were not tested with loads.
Letters denote the movements evoked at threshold where
microstimulation was effective: E, elbow; S, shoulder; W,
wrist; F, finger.
M. D. CRUTCHER
158
AND G. E. ALEXANDER
the SMA had a preponderance of cells with both static and
dynamic load effects and a relative paucity of cells with
only dynamic load effects, and 2) the putamen had relatively more cells with only dynamic load effects and fewer
with only static load effects. These differences were due
primarily to the small proportion of cells with static load
effects in the putamen compared to the SMA.
280
CR
z
c,
140
0
- i40
-iSO
251
“Active” versus “passive” directional activity
An attempt was made to determine whether any of the
directional movement-related activity could have been because of directional sensory feedback during the movement. If there was a short-latency response (~60 ms) to the
load applications, which passively moved the arm in the
preferred direction, the cell was considered to be passively
driven and was therefore categorized as a “passive” directional cell. If not, the cell was labeled as an “active” directional cell. The torque application was considered to be an
effective probe for proprioceptive input because in each
monkey the resulting peak velocity induced by torque application was at least twice that of the active movement
associated with side target capture (see Fig. 5).
The activity patterns of active and passive directional
TABLE 5.
Muscle lead times
Spinodeltoid
Biceps
Flexor carpi radialis
Brachialis
Acromiodeltoid
Splenius capitus
Supraspinatus
Brachioradialis
Triceps, lateral
Cervical paraspinous
Infraspinatus
Pronator teres
Palmaris longus
Triceps, long
Pectoralis major
Flexor digitorum profundus
Atlantoscapularis anterior
Extensor carpi ulnaris
Teres major
Extensor carpi radialis
Flexor digitorum superficialis
Sternocleidomastoid
Flexor carpi ulnaris
Trapezius
Thoracic paraspinous
Lumbar paraspinous
Extensor digitorum communis
Cervical rhomboids
Latissimus dorsi
Semitendinosus
Cleidooccipitalis
Panniculus carnosus
Serratus anterior
Pectoralis minor
Temporalis
Quadriceps femoris
Biceps femoris
Gastrocnemius
Tibialis anterior
82
80
79
77
73
71
65
62
56
56
48
48
48
47
41
37
35
33
27
17
6
4
2
2
-13
-16
-42
-47
-48
-50
-63
-65
-69
NR
NR
NR
NR
NR
NR
Values represent the median of single trial lead times. NR, no response.
35
30
25
20
15
10
5
0
-280
Lead time
(ms)
FIG. 8. Onset latency histograms for all cells with movement-related
activity. The onsets of activity in SMA neurons were significantly earlier
than those in MC, which were in turn significantly earlier than those in
putamen.
cells from the MC are shown in Figs. 5 and 6, respectively.
For the active directional cell (Fig. 5) there was an increase
in activity before and during the active extension movements to capture the side target (right half of the figure).
There was also a weak increase in activity, which began
- 150-200 ms after the application of the extensor load (a
load opposing extension). This was the time of the active
extension movement required to bring the arm back to the
center after the passive flexion produced by the torque
application. The passive directional cell shown in Fig. 6
had a directional increase in activity during active elbow
flexion. Namely, it showed increased discharge in relation
to the active flexion movements to capture the side target
(right side of the figure) and to the active flexion to recover
from the application of the flexor load (150-200 ms latency). However, this cell also had a brisk short-latency
response to the application of the extensor load (which
passively flexed the elbow). Therefore all or part of the
directional activity seen during active flexion movements
may have been because of directional
proprioceptive
inputs. The numbers and percentages of both types of directional cells are shown in Table 4. Most cells were of the
active variety for all three motor areas. Differences between
the SMA, MC, and putamen in terms of the relative proportions of the two types of directional cells were not significant.
Locations of cells with directional
The relative
like patterns
whether there
these types of
the SMA and
or muscle-like activity
locations of cells with directional or muscleof activity were examined to determine
was a differential distribution of cells with
activity in any of the three motor areas. For
putamen, there was no significant difference
MOVEMENT-RELATED
TABLE 6.
ACTIVITY
IN THREE
MOTOR
AREAS
159
Lead times of all movement-related cells
Median, ms
Mean, ms
n
SMA
MC
Putamen
58
47 t, 8
114
31
23 k 6
156
-13
-33 k 6
229
[ P<
0.009
[ P<O.OOl
]
P <
Values are means t SE. Abbreviations,
Passive
Directional
-iSO
]
0.001
see Table 1.
-280
in the anteroposterior
distributions
of directional and
muscle-like cells (t tests, P > 0.05). The locations of these
two cell types within the MC are shown in Fig. 7. For the
MC, the perpendicular distance from the central sulcus was
measured. Although there was a high degree of overlap in
the distributions of the two cell types, the active directional
cells tended to be located more rostrally than the musclelike cells (t test, P < 0.01).
Muscle-like
0
I
I
140
Lead
Responseonsetlatencies
One of the principal goals of this study was to compare
the timing of movement-related neuronal activity in these
three motor areas. For reference, the times of activation
(lead times) of task-related muscles are shown in Table 5.
The earliest muscle lead time was 82 ms. Although the
range of lead times was surprisingly large, most task-related
muscles (73%) became active before the onset of movement, and the later muscles were generally trunk muscles
with weak task-related activity.
The response onset latency histograms for all cells with
movement-related activity in these areas are shown in Fig.
8. Although there is a great deal of overlap in the distributions, it is clear that the SMA generally leads the MC,
which in turn leads the putamen. T tests comparing the
I
b
time
I
-ii80
(ms)
FIG. 10. Onsets of movement-related activity in these different classes
of directional and muscle-like cells were not significantly different in
motor cortex.
means for pairs of areas indicated that these differences
were significant (Table 6). These latency differences between motor areas were also evident when the percentages
of cells with onsets in activity before the earliest change in
EMG activity were compared. These percentages were 34%
for the SMA, 24% for MC, and 5% for the putamen.
In addition to comparing the lead times between these
areas for all cells with movement-related activity, we also
compared the lead times between these areas for cells with
different categories of movement-related
activity. Response latency histograms of passive and active directional
Passive
Directional
Cells
260
140
6
-ire
-i80
v)
z!
280
140
0
- 140
-280
6
Active
Directional
Active
Directional
Cells
11
-280
2
zho
IlO
b
-iSO
Muscle-like
Muscle-like
-1'40
Lead
time
(ms)
FIG. 9. Onset latency histograms for passive and active directional cells
and muscle-like cells in the SMA. The onsets of activity in active directional cells were significantly earlier than the onsets in muscle-like cells.
Lead
time
(ms)
FIG. 1 1. Onsets of movement-related
activity in these different classes
of directional and muscle-like cells were not significantly different in putamen.
M. D. CRUTCHER
160
AND G. E. ALEXANDER
cells and of muscle-like cells with dynamic load effects in
the SMA, MC, and putamen are shown in Figs. 9-l 1, respectively. The statistics are shown in Table 7. Just as for
all cells with movement-related
activity, within categories
of cells the SMA was significantly earlier than the MC,
which was significantly earlier than the putamen (P values
are shown in Table 7). The only exception was that the
difference in lead times between the dynamic muscle-like
cells in the SMA and MC was not significant.
In addition to comparing the relative times of activation
between different structures, we also compared the lead
times of different categories of cells within structures. For
example, if the directional movement-related
activity of
some cells was because of sensory feedback during the
movement, then one might expect these cells to have later
lead times than directional cells without sensory driving.
The response latency histograms for passive and active directional cells in SMA, MC, and putamen are shown in
Figs. 9- 11, and the means and medians are shown in Table
7. The responses of most passive directional neurons occurred after the onset of movement. The earliest lead time
for these cells was 63 ms. However, the latency difference
between the active and passive directional cells was not
statistically significant for either the MC or putamen (P
values not shown). The t test for the SMA was not done
because of the paucity of passive directional cells in our
sample.
There is a related question concerning the relative timing
of response onset latencies for different categories of
neurons. If active directional activity represents a command signal for the direction of movement, which is logically antecedent to a command related to muscle activation patterns (see Fig. 1 of Alexander and Crutcher 1990),
then one might expect active directional cells to have earTABLE
SMA
MC
Putamen
53
53 ms
1
-16 ms
-14-+ 16ms
13
-53 ms
-69& 18ms
17
[ P < 0.05 ]
Active directional cells
Median, ms
Mean, ms
n
83
76 +_ 8 ms
23
[ P<O.OOl
25
15 _+ 15 ms
21
1
C
]
-13 ms
-40 t 10 ms
93
[ P<O.OOl
P < 0.001
[
Dynamic muscle-like cells
Median, ms
Mean, ms
n
23 ms
17+ 11 ms
42
NS
50 ms
35 + 10 ms
34
1
P < 0.05
]
1
-21+
DISCUSSION
Neuronal activity related to the direction of limb movement (directional cells), independent of the associated pattern of muscle activity, was found in all three motor areas
examined in this study. In addition, however, neuronal
activity that appeared to be related to the pattern of muscle
activity (muscle-like cells) was also found in all three structures. The fact that large proportions of both types of cells
were found in all three motor areas suggests that neural
representations of both of these levels of motor processing
may be distributed throughout the basal ganglia-thalamocortical motor circuit. This finding does not imply that the
SMA, MC, and putamen are functionally equivalent. Clear
differences between these motor areas have been described
(Kurata and Tanji 1985; Okano and Tanji 1987; Tanji and
Kurata 1982; Tanji et al. 1980). However, the fact that
processes as fundamental as the specification of movement
direction and muscle activation patterns appear to be so
widely distributed argues against a strictly hierarchical organization of the motor system and suggests that the degree
of functional localization within the motor system (i.e., the
control of a given motor function by a single motor area)
may be less than is commonly assumed.
Activity coding movement direction
7. Lead times of directional and muscle-like cells
Passive direct ional cells
Median, ms
Mean, ms
n
lier lead times than muscle-like cells. This expectation was
only partially borne out by our data. The response latency
histograms for the muscle-like cells in SMA, MC, and putamen are also shown in Figs. 9- 11, respectively, and the
means and medians are in Table 7. For the SMA, the lead
times of active directional cells were significantly earlier
than those for the muscle-like cells (t test, P < 0.001). In
contrast, for the MC and putamen the difference was not
statistically significant for either area (P values not shown).
-5 ms
9ms
43
[ P < 0.001 ]
I
Values are means + SE. Abbreviations, see Tables 1 and 2. *Includes
muscle-like cells with dynamic load effects.
Many previous studies have described neuronal activity
that was related to the direction of limb movement in the
SMA (Tanji and Kurata 1982), MC (Evarts and Fromm
1978; Evarts and Tanji 1976; Fetz et al. 1980; Georgopoulos et al. 1982, 1985, 1989; Kalaska et al. 1983; Kubota
and Funahashi 1982; Lamarre et al. 1983; Murphy et al.
1982; Schmidt et al. 1975; Schwartz et al. 1988), and putamen (DeLong 1973; Kimura 1986; Liles 1979, 1985; Liles
and Updyke 1985). However, because muscles are inherently directional, in all of these studies the pattern of muscular activity covaried with the direction of limb movement, making it impossible to determine whether directionally selective neuronal responses were related to
movement direction per se or to force or muscle pattern.
However, a few studies have dissociated these variables by
the use of opposing and assisting loads. The earliest studies
of this type were carried out in the MC and strongly emphasized the relation of neuronal activity to muscular force
(Conrad et al. 1977; Evarts 1967, 1968, 1969). Nevertheless, each of these early reports mentioned that neurons
had been found whose activity was directional and unaffected by the loading conditions. The activity of a small
proportion of pyramidal tract neurons and most corticorubra1 neurons in the MC has been reported to be unrelated
MOVEMENT-RELATED
ACTIVITY
to different static loads (Fromm 1983a). More recently, a
preponderance of directional over muscle-like cells with
movement-related activity has been described in the putamen (Crutcher and DeLong 1984a) and in the globus pallidus (Mitchell et al. 1987). A recent study using a two-dimensional tracking task in the MC has also described cells
with directional activity with little or no dependence on the
inertial load (Kalaska et al. 1989). The results of these
recent studies and the present study suggest that directional
movement-related activity, independent of muscle activity
patterns, is much more abundant and widespread than earlier studies had suggested.
In the present study we found approximately equal proportions of directional and muscle-like cells in both SMA
and MC, whereas the proportion of directional cells in the
putamen was more than twice that of muscle-like cells.
These results could be an indication that the putamen preferentially receives inputs from directional neurons in the
cortex. However, the fact that 52% of cells in the putamen
were classified as directional compared with 38-4 1% for
the cortex does not necessarily mean that there is a fundamental difference between the putamen and cortical motor
areas. It is possible that some cells in the putamen had load
effects that were too weak to be detected with the relatively
conservative probability level that was used in the present
study, because movement-related activity in the putamen
was generally less robust than that in either the SMA or
MC. A recent study of single-unit activity in the putamen
(Liles 1985) found that for 59% of cells the movement-related activity increased with increasing magnitudes of opposing loads, and that 4 1% of cells were unaffected by the
loads (up to 0.2 Nm). These proportions are comparable to
those for the SMA and MC in the present study. This suggests that, although it is possible that the basal ganglia are
less involved in the specification of the dynamics of movement than the SMA and MC, this conclusion must remain
tentative pending further study.
There are several possible roles that directional cells
might play in the control of movement. The activity of
these cells could represent an intermediate
step in the
transformation that the motor system performs to translate
the spatial location of the target or goal of the movement
into the muscle commands necessary to accurately reach
that goal. The directional cells might therefore be thought
of as representing either the trajectory or the kinematics of
the movement. Some of the directional movement-related
activity may represent the neural correlate of a command
signal for the direction of limb movement and might be
involved in movement initiation. This possibility would be
most plausible for cells whose activity begins well before
the onset of movement. Directional cells with relatively
late onsets of discharge could be receiving a corollary discharge of such a command signal. This could be used either
for on-line error correction during the movement or for
comparison of the intended movement with the final outcome. The activity of directional cells that began to discharge after the onset of muscle activity might also have
been driven by proprioceptive feedback associated with the
active movement.
To determine whether the directional movement-related
responses that were load independent could be accounted
IN
THREE
MOTOR
AREAS
161
for by proprioceptive inputs activated during movement
execution, we analyzed the responses of these cells to the
application of torque loads. If there was a short-latency
response (~60 ms) to the load applications, the cell was
judged to be passively driven and was therefore categorized
as a passive directional cell. Otherwise, the cell was labeled
as an active directional cell. The overwhelming majority of
directional cells in all three motor areas (79-94%) were
judged to be active directional cells. It is possible that we
underestimated the number of directional cells with passive driving because the load application may not have
been effective in activating all receptors that were driven
during the active limb movements. However, we believe
that the torque application was a reasonably effective probe
for proprioceptive input, because the resulting peak velocity induced by torque application was approximately twice
that of the active movement associated with side target
capture. Thus, if a cell had been receiving directional somatosensory input during the active movement, it should
also have been activated by the torque application, especially given the evidence that somatosensory information is
generally suppressed during active movements (Coquery
1978; Coulter 1974; Starr and Cohen 1985). The lack of
evidence of proprioceptive inputs to the active directional
cells should not, however, be construed as evidence that
these motor areas do not receive proprioceptive input. A
significant percentage of neurons in the MC (Fetz et al.
1980; Lemon and Porter 1976; Rosen and Asanuma 1972;
Wong et al. 1978) and putamen (Alexander and DeLong
1985; Crutcher and DeLong 1984b; Liles 1985) and a modest number in the SMA (Brinkman
and Porter 1979;
Hummelsheim et al. 1988; Wise and Tanji 198 1) respond
to somatosensory stimulation. In the present study less
than one-half of our total sample of movement-related cells
(SMA, 36%; MC, 32%; putamen, 44%) were judged to be
active directional cells without apparent proprioceptive
driving. Moreover, we selected cells for study only if they
were related to active movement. This may well have excluded some cells with somatosensory driving that were not
active during voluntary movements.
Muscle-like activity
Neurons with patterns of activity similar to those of
muscles were found in each of the three motor areas examined in this study. This is consistent with the large number
of studies that have described neural relations to muscular
force (Cheney and Fetz 1980; Conrad et al. 1977; Crutcher
and DeLong 1984a; Evarts 1967, 1968, 1969; Evarts et al.
1983; Fromm 1983b; Fromm and Evarts 198 1; Hepp-Reymond et al. 1978; Kalaska et al. 1989; Kalaska and Hyde
1985; Liles 1985; Mitchell et al. 1987; Schmidt et al. 1975;
Smith 1979; Smith et al. 1975; Thach 1978). Such musclelike activity may represent a neural correlate either ofjoint
torque or of the specification of muscle activation patterns.
No attempt was made to dissociate these two variables in
this experiment. However, like the directional cells, some
of the muscle-like cells became active quite late in the reaction time or even after the onset of movement. Their activity was therefore unlikely to represent a command signal
for the generation of a calculated joint torque or the acti-
162
M.
D.
CRUTCHER
AND
vation of a specific muscle. These cells might have been
receiving a corollary discharge of a command signal to
muscles. Alternatively, muscle-like cells with late onsets
might be receiving muscle-like feedback from the periphery.
Relative timing ofmovement-related
activity
This is the first direct comparison of single-cell activity in
SMA, MC, and putamen. By examining all three structures
in the same study, we hoped to be able to make more valid
comparisons among them. We found that the average lead
time in the SMA was before that in the MC, which was
before that in the putamen. These timing differences were
consistent with previous work. In studies that directly
compared the SMA and MC, it was reported that the
movement-related activity in the SMA began earlier than
that in MC (Okano and Tanji 1987; Tanji and Kurata
1982). Also, previous studies that examined only one
motor area have strongly suggested that movement-related
activity in the striatum (Crutcher and DeLong 1984a; Liles
1985) and globus pallidus (Anderson and Horak 1985)
began later than that in the MC (Georgopoulos et al. 1982,
1989; Murphy et al. 1982; Thach 1978). The onsets of
movement-related
activity observed in the present study
were generally later than those reported in the previous
studies of these motor areas. For example, in the present
study the median lead time for the MC was 3 1 ms, whereas
two previous studies of the MC found median lead times of
54 ms (Thach 1978) and 110 ms (Georgopoulos et al.
1982). Similarly, in the present study the median lead time
for the putamen was - 13 ms, whereas a previous study of
the putamen found a median lead time of 15 ms (Crutcher
and DeLong 1984a). These latency differences may have
been because of differences in the techniques used to determine the response onset latency for each cell. We determined the onset latency for each trial in the cell’s preferred
direction and used the median of single-trial lead times as
the latency for that cell. This approach will obtain a later
onset latency than any technique based on determining the
time of onset of the earliest trials, such as the commonly
used method of examining the histogram of all trials.
Which of the two techniques is preferable is unclear.
The fact that neuronal activity was studied in three interconnected motor structures provided a unique opportunity to address the issue of serial versus parallel processing
within the basal ganglia-thalamocortical
motor circuit.
Superficially, the significant differences in average lead
time among the three structures suggest that there may be
some degree of sequential processing from the SMA to MC
and thence to the putamen. This is consistent with the
commonly held view that the SMA is at or near the “highest” level of the motor system (Eccles 1982; Kurata and
Tanji 1985; Mann et al. 1988; Roland et al. 1980; Tanji
and Kurata 1985). However, the timing data obtained in
this study are difficult to reconcile with the concept of
strictly serial processing within the motor system. Although
the mean lead times for the SMA, MC, and putamen were
significantly different, the degree of overlap of the distributions was striking. This, together with the fact that the
durations of the movement-related
activity were often
G. E. ALEXANDER
quite long, indicate that many directional and muscle-like
cells in all three areas were active simultaneously. Overall,
then, the results presented here strongly suggest that multiple levels of motor processing proceed in paralle/ within
each of the three motor areas examined in this study. Recently, Hyland et al. (1990) reached similar conclusions
after comparing movement-related
neuronal activity in
SMA and MC.
The software
employed
in this study was developed
by F. H. Baker and
R. G. Cutler.
M. R. DeLong
provided
helpful comments
on the manuscript. Technical
assistance
was provided
by L. H. Rowland.
B. A. Zuckerman assisted in the preparation
of the manuscript.
This work was supported
by National
Institute
of Neurological
Disorders and Stroke Grant NS-17678.
Address
for reprint
requests:
G. E. Alexander,
Dept. of Neurology,
Meyer 5- 185, Johns Hopkins
University
School of Medicine,
600 N. Wolfe
St., Baltimore,
MD 2 1205.
Received
24 April
1989;
accepted
in final
form
15 February
1990.
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