Activity of primate precentral neurons during voluntary movements triggered by visual signals

Brain Research, 236 (1982) 429-449 Elsevier Biomedical Press

429

ACTIVITY OF PRIMATE PRECENTRAL NEURONS DURING VOLUNTARY MOVEMENTS TRIGGERED BY VISUAL SIGNALS

J. T. MURPHY, H. C. KWAN, W. A. MacKAY and Y. C. WONG

Department ofPhysiology, University of Toronto, Toronto, Ontario M5S 1 A8 (Canada)

(Accepted August 13th, 1981) Key words: primate motor cortex - precentral neurons - voluntary movements

SUMMARY

Awake, intact monkeys were trained to perform discrete flexion or extension movements of the hand about the wrist in response to visual signals. The object of the movement was to align a cursor, coupled to a manipulandum, on a target line. Cursor and target lines were displayed on a video monitor placed in front of the monkey. The target line was stepped to the right or left, randomly with regard to direction and timing, with each step implying an instruction for the monkey to make a voluntary movement for alignment. Single unit recording was made in the forelimb area of contralateral precentral cortex. Neurons were classified by their responses to passive sensory stimulation and the effects of local intracortical microstimulation into two populations: wrist flexion-extension (F-E) neurons, and all other forelimb neurons (non-wrist (F-E)). A significantly higher proportion of wrist (F-E) neurons as compared to non-wrist (F-E) neurons were task-related. Moreover the wrist (F-E) neurons exhibited exclusively reciprocal responses to the oppositely directed visual signals, whereas the non-wrist (F-E) neurons showed both reciprocal and bidirectional responses. No significant differences in mean latencies of responses, either in respect to the visual signals or to movement onset, were observed between the two populations of neurons. However the range oflatencies in both instances was greater in the non-wrist (F-E) populations. The wrist (F-E) population showed significantly less response variability than the non-wrist (F-E) population with regard to response latencies to visual signals and movement onsets, and the degree of correlation between duration of response and reaction time.

INTRODUCTION

There have been a number of studies correlating neuronal activities in primate 0006-8993/82/0000-0000/$02.75 © Elsevier Biomedical Press

430

motor cortex with voluntary movement in the context of a visual stimulus. Of particular interest is the demonstration by Evarts 2-4, later confirmed by Yumiya 24 , that neurons in motor cortex modify their discharge activity about 100 ms after a visual signal, and about 100 ms prior to the onset of voluntary movement (EMG) triggered by this signal. Such cells respond differently depending on the information content of the signaI 6 ,lO,20. In addition, cortical responses to the visual signal may occur without subsequent change in the EMG20. Interpretation of these studies is complicated, however, by a fundamental problem in the correlation of motor cortical activity and movement parameters. Muscle contractions performed by a trained monkey are not restricted to a single joint, even when the movement paradigm has been designed for that purpose. In general, the occurrence of movements about a distal joint is preceded and accompanied by a fixation of more proximaljoints18 . Thus cortical activity not directly related to movement about a particular joint may still be intimately involved in the total act. If motor cortex is organized into regions controlling single joints, then functional analysis of unit discharge requires identification of the controlled joint. Given the extensive population of muscles, acting at different joints, involved in any motor task, this identification cannot be made simply on the basis of a temporal correlation of neuronal activity with movement parameters, or even with EMG activity. Neurons in the forelimb area of primate precentral cortex are organized into populations which are functionally coupled to the peripheral musculature in such a way as to provide a major component of the control of position of limb parts about single, forelimb joints. The constituent cells of these populations are spatially contiguous, in the horizontal and vertical domains, to form clusters. The functional coupling of these clusters to single joints has been defined in terms of two independent criteria; responses of the constituent cells to somatosensory input, and the effects of intracortical microstimulation (ICMS) on motor output l l ,14,21. These bases for identification of a cluster with a particular forelimb joint suggest, but do not prove, a preferential role for the clusters in voluntary movement involving the same joint. In a series of recent studies, we have investigated the possibility of a preferential role for these clusters in the genesis of a voluntary movement occasioned by a somatic stimulus to the forelimb. This stimulus was in the form of a torque pulse delivered in such a way as to cause flexion or extension of the wrist. The monkey was trained to produce a restorative movement of the hand about the wrist. These studies showed that neurons defined by passive somatosensory stimulation and ICMS as 'wrist' cells, as contrasted with non-wrist forelimb cells, were preferentially utilized in this task. This conclusion was based on the proportions of cells responding 22 , the number of cells exhibiting reciprocal patterns of response to oppositely directed torques 15, and the temporal variability of the responses in the wrist and non-wrist populations respectively23. The present study examines the behavior of such clusters of cortical cells in a different context, in which a voluntary movement occurs in response to a purely visual stimulus. Also of relevance to the present study is the possibility that 'wrist' and 'nonwrist' populations of neurons, as defined by ICMS, exhibit different, although

431

overlapping, temporal characteristics in the context of visually triggered movements of the hand about the wrist 24 . METHODS

Task description The two stump-tail monkeys (Macaca arctoides) used in this study were trained to grasp a manipulandum attached to the shaft of a torque motor and to perform a visually guided voluntary movement requiring flexion and extension of the hand about the wrist. A moulded cast was placed about the animal's forearm, which restricted movements other than flexion and extension. A vertical target line was displayed on a video monitor I m in front of the animal. A square cursor was also displayed on the video monitor, and the horizontal position of this cursor was controlled by the manipulandum such that a zero angular displacement at the wrist corresponded to a central position of the cursor on the screen. The position of the target line was controlled by computer. The monkey's task was to keep the cursor superimposed on the target line, by appropriate flexion and extension movements about the wrist. The target line was moved at random times in steps either to the left or to the right, with direction chosen randomly, such that a voluntary movement of 15° of flexion or extension was required for realignment. The animal, which thus had no prior knowledge of the time or direction of the applied visual signal, was required to make a correct movement within I s of the signal. No mechanical stops were used. Instead, a small amount of viscous damping was provided by the motor to reduce overshoot. An attempt was made to achieve control over the animal's behavioral and central brain state in the following manner. The video screen was initially blank. At random times the target line and cursor appeared on the screen, signifying the onset of the preliminary period (Fig. 1). The animal was trained to align the target line and cursor. After alignment was successfully completed, the target line was stepped to the center of the screen, requiring a second alignment of target and cursor. Data collection was initiated during this second holding period, which acted as a control recording period for cellular activities. After this control period, which had a randomly variable duration of at least 1 s, the test visual signal was applied in random fashion as described above. The animal was required to hold on target during the test period for a variable period of at least 2.5 s from the initial signal. Thus the animal's behavioral state with respect to forelimb motor control was always the same prior to the onset of each test trial. Recording After the animals were fully trained, a chamber was implanted under sterile operative conditions with the animal fully anesthetized. The implantation was placed such that daily recordings could be made over the forelimb area of motor cortex. The methods of surgical implantation have been fully described previously2,22. Recording was carried out in each monkey for about 3 h per day over a period of about 10 months. Glass coated platinum-iridium microelectrodes were used for

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recording. These had impedances of about 0.5 Mil measured at 1 kHz. Units were isolated with a voltage discriminator and sampled at 1 msec intervals by computer. Manipulandum position and velocity were sampled at 10 ms intervals. During some recording sessions, hOlizontal eye movements (EOG) and the electromyogram (EMG) of various forelimb muscles were recorded, using intramuscular wire electrodes. Classification of neurons Each neuron was classified as being functionally coupled to a single forelimb joint, utilizing previously developed criteria involving responses both to passive sensory examination and to ICMS applied to the locus of recording14 • For example wrist (F) neurons were defined as those which responded to passive extension at the wrist, and which upon ICMS at the same locus produced a flexion movement about the wrist joint. Non-wrist (F-E) neurons were lumped into a single set which included shoulder, elbow, wrist (other than flexion or extension), and finger (and thumb) neurons. The entire forelimb area was systematically and extensively explored in each monkey, in an effort to reduce sampling bias. Histology When all experiments from a monkey were completed, small electrolytic lesions were made at various recording sites 21, using the same X-Y coordinate system that

433

had been used for recording. Frozen serial sections of cortex, 60 ,um in thickness, were made at 240 ,um intervals and stained with cresyl violet. Recording sites were reconstructed on the basis of these data. Data analysis The analysis, the same as that in our previous studies 13 ,22,23, was designed to test for differences in response variability of the two populations of neurons in motor cortex: wrist (F-E) and non-wrist (F_E)1l,14,21. For a particular cell, an excitatory neuronal response was determined from a peristimulus time histogram (PSTH) containing more than 10 trials, and was defined as one in which two or more consecutive 10 ms bins each contained a number of discharges exceeding 2 standard deviations (SD) above the mean number of discharges per bin in the control period prior to the stimulus. In cases of inhibition, 2 SD below the mean background activity was used as a criterion of significance. If the modification of cortical discharges passed the above test, the cell was classified as a responsive or task-related neuron. Response variability was defined by 3 criteria. Firstly, a response index, P, was defined as the number of responsive trials divided by the total number of trials. Secondly, among responsive trials the timing of the onset of each burst varied. The onset time of response in each trial was defined by the onset of the first spike in the response. The onset times of each trial were used to compute the mean onset latency, Xs and Xm , for all trials with respect to the sensory event and with respect to the onset of the subsequent voluntary movement, respectively. Corresponding standard deviations, SD s and SD m respectively, were also computed. Thirdly, variability in spike train response duration was assessed. The definition of the exact onset of inhibition always poses difficulties in extracellular unit studies. We arbitrarily chose the time of the occurrence of the last spike as the onset time for inhibition, although this measure provides only an estimate of the actual onset time. Other possible measures were found not to offer any particular advantage in the present study. RESULTS

Analysis of behavioral responses For the present paradigm, it was convenient to use as an index of movement response in each trial the time at which the velocity trace became non-zero (V",) following the visual signal (Figs. 1 and 2). Very small and unsustained fluctuations of the velocity trace were excluded by a simple algorithm, the effectiveness of which was verified in each case by inspection. A distribution of V", for all trials (n = 3915) is shown in Fig. 2. The mean behavioral reaction time was 220 ± 45 ms. Less than 1.5 % of the V", values were greater than 310 ms. These latter, relatively long latency trials were not included in the following comparisons of response properties between the wrist (F-E) and non-wrist (F-E) populations. Characteristic activities of the agonist and the antagonist muscles during the task are shown in Fig. 3, which displays in raster form the firing of single motor units during experimental trials together with the associated movement records. These data show

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Fig. 2. Relative frequency histogram of reaction time, Ve , which is defined as a change of velocity from zero value. Ve values over 310 ms are contained in the shaded bin. Bin size, 10 ms; X, mean; sd, standard deviation; S, onset of visual instruction signal. At the top of the histogram plot are indicated both the target position (dotted line) and the handle position (solid line). In a successful trial, these two lines overlap each other during most of the trial, as shown.

the expected reciprocal behavior of the motor units, which are activated in the agonist mode and inhibited in the antagonist mode. Occasionally the inhibition seen during antagonist action is followed by a moderate excitation (Fig. 3A, right panel). This following excitation would act to decelerate the limb part (hand) and stabilize it at its new position. However more often the strategy employed by the monkey involved allowing the mechanical properties of the limb to decelerate the hand, in which case no 'active' braking action was required. The mean timing of the change in EMG activity in relation to the visual sensory signal (K s ) and to the onset of movement (K m ) is indicated for each condition of Fig. 3. One interesting aspect of these characteristic timing data is that the inhibitory changes in the antagonist muscles occur at an earlier time relative to the movement onset (K m = -64 and -72 ms, lower left and upper right panels of Fig. 3) than do the excitatory changes in the agonists (K m = -29, -16). This is in agreement with previous results 4 ,7,8. This latency difference between inhibitory and excitatory changes in firing is compatible with the timing of activity changes of neurons in motor cortex which putatively control these muscles (Fig. 6). Response properties of cortical neurons The responses of the 4 neurons illustrated in Fig. 4A-D display several typical features of cells in the forelimb area of motor cortex. Firstly, each neuron exhibits a change in firing which follows the visual signal and which leads the subsequent voluntary movement. Secondly, the wrist (F) neurons (Fig. 4A, B), defined as such by direction of movement induced by local ICMS, show increased firing prior to a voluntary flexion movement, whereas wrist (E) neurons correspondingly increase their discharge rate prior to an extension movement. Of interest in this regard is the

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apparent second discharge prior to a second flexion movement in trials 1,4, 5 and 7 of Fig. 4B. The generality of such directional selectivity will be elaborated in a following section. Finally, there is a high correlation between the duration of the burst in firing and the reaction time in the case of the wrist (F and E) neurons. This is particularly well illustrated in the fifth trial from the top of Fig. 4A where the discharge is sustained throughout the unusually long reaction time. This qualitative impression of a positive correlation between burst durations and reaction times in individual trials holds true for the population of all wrist (F or E) neurons, as shown by the graph of Fig. 4E which

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437 plots these two variables for all cells. The assumption ofa linear correlation between the two variables yields a correlation coefficient of 0.51. In contrast these two variables are much less strongly correlated in the case of non-wrist (F-E) neurons (Fig. 4F). Despite the consistency of the above described relationships for wrist (F or E) neurons, a degree of trial to trial variability in this relationship could at times be observed for a particular neuron. This variability in the putative functional relationship between burst duration and reaction time was occasioned by variability in either or both the cell discharge and the behavioral response. Both types of variability are present in the individual trials in the panels of Fig. 4. An interesting, extreme example is illustrated in the second trial of Fig. 4B. In this case the typical burst in firing occurred following the visual signal, but the expected behavioral response was absent. It should be emphasized that all cortical neurons designated as wrist F or E cells did not behave exactly the same in this paradigm. For example, careful comparison between the responses of the wrist (F) cells in Fig. 4A and B reveals that the discharge onsets in the former appear more closely related to the visual stimulus onset than the movement onset, whereas the converse was the case in the latter. Various factors may be involved in these differences including most particularly how close a particular neuron is positioned to the sensory or motor end of a sensorymotor 'chain' involved in the task. For example, PT and non-PT neurons may behave differently in these regards, as pointed out by Evarts 2 with PT cells located quite near to the motor end of such a chain. Proportions of task-related neurons A central question of the present study concerned a comparison between the wrist (F-E) and non-wrist (F-E) neuronal populations in the context of the present task involving visually guided, voluntary flexion or extension movements of the hand about the wrist. One means of comparison is the proportion of task-related neurons in each population. The data relating to this question is given in Table 1. A total of 636 neurons in the forelimb area of motor cortex were adequately investigated, of which 27 % were task-related. Those neurons which showed a change in firing in association with the visual signal and/or the subsequent movement were classified as task-related. The data in Table I shows that the wrist (F-E) population contains a significantly TABLE I Proportion o/task-relatedneurons Population

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438 higher proportion of task-related neurons (50 %) than do the non-wrist (F-E) populations (24.6 %) (X 2 = 16.9: P < 0.005). Within the non-wrist (F-E) population, the constituent sub-populations show a decreasing task-relatedness in the following order: fingers, wrist (other), elbow and shoulder. Directional selectivity of responses We compared the directional selectivity of the two populations of neurons, wrist (F-E) and non-wrist (F-E). It will be noted that a movement of the target line in one direction carries with it an implied instruction for the monkey to move the handle in a particular direction, namely that which aligns cursor and target. Hence the propensity of a particular neuron to respond selectively depending on the movement direction implied by the instruction could be assessed. Characteristic responses of individual neurons are illustrated in Fig. 5. Here it can be seen that a wrist (E) neurons responded reciprocally to the oppositely-directed visual target steps (Fig. 5A). In contrast, some non-wrist (F-E) neurons responded reciprocally (Fig. 5C), whereas some others responded bidirectionally (Fig. 5B) to these oppositely-directed visual signals. Composite results for the total of 261 responses (188 excitatory (72%), and 73 inhibitory (28 %)) are shown for the non-wrist (F-E) and wrist (F-E) populations in Table II. In this table, an excitatory response in association with a flexion movement is designated f' whereas an inhibitory response prior to an extension movement about the wrist is

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440 designated '-e'. The table shows that wrist (E) neurons are active only in the extension-related condition, while the converse is true for wrist (F) neurons. Hence the neuronal responses during voluntary movement are congruent with the behavioral responses observed with ICMS. An important result of Table II is that no bidirectional responses were found among the wrist (F-E) neurons. Finally non-wrist (F-E) neurons were distributed in their responses between bidirectional and reciprocal types, as suggested by Fig. 5. Latency analysis The distributions of response latencies are shown in Fig. 6A and B. Excitatory responses are indicated above the abscissa, while inhibitory responses are below. The latency measurements are taken with respect to the visual sensory signal (Fig. 6A) and with respect to the onset of movement (Fig. 6B). When wrist (F-E) and non-wrist (F-E) populations were compared with respect to mean latencies, no significant differences were observed either when latencies were measured with respect to the visual sensory signal, or with respect to the onset of the movement (P < 0.05). This was true both for excitatory responses (t = 0.31 and t = 0.62 for Xs and Xm respectively), and for

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441 inhibitory responses (t = 0.52 and t = 0.35 for Xs and Xm respectively). In contrast to the absence of differences between the latency means for the two populations, the range of latencies did differ between the wrist (F-E) and non-wrist (F-E) populations (P < 0.05), as can be seen from inspection of Fig. 6A and B. In particular, the nonwrist (F-E) population showed a number of very long latency responses. If the neurons under study are functionally related to the task, a correlation between Xs and Xm would be necessary. Stated another way, for any given position of a neuron along the sensory-motor chain involved in this task, Xs and Xm should be variables which are dependent. The results indicate a positive correlation between these parameters in the total population of neurons, both for excitatory (Fig. 6C, r = 0.71) and inhibitory (Fig. 6D, r = 0.84) responses. This finding is compatible with the interpretation that these neurons are indeed functionally related to the task. Response variability

As defined in the Methods, response variability was assessed by 3 criteria including the response index, P, and the standard deviations for the response latencies with respect to the visual signal and the onset of the motor response, SD s and SD m , respectively. A comparison of these criteria for the wrist (F-E) and non-wrist (F-E) populations is provided in the relative frequency histograms of Fig. 7. In Fig. 7 it can be seen that the response index, P, varied between 0.5 and 1. The mean value of P for

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442 the wrist (F-E) population was 0.88, while that for the non-wrist (F-E) population was 0.85. These means do not differ significantly (for P < 0.05). The distributions of the standard deviations for the latency of the onset of response to the visual signals are shown in Fig. 7B. The means of these standard deviations were 26.8 and 33.7 ms for the wrist (F-E) and non-wrist (F-E) populations respectively. Corresponding relative frequencies of standard deviations for the latency of the motor response are shown in Fig. 7C, with means of the standard deviations being 24.5 and 33.1 ms for the wrist (F-E) and non-wrist (F-E) populations respectively. We found that the means of the values of SD s and SD m each differed between the wrist (F-E) and non-wrist (F-E) populations (P < 0.05). Two necessary conditions underly the validity of the above comparisons between

Fig. 8. Correlation of SD and X with respect to sensory events, s (A) and with respect to motor events, m (B) for the wrist (F-E) population (uppermost panels) and for the non-wrist (F-E) population (middle panels). Dotted lines show the regression lines as calculated by least-mean-squares method with resultant correlation coefficient (r) as indicated in the upper right corner of each raster display. The lowest panels show the arbitrary boundary lines enclosing most of the values of the two panels above: wrist (F-E) neurons (solid line) and non-wrist (F-E) neurons (dotted line).

443

the variability of response latencies for the wrist (F-E) and non-wrist (F-E) populations. The first is that these populations must have similar latencies. This condition is validated by the data of Fig. 6 which indicates that differences in latencies between the two populations are not significant, as discussed above. The second condition is that the two populations must exhibit a similar relationship between latency and SD. In order to gain insight into this second condition, we analyzed the relationship between SD and mean latency for both populations, both with respect to the visual sensory signal and to the motor response. The results ofthis analysis are given in Fig. 8, which shows a roughly monotonic increase (or decrease in the case of Xm ) in the SD value for a corresponding increase of the mean latency for each of two populations. The assumption of a linear relationship between the SD and X values yields correlation coefficients of about + (or -) 0.30, as indicated. These data offer support for the requirement of a similar relationship between SD and X values for each of the two populations in each of the two conditions (Fig. 8A and B). The data of Fig. 8 also provide an opportunity to determine whether the differences in SD values between the two populations, shown in Fig. 7B and C, remain true when the SD values are normalized for differences in latencies. Stated another way, are the differences in SD simply due to differences in latency between the two populations? To facilitate this analysis, arbitrary inclusive boundaries for the wrist (FE) and non-wrist (F-E) populations are provided in the lower panels of Fig. 8. This enables an estimation of slope and elevation (y-shift) for the distributions, both of which must be considered in order to determine whether SD values for a given latency differ between the two populations 16 . If either slope or elevation differ, one may conclude that the SD values for a given latency differ between the two populations. When this comparison is made, it is found that the differences in slopes between the populations are not significantly different in either the SD s or SDm cases (P < 0.05). In contrast, the elevations of the slopes do differ significantly in each case (P < 0.005). Thus the observed differences in SD are not simply due to latency differences between the two populations, and must represent intrinsic differences in probabilistic behavior for each population. Spatial arrangements To study the spatial distribution of cells, the location of each cell was plotted on a two-dimensional surface map of precentral cortex 21 . This map is unfolded about the Rolandic sulcus, in order that the horizontal distribution of all cells could be determined. The locations of all task-related cells, wrist (F-E) and non-wrist (F-E), for one of the two monkeys are shown in Fig. 9A. The task responsive wrist (F-E) cells are loosely clustered in the more medial portions of the forelimb region of precentral cortex. This clustering is also evident in Fig. 9B, which plots the locations of taskrelated and non-task-related wrist (F-E) cells. The map for the second monkey was similar. Although not shown in the map, we also observed that flexion-related and extension-related neurons were in some instances located contiguously, thus confirming the findings of previous studies1,lO.

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Fig. 9. Horizontal location of neurons in forelimb region of precentral cortex for one of the two monkeys. Conventions describing the method of unfolding of cortex have been described previously (ref. 20). The location of cells in the depths of cortex is determined with reference to the orthogonal, radially oriented fibers of cortex. Solid line at the right of each panel indicates the bottom of the central sulcus, and represents 10 mm. The middle of the three vertical dashed lines indicates the top of the central sulcus. The remaining two vertical dashed lines divide this part of cortex into the 3 cytoarchitectonic areas: 3a, 4 and 6. A: the location of all task-related cells. Filled circles represent wrist (F-E) cells, and plus symbol represents non-wrist (F-E) cells. B: location of all wrist (F-E) cells only. Filled circles indicate task-related cells, and open circles indicate non-task-related cells. DISCUSSION

M ethodologic considerations

Interpretation of the timing of changes in neuronal activity in precentral cortex requires control of the behavioral response, which may vary from trial to trial. In the case of very large variations in a response, this control was achieved by aborting both the trial and subsequent data collection. In the great majority of trials variation at the output was not very large, in respect either to EMG activity in agonists and antagonists acting at the wrist (Fig. 3) or to the actual timing of the movement itself (Fig. 2). Greater than 98 % of reaction times fell within an homogeneous population, with a range of 160-310 ms, and a mean of 220 ± 45 ms. Those few trials falling outside this population (Fig. 2) were excluded from the comparison of response properties between wrist (F-E) and non-wrist (F-E) populations. A comparison between the two neuronal populations may not be valid in the case of these very long latency reaction times, since a variety of factors other than the visual signal or the voluntary movement may be involved in the responses of either or both populations in such cases. Response latencies

The mean latencies of cortical cell responses to the visual signals were 170 ± 40 ms, for both wrist (F-E) and non-wrist (F-E) forelimb neurons. There are no similar latency studies of the behavior of a comparably large population of precentral neurons. However this value of 170 ms (Xs , Fig. 6A) compares favorably to that observed by Evarts under similar conditions 2 - 4 • Similarly, the latency of cell firing

445 with respect to onset of movement, -50 ± 44 msec (Km , Fig. 6B), corresponds closely to that observed in previous studies 2 - 4 ,24. These values, taken together with the positive correlation between K s and Km (Fig. 6C, D), serve to emphasize the intimate relationship at precentral cortex between information related to visual sensory events, and subsequent motor events. Thus as the latency to the visual input increases, that to the motor event decreases, and conversely: in either case the change in activity of the precentral neurons characteristically falls between the sensory and motor event. Similar relationships have been observed in cases where the sensory perturbation arises in somatic structures 23 • However, the mean latency of precentral responses following somatic perturbations is much shorter (about 50 ms) than that following visual signals, whereas the latency to the motor event is somewhat longer (about 95 ms). These differences undoubtedly reflect different input and output processing mechanisms in the two situations. One interesting aspect of the latency data concerns the differences in ranges of both Ks and Km between wrist (F-E) and non-wrist (F-E) populations (Fig. 6A, B). It has already been pointed out that some of the very long latencies for both Ks and Km (right side of frequency distributions in lower panels of Fig. 6A, B) may be indicative of cellular activity changes which are not directly related to the visual signal or to the motor event. However it is important to note that those muscles not involved in wrist flexion or extension themselves exhibit greater variability in terms of timing of the EMG activity than do the wrist flexors and extensors in this kind of task 12 ,23. Hence the broader range of latencies in the non-wrist (F-E) precentral neurons is compatible with a functional relationship between these neurons and those forelimb muscles other than wrist flexors or extensors. If, as the data suggest, the neurons designated wrist (F-E) are indeed functionally coupled to wrist flexor or extensor muscles during this task (cf. following), then it is relevant to compare the latencies ofexcitatory responses to those ofinhibitory responses It can be seen that the inhibitory responses occur at a shorter latency (Fig. 6A, B, upper panels). Under the not unreasonable assumption that some of the neurons exhibiting these inhibitory responses serve to control activity in antagonists, one would expect earlier inhibition in the antagonists relative to the excitation in the agonists, in the course of the task. Such a difference in timing ofthe EMG activity was in fact present (Fig. 3), and has also been previously observed in different contexts in both primates 4 and man (refs. 7, 8). Hence our observation of a shorter latency for inhibitory neuronal responses may constitute a cortical substrate for the observed timing pattern of EMG activity. Proportions of task-related cells Movement of the hand about the wrist joint is of primary importance in the successful execution of the present task. Gripping of the manipulandum with fingers and thumb, elbow fixation and shoulder fixation are, in descending order, of secondary importance. These intuitive interpretations concerning behavioral aspects of the task are sustained by consideration of the degree of variability of the EMG activity in various muscles, as discussed above 24 . If activity in the population of wrist (F-E)

446 neurons is functionally related to wrist flexion or extension, one would thus predict for the present task a higher proportion of task-related cells in this population as compared with the non-wrist (F-E) population. This prediction was affirmed (Table 1). Moreover, as expected from these considerations of behavioral aspects ofthe task, the constituent subpopulations of the non-wrist (F-E) population showed a decreasing degree of task relatedness in the order: fingers, wrist (other than F-E), elbow and shoulder. Relationship ofprecentral activity to direction of visual target step In the present task voluntary movements were required in either the flexion or the extension direction about the wrist. Hence it might be expected that the activity of wrist (F-E) neurons would exhibit directional selectivity in their responses to oppositely directed steps of the visual target. The reason for this expectation is that movement of the visual target line in a particular direction carries with it an implied instruction for movement of the handle in a particular direction, that which moves the cursor towards the target. The data indicate that the wrist (F-E) neurons showed exclusively reciprocal responses to the oppositely directed visual disturbances (Fig. 5; Table II). In contrast, neurons in the non-wrist (F-E) populations exhibited both reciprocal and bidirectional responses, in keeping with the largely joint stabilizing activities of the muscles which are putatively controlled by these neurons. Reciprocal and non-reciprocal neurons, which were not identified with respect to parts of limb, were observed in the post-arcuate area in a similar tracking paradigm 10 . Our observations in the rostral precentral cortex (Fig. 9) are in congruence with this finding. A similar distinction in directional selectivity between wrist (F-E) and nonwrist (F-E) neurons has been noted in a non-visual task, namely one in which the instruction to flex or extend at the wrist is implied by the direction of a torque applied at the wrist 15 . Response variability ofprecentral populations Because of the fact that forelimb muscles other than the principal agonists and antagonists exhibit greater temporal variability in activity in this type oftask 12 ,22, it is of interest to compare the variability of activity of the wrist (F-E) population of precentral neurons to that of the non-wrist (F- E) population. Two of the 3 independent measures ofvariability which were assessed differed significantly between the two populations, with the wrist (F-E) population showing less variability. These include the standard deviations ofthe mean latencies with respect to the onset ofthe visual sensory signal SD s (Fig. 7B) or of the motor event, SDm (Fig. 7C), and the correlation between burst duration in the spike trains precentral neurons and reaction times (Fig. 4E, F). These findings add to the other evidence presented that the activity in the wrist (F-E) population may be functionally related to the activity of wrist flexor and extensor muscles during this voluntary movement. One conclusion which emerges from the data is that latency of responses of precentral neurons does not serve to uniquely identify functional relationships between these neurons and particular forelimb muscle groups (Fig. 6); for example,

447 Fig. 6 shows considerable overlap between latencies of wrist (F-E) and non-wrist (F-E) populations with respect to both the visual sensory event and the motor activity. For this reason measures of latency variability such as those employed in the present analysis are helpful in the assessment offunctional relationships for these populations. In this regard it is interesting to note that differences in SD s and SPm values between the two neuronal populations remain significant even when SD values are normalized for variations in latency (Fig. 8). These observations concerning the usefulness of latency variability of neuronal responses, as opposed to latency alone, as additional measures of functional relationships, would appear to be generally applicable, as similar findings arise in cases in which a voluntary movement is elicited following a somatic perturbation 23 • We may infer from the present and previous 9 ,14 data that the forelimb area of precentral cortex consists of ensembles of neurons which provide large numbers of descending inputs to segmental control centers for forelimb muscles, which in turn control limb parts about single joints during voluntary movement. In considering the significance of this observation, it is interesting to observe that theoretical studies have demonstrated that input uncertainty can be reduced by having a larger number of input lines, and that this reduction is improved when the activity in the individual lines is relatively uncorrelated, i.e. subject to random fluctuations 17 • Possibly the control process has evolved in such a way as to utilize such ensembles of neurons within the forelimb area of precentral cortex for particular functions, including the control of limb movement about a single joint14 • Spatial arrangements The above considerations concerning the possibility that functional ensembles of neurons are functionally correlated with forelimb movement make it of considerable interest to analyze the spatial arrangements of such ensembles. The data of Fig. 9A show that wrist (F-E) cells which are related to the visually instructed movement task are loosely clustered mainly in the medial portions of the forelimb area (Fig. 9A). This clustering is by no means exclusive, with the illustration showing a modest degree of interdigitation of wrist (F-E) and non-wrist (F-E) cells. Spatial clustering of neurons with different functional properties has also been observed in precentral cortex in other experimental contexts 19 • Fig. 9B is also instructive with regard to the spatial arrangements. This figure shows a ring-like arrangement of all wrist (F-E) cells, as previously observed 14 • The present data of Fig. 9B add the possibility that specific functions may be spatially partitioned within such a ring-like arrangement. For the present task, the putative mediators of the visually instructed movement are located in the more medial and, to a lesser extent, rostral and caudal portions of the ring. The specific functions of the remaining wrist (F-E) cells in this ring (open circles), defined as such by responses to passive sensory stimulation and to ICMS, are unknown. Although these cells whose activity is not correlated with the present task probably share common output connections with the task-related cells, as judged from ICMS data, their input connections are evidently not identical. This leads to the suggestion that the activities of these

448 cells might be correlated with flexion or extension about the wrist in a different context (ref. 23). Such a different context might involve the same or different sensory channels. Other techniques, particularly spike-triggered averaging 5, might be helpful in inferring such postulated corticomotoneuronal connections in future studies. ACKNOWLEDGEMENTS

We express our gratitude to Mr. H. Nguyen-Huu for his computer expertise in the control of experiments and data acquisition. This work was supported by the Medical Research Council of Canada Grant MT-4140.

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