The premotor cortex and nonstandard ... - Semantic Scholar

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The premotor cortex and nonstandard sensorimotor mapping1 S.P. Wise, G. di Pellegrino, and D. Boussaoud

Abstract: We often gaze at and attend to an object while preparing to reach toward and grasp it, and continue doing so when the plan is executed. Elaborate machinery, much of it in the brainstem and spinal cord, provides control systems for the spatially congruent guidance of the eyes, limbs, and body toward targets in visual space. We will use the term standard mapping for the sensorimotor transformations that underlie such behavior. Despite the commonsense character of standard mapping, the targets of gaze, attention, and reaching can be dissociated from each other. We can attend to stimuli in locations that differ from the target of action. We can gaze in one direction while reaching in another. And we can guide spatial action with nonspatial stimuli, such as when, in conditional motor tasks, the color of an object instructs a movement elsewhere in space. All of these situations, and many others, call for a process that we term nonstandard mapping, wherein the central nervous system must reject the commonplace correspondences among visuospatial stimuli, gaze, attention, and reaching movements. We focus in this article on the possibility that premotor cortex underlies nonstandard mapping and, therefore, the behavioral flexibility that such a process allows. Key words: premotor cortex, frontal cortex, sensorimotor mapping, behavioral neurophysiology. Résumé : Il nous arrive souvent d’observer attentivement l’objet que nous nous préparons à saisir, et ceci jusqu’à ce que notre but soit atteint. Un mécanisme élaboré, se situant principalement dans le tronc cérébral et dans la moëlle épinière, est doté de systèmes de contrôle assurant le guidage spatial cohérent des yeux, des membres et du corps vers des cibles de l’espace visuel. Nous utiliserons l’expression schéma sensori-moteur standard pour désigner les transformations sensori-motrices qui sous-tendent un tel comportement. Associées au schéma sensori-moteur, les tâches de fixation, de poursuite et de préhension peuvent néanmoins être dissociées les unes des autres. Ainsi, notre attention peut être dirigée par des stimuli situés hors du champ de la cible d’action. Nous pouvons fixer notre regard dans une direction et saisir un objet situé dans une autre. Et nous pouvons guider une action spatiale au moyen de stimuli non spatiaux, comme lorsque, dans des tâches motrices conditionnelles, la couleur d’un objet ordonne l’exécution d’un mouvement ailleurs dans l’espace. Toutes ces situations, et de nombreuses autres, font appel à un processus, que nous nommons schéma non standard, où le système nerveux central doit rejeter les correspondances habituelles entre les stimuli visuo-spatiaux, la fixation, le mouvement des yeux et les mouvements de préhension. Nous soulignons la possibilité que le cortex prémoteur sous-tende le schéma non standard et, par conséquent, la flexibilité comportementale qui lui est associée. Mots clés : cortex prémoteur, cortex frontal, schéma sensori-moteur, neurophysiologie comportementale. [Traduit par la Rédaction]

Introduction Gaze, attention, motor preparation, and action often correspond in space and time. The central nervous system, through experience, learns to produce the motor commands necessary to bring the fovea (Munoz and Wurtz 1993a, 1993b) and the hand (Burnod et al. 1992; Jeannerod 1991; Soechting and Flanders 1991; Kalaska 1991) to bear on places and objects. Received July 10, 1995. S.P. Wise,2 G. di Pellegrino,3 and D. Boussaoud.4 Laboratory of Neurophysiology, National Institute of Mental Health, P.O. Box 608, Poolesville, MD 20837, U.S.A. 1 2 3

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This paper has undergone the Journal’s usual peer review. Author for correspondence. Present address: Universita’ degli Studi di Verona, Dipartimento di Scienze Neurologiche e della Visione, Fisiologia Umana, Strada Le Grazie, 8, I-37134, Italy. Present address: Vision et Motricité, INSERM U94, 16 Avenue du Doyen Lépine, 69500, Bron, France.

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For example, the superior colliculus can be viewed as a mechanism for driving the angle of gaze to a spatial target and fixing it there. Distal teacher models (Kuperstein 1988a, 1988b; Jordan and Rumelhart 1992) illustrate one possible mechanism for learning such “standard mapping” functions, in which the visual stimulus guiding an action is the target of action. Several elegant theories have been devised for standard sensorimotor mapping (Mel 1991; Burnod et al. 1992; Bullock et al. 1993; Munoz and Wurtz 1993b). Standard mapping mechanisms surely evolved before the advent of mammals and our neocortex. Most vertebrates shift gaze and move in relation to objects. However, the behavior of advanced mammals would be unrecognizable were our behavioral repertoires so constrained. The present article explores certain aspects of more flexible behavior, which differs from standard sensorimotor mapping in one of two ways: (i) the relationship between a stimulus and the action it guides is arbitrary (conditional motor behavior) or (ii) the targets of gaze, spatial attention, and limb movement differ from each other or from the visuospatial stimuli that guide them. Our thesis stems from two principal sets of findings. The © 1996 NRC Canada

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ablation of the premotor cortical areas does not severely disrupt direct, “standard” reaching movements to a visible target (Moll and Kuypers 1977; Rea et al. 1987). However, neurophysiological studies provide ample evidence of spatial information processing there during standard-mapping tasks. To reconcile these two sets of findings, we hypothesize (i) that the spatial information processing observed during standardmapping tasks is necessary because premotor cortex (PM) must learn the standard mappings to compute nonstandard ones and (ii) that each premotor area plays a role in different varieties of nonstandard sensorimotor mapping. Nomenclature Based on a broad array of anatomical, physiological, and neuropsychological data, prefrontal cortex (PF) can be distinguished from the more caudally situated frontal motor areas (Passingham 1993). Figure 9 shows some of the relevant areas in macaque monkeys. Among the motor areas, a distinction has generally been recognized between primary motor cortex (M1), roughly area 4, and premotor (PM) or nonprimary motor areas, mainly areas 6 and 24. Note that the use of the terms motor cortex or premotor cortex does not imply that either is a single area, any more than the term visual cortex implies that there is but one visual cortical field. Indeed, several schemes for subdividing PM have been proposed, but for present purposes we need consider only the medial premotor areas (including the supplementary motor area (SMA) and the cingulate motor areas (CMA)) and the lateral premotor areas, consisting of the dorsal and ventral premotor areas (PMd and PMv, respectively). Rostral to both PMd and PMv, within parts of areas 45, 8, and 6, two oculomotor areas have been identified. The most ventral one is the well-known frontal eye field (FEF). The area situated rostromedial to PMd has been named the supplementary eye field (SEF).

Nonstandard mapping. I. Nonspatial instructions Neuropsychology Ablation studies have shown that PMd plays an important role in conditional motor behavior, in which actions must be selected on the basis of arbitrary sensory stimuli. These stimuli are arbitrary in that the action they instruct has no relationship to the stimulus other than the associative link forged in the laboratory. They are also, typically, nonspatial, but only in a restricted sense of that term. Of course, the instruction stimulus can and does occur at some place, but that location has no relevance to the action it instructs. Monkeys with premotor cortex lesions show poor performance in learning or relearning conditional motor tasks (Halsband and Passingham 1982, 1985; Passingham 1985a, 1985b, 1986, 1988; Petrides 1987). When the color of a visual cue instructs a monkey to make one of two limb movements (e.g., pull vs. twist a manipulandum), ablation of PMd (Petrides 1987), PMd + PMv (Halsband and Passingham 1982), or PMd + adjacent PF (“prearcuate”) (Petrides 1982) leads to severe deficits in task acquisition and performance. Recently, deficits have been observed in similar tasks during localized inactivation of PMd, but not PMv, with the GABA agonist muscimol (Kurata and Hoffman 1994). When visual stimuli are used, the deficit is specific to

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visuomotor associations (e.g., mauve means move, but indigo instructs inaction) vs. visuovisual ones (e.g., baseballs stimulate grasping a glove, but a piece of paper promotes picking up a pen). In the visuomotor task, the color of an object instructs the monkey, for example, to either pull or twist a handle. In the visuovisual task, the color of an object instead tells the monkey which of two other objects to displace in order to receive a reward. Stated very generally, when a cue’s hue determines which direction to move a lever, monkeys with PMd damage are impaired, but when a similar cue indicates which of two objects to displace to find a reward, monkeys without PMd show normal learning and performance (Halsband and Passingham 1982, 1985; Passingham 1985a; Petrides 1987). These and related findings have led to the suggestion that the specific deficit after PMd lesions lies in the retrieval of movements from memory on the basis of associated cues (Passingham 1989). Intriguingly, there is at least one exception to the rule stated above. If the color of a manipulandum provides the instruction of whether to pull or twist it (Passingham 1985a, 1985b, 1986), monkeys with PMd ablations show virtually no deficits. For simplicity of reference, we will call this the coloredhandle task. Put differently, it appears that if the motor instruction is part of the object to be manipulated, PMd is unnecessary for normal performance, whereas if the instructional cue is spatially dissociated from the object, PMd is crucial. One obvious possible explanation of this dissociation involves spatial attention. Perhaps, after PM lesions, monkeys simply cannot attend to a location other than that of the handle. However, this possibility has been convincingly ruled out by results from the visuovisual conditional tasks, noted above. Monkeys with PMd lesions can attend to an object dissociated in time and space from the action to be taken, at least when that object tells the monkey which object to displace. We suggest a different explanation. Compared with typical conditional motor tasks, the colored-handle task involves a different kind of nonstandard mapping. In the colored handle task, as in most standard mapping tasks, motor instructions arise from the object to be acted upon. In the typical conditional motor tasks, instructions arise from elsewhere. If, as we will argue below, different premotor cortical areas subserve various types of nonstandard sensorimotor mapping, it is possible that a major distinction can be made in terms of whether the information about movement arises from the object of action. We suggest that PMd becomes essential when stimuli other than the object of action instruct a response. Neurophysiology Many studies of PM neurons have used “instructed delay tasks,” in which monkeys are operantly conditioned to make limb movements in response to sensory cues (Godschalk et al. 1981; Rizzolatti et al. 1987, 1990; Riehle and Requin 1989; Riehle 1987; Kurata 1989, 1993; Alexander and Crutcher 1990b; Caminiti et al. 1991; Fu et al. 1993, 1995; Kalaska and Crammond 1992; Kalaska et al. 1992; Crammond and Kalaska 1994; Johnson et al. 1996). A cue, usually visual, is given to the animal to instruct it about the action to perform. Most often, the visual cue is also the target of limb movement. However, nonspatial aspects of the cues, e.g., color, have also been used to instruct actions. After a variable delay period, termed an instructed delay period, a trigger signal evokes the © 1996 NRC Canada

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overt motor response. Under such conditions, PMd neurons, much like neurons throughout the frontal lobe and elsewhere, discharge (i) prior to the occurrence of temporally predictable cues, (ii) in a time-locked, response-like fashion after cue onset, (iii) during the instructed delay period, (iv) prior to movement, and (v) while maintaining steady posture at a target location. These activity patterns have been referred to as precue, signal (or postcue), set (or delay period), movement, and position related, respectively. A given PMd neuron may show any combination of these activity patterns. Most studies of the premotor areas, cited above, have employed direct, visually guided reaching movements as responses. They showed that neurons in all premotor areas, including PMd, have strong modulation during direct, visuospatial movement to visible targets. We will argue that the specific function of the premotor areas involves the computations underlying nonstandard mapping of sensory signals onto learned motor responses. However, this proposition does not imply that the premotor areas are totally uninvolved in standard sensorimotor mapping tasks, only that they are obligatorily engaged in the nonstandard mapping tasks, such as conditional motor learning. Neurons in at least two premotor areas, PMd and SEF, show evolving activity during conditional motor learning, a finding that strongly supports the hypothesis that they play a role in nonstandard sensorimotor mapping (Mitz et al. 1991; Chen and Wise 1995a, 1995b). The experimental approach of Wise and his colleagues has involved examining the activity of neurons as monkeys solve conditional visuomotor “problems” by trial and error. A problem, in this sense, consists of learning the “correct” response to a nonspatial visual instruction stimulus. Conditional skeletomotor learning was studied for PMd, conditional oculomotor learning for SEF. A substantial proportion of adequately tested neurons in PMd and SEF show gradually increasing modulation as monkeys learn new, arbitrary associations. On average, the activity of these cells increases in close correlation with the animal’s learning curve. In most instances, cells showing this learning-correlated increase in activity develop patterns and magnitudes of activity that resemble those observed when highly familiar stimuli instruct the same action. Other task-related neurons, especially in SEF, show their maximal activity during the earliest phases of learning. These cells often decrement gradually in activity until they become inactive, or nearly so, after the monkey has learned an initially novel visuomotor association (Chen and Wise 1995a). These data provide strong support for the hypothesis that PMd and SEF play important roles in the selection of action, whether oculomotor or skeletomotor, on the basis of nonstandard, arbitrary sensorimotor mapping. A related study supports this conclusion for PMd through a different experimental approach (Germain and Lamarre 1993).

Nonstandard mapping. II. Spatial incongruities In a second type of nonstandard mapping, spatial incongruities exist among the locus of spatial attention, visuospatial stimuli, response direction, and gaze angle. A wide variety of such behaviors have been grouped under the heading of stimulus– response incompatibility tasks. Kornblum et al. (1990) have reviewed this vast literature. Indeed, the incongruities need not

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be limited to the spatial domain, and the arbitrary stimulus– response associations described as conditional motor learning might also be viewed as a special form of stimulus–response incompatibility. Psychophysics In normal situations, once an object in the visual field attracts a subject’s attention, a complex chain of sensorimotor transformations may end in a reaching and grasping movement or a saccade to that stimulus. In this standard-mapping situation, attention, gaze, and limb movements are spatially congruent. We conjecture that the advantages of this standard-mapping condition lie in exploitation of its inherent spatial regularities. Responding to stimuli and events by attending, gazing, and acting in spatial concert allows the fastest and most automatic behavior, building on relationships between spatial stimuli and motor commands that can be learned and adjusted continuously with experience (Hein 1974; Held and Bauer 1974). In a typical experiment supporting this view, a subject is instructed to attend to and expect a target in one location, although in a relatively small proportion of trials the target will appear somewhere else. Reaction times increase for both eye and hand movement when the target appears at an unattended location (Posner and Cohen 1980). Incongruity of gaze and action also yields reaction-time increases. For hand movements without vision of the hand or when gaze angle remains fixed, response latencies are 25 ms slower than in standardmapping conditions (van Donkelaar et al. 1994) and appear to be less accurate, as well (Prablanc et al. 1986). Simply requiring subjects to visually fixate leads to hypermetric movements (Bock 1986; Prablanc et al. 1979a, 1979b). In addition, eye movements appear to affect the direction of limb movements to fixed targets (Frens and Erkelens 1991). In the oculomotor domain, Sheliga et al. (1994) have recently reported that spatially directed attention can cause the deviation of oculomotor trajectories toward the side of attention, an effect that is independent of whether the movement is triggered by a visual cue at the attended location or by a nonspatial auditory cue. Single-cell neurophysiology As noted above, most behavioral neurophysiology has focused on standard-mapping conditions. These studies show that motor command and motor preparatory signals abound in the premotor areas, and that the activity of many neurons reflects the direction of intended or ongoing limb movement (Wise 1989). However, a small number of studies have reported results from nonstandard-mapping tasks, particularly those in which a spatial stimulus directs a motor response elsewhere. Many cells in the supplementary motor area (SMA), primary motor cortex, and putamen appear to reflect the location of a target regardless of whether that stimulus instructs limb movements in the same or in the opposite direction (Alexander and Crutcher 1990a; Riehle et al. 1994; Shen and Alexander 1994). One interpretation of this finding is that these cells are involved in coding the target (or goal) rather than limb-movement direction. However, because these experiments did not control for the orientation of spatial attention, the results interpreted as resulting from stimulus or goal location could as readily be interpreted as effects of selective spatial attention. The same problem can be found in studies of PF (Funahashi et al. 1993) © 1996 NRC Canada

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and PMd (Crammond and Kalaska 1994) in conceptually similar tasks. Other reports of cell activity in PMv and PF, interpreted in terms of movements of stimuli, experimenters, and other objects in an animal’s environment (di Pellegrino et al. 1992; Graziano et al. 1994), might also reflect the reorientation of spatial attention. In the sections immediately below, we will briefly sketch some relevant results from experiments with behavioral designs that begin to address some of the interpretational problems noted above. However, all experiments have their interpretational limitations, and the problems noted above should not be construed as censure. The experimental designs from our laboratories, outlined below, have limitations, as well. For example, those experiments entail no effort to dissociate selective spatial attention from spatial memory. For convenience, however, we will assume that, of these two covert processes, spatial attention is the predominant factor. However, distinguishing these two factors represents an important goal for future experiments. Gaze effects Boussaoud (1995) and his colleagues (Boussaoud and Wise 1993a, 1993b; Kermadi and Boussaoud 1995) have employed a conditional motor task in which gaze angle is dissociated from both the instruction for action, which is on a video screen, and the spatial target of action, which is below the screen. The subjects were required to maintain gaze toward a spot on the video screen. The instruction could be presented at the fixation spot, and therefore at the fovea, but was usually elsewhere in retinal coordinates. In addition, the fixation spot could be moved to different screen locations. With the head fixed mechanically and the eyes fixed behaviorally, retinal, cranial, shoulder, and extrinsic coordinate frameworks were linked. If the motor instruction was red, the monkeys were required to contact a target to the left of current posture; if it was green, the opposite movement direction was required. When the instruction disappeared after a delay period of 1–3 s, the monkeys could move from the starting posture to contact one of the two potential limb-movement targets. With this experimental design, gaze, limb movements, and attention were directed to incongruous parts of space. Boussaoud (1995) found that delay-period activity of PMd cells was dramatically affected by gaze angle. In his sample, most PMd neurons with delay-period (set related) activity differed significantly for the two movement directions. Approximately 80% of those PMd neurons were significantly affected by the direction of gaze. This “gaze effect” could be observed for the preferred direction, the nonpreferred direction, or both, and gaze angle usually modulated the activity linearly in both horizontal and vertical dimensions. The direction of gaze could either enhance or detract from the directional preference of the cell, with roughly comparable probability. For example, when gaze was directed to the center of the video display, one PMd cell showed greater delay-period discharge before rightward than before leftward limb movements. However, when gaze was deviated to the left, the directional preference of the cell virtually disappeared. In contrast, when gaze was deviated toward the right, the directional preference for rightwardintended limb movement was dramatically enhanced. These results show that PMd activity is strongly and linearly modulated by gaze during a nonstandard-mapping task, one which


involves spatial incongruity of gaze angle, attention, and skeletomotor response. Attention effects Gaze angle is not the only factor influencing cell activity in PMd. Attentional signals can, as well. Boussaoud and Wise (1993a, 1993b), in an experiment related to the one described above, used one cue to induce two different covert behaviors, depending on when during a trial that cue was presented. As the monkey maintained fixation on a centrally located fixation spot, a sequence of cues was presented on the video screen. Unlike the behavioral design of Boussaoud (1995), mentioned above, in this study the fixation point was at the center of the screen on all trials. After the monkey achieved fixation, a cue, which was either a 2° red or green square, guided an attentional shift. For example, a red square could be presented at a certain coordinate above and to the left of the fixation point. The color of that cue was irrelevant, but its location was important. The monkey had to shift spatial attention to that location because a cue there and only there would instruct the monkey what to do in order to receive a reward. Later in the same trial, another cue would appear at the previously cued location and (usually, but not always) simultaneously somewhere else on the screen. The stimulus at the previously cued location served as a motor instruction. If it was a red square, it instructed the monkey to make a limb movement to touch the leftmost of three touch pads. If it was a green square, the monkey was to move to the right touch pad. In our example, if the cue in the upper left quadrant was a red square, but the cue at another screen location was green, then the rewarded response was a movement to the left limb-movement target. Most cells in PMd (55%) showed greater discharge modulation after motor instructional cues than after the attentional cue, although the stimulus was otherwise identical in all respects. We have previously discussed the significance of this finding (Boussaoud and Wise 1993a, 1993b; Boussaoud et al. 1996) in some detail. However, here we stress the fact that a minority of PMd cells (15%) are preferentially active after attentional cues (Boussaoud and Wise 1993b). These results show that attentional and motor instructional signals coexist in PMd and that attention can affect the sensory signals that guide action. The results obtained by di Pellegrino and Wise (1993), which involved a different mode of undermining the standard mapping condition, can also be interpreted as an interaction between spatial attentional and motor preparatory signals. In that experiment, there was independent control of gaze, spatial attention, and the intended direction of limb movement. This objective was achieved as follows. During each trial, the monkey was required to maintain gaze at a central location while stimuli flashed in peripheral visual space. The first stimulus that appeared on a given trial, termed the prime stimulus, cued the monkey to shift spatial attention to its location. This aspect of the experimental design, alone, created an incongruity of gaze and attention because the monkey had to attend to the cued location but maintain a central gaze angle. Of course, the location of the prime stimulus varied from trial to trial and could be in any of the eight light-emitting diodes, arranged as illustrated in Fig. 1. During a relatively long delay period, several diodes flashed on and off. If they were in a different location than the prime stimulus, they were behaviorally © 1996 NRC Canada

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Fig. 1. Behavioral paradigm from di Pellegrino and Wise (1993). Each part of the figure (1–8) shows a sketch of the circular panel; each small circle represents a light-emitting diode (LED). Closed circles indicate illuminated LEDs, and the square around the central LED represents the central visual fixation window. The eight parts of the figure (1–8) present the stimulus events in the order they occurred. The broken arrow represents the location that the monkey had to remember or attend to during the period between prime-stimulus presentations. The bold arrow shows the direction of forelimb movement in the two conditions. Ref, reference period; Stim, stimulus.

irrelevant. If their location matched that of the prime stimulus for that trial, the monkey was required to initiate a reactiontime hand movement to one of eight targets, each directly beneath one of the diodes (Fig. 1). In one condition, termed the compatible condition, the monkey made movements to the attended location (which was also the site of the prime stimulus); in the other, called the incompatible condition, the monkey made a fixed response that bore no consistent relation to the locus of spatial attention (Fig. 1). Thus, in the compatible condition, spatial attention, limb-movement target, and primestimulus location were congruent, although as noted above, gaze was incongruent with each of these variables. The incompatible condition created further incongruities. In that condition, the target of intended limb movement was always the same, and thus additionally dissociated from both the direction of gaze, the prime stimulus, and attention. Figure 2 exemplifies one key result: delay-period activity was systematically affected by the locus of spatial attention. The neuronal activity illustrated in Fig. 2 was recorded during the performance of the incompatible condition, thus the movement was identical for all trials. However, a clear directional “tuning curve” can be appreciated from the differences in delayperiod activity among the various prime-stimulus locations. di Pellegrino and Wise (1993) termed this difference a position effect, referring to the location of the prime stimulus, but it appears most likely that the locus of spatial attention is the more important factor. This point will be taken up in more detail below. The influence of selective spatial attention was observed in the majority of PMd neurons (61–80%, depending

on the period during a trial), despite the fact that the intended limb movements were identical. Thus, it is clear that a signal reflecting a factor other than limb-movement direction influences the activity of PMd neurons, and it is likely that this factor is, at least in part, attentional in nature. Motor preparatory effects Figure 3 shows another result of creating incongruities in directed spatial attention and limb movement. This PMd cell showed a phasic, postcue discharge that looks very much like a visual response. However, comparison of the cell’s activity after identical stimuli in the compatible versus the incompatible conditions (Fig. 3B vs. 3D, respectively) reveals that this apparent “response” is not sensory at all. The cell’s activity reflects the factor differing in the two conditions, i.e., the instructional significance of the cue. We have argued in detail (di Pellegrino and Wise 1993) that this aspect of the signal reflects the preparation for the specific limb action instructed by the prime stimulus. Population neurophysiology Calculation of the ensemble population averages, termed population vectors, has proven to be a useful measure in comprehending the activity of motor cortical areas (Georgopoulos et al. 1982, 1983; Caminiti et al. 1990a; Lurito et al. 1991; Schwartz 1993, 1994; Ashe et al. 1993). The methods and procedures for calculating the preferred directions (PDs) of motor cortical neurons and the population vector have been described previously by Georgopoulos and his colleagues © 1996 NRC Canada

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Fig. 2. Activity of a dorsal premotor cortex (PMd) neuron (data from di Pellegrino and Wise 1993). The eight raster and reciprocal-interval plots, from activity in the incompatible condition, are arranged in accordance with the prime-stimulus location (see Fig. 1). Each raster line shows the time of action potentials (vertical tick marks) aligned on the presentation of the first prime stimulus (continuous vertical line). After a variable delay, the second prime stimulus onset is marked beneath each raster line (u). This event served as the “go” or trigger signal. In the center, the limb-movement direction is shown by the arrow. Activity scale (in impulses/s) is the same in all displays.

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Fig. 3. Condition effects. PMd neuron showing dramatically greater post-PS1 (and post-PS2) modulation during the compatible compared with the incompatible condition. (A) Raster and histogram display of activity for the preferred direction in the compatible condition. (B) Same as Fig. 3A, with expanded time scale (lower right). (C) Plot of mean (±SD) post-PS1 activity for each of the eight prime-stimulus locations in both conditions. (D) Raster and histogram display of activity following the same stimulus as Fig. 3B, but for the incompatible condition. Activity scale (impulses/s) is the same in all displays. The angle convention differs from that in Fig. 2: 0°, the preferred direction of the cells, is down and to the left, at –135° in the convention of Fig. 2.

(Lurito et al. 1991). In brief, the activity of neurons is studied during different task periods and for several (usually eight) directions of limb movement, and the interpolated or averaged direction for which neuronal modulation is maximal is considered the cell’s PD. Based on the assumption that a cell always contributes to the population output in its preferred direction and that its contribution is proportional to it level of activity for each direction of movement, an average population vector can be computed. Note that the population vector must always be computed with respect to some “canonical” PD. PDs change depending on task period (di Pellegrino and Wise 1993; R. Caminiti and P. Johnson, personal communication) and experimental condition (di Pellegrino and Wise 1993). Accordingly, one must choose some task condition and period for which to “define” the cell’s PD for the purpose of calculating an average population vector. In most studies to date, and here, the canonical PD is that defined during the movement to

peripheral targets from a common position (Lurito et al. 1991; Schwartz 1993, 1994; Ashe et al. 1993). We used a similar method of analysis on the data taken from the experiment, described above (see Fig. 1), in which identical stimuli guided either fixed (incompatible condition) or variably targeted (compatible condition) responses. We calculated a population vector for each of three task periods, shown in Fig. 4: the prime-stimulus period, the end of the instructed delay period, and the movement period. A preferred direction was calculated for each task period by taking a weighted circular mean of activity during that task period, then performing a regression to a cosine function. PDs in the PMd population were distributed quite uniformly. The population vector was then computed as a weighted circular mean of the individual cell’s activity for each prime-stimulus direction, subtracting a period of 500 ms during a reference period immediately before the onset of the first prime stimulus. Thus, © 1996 NRC Canada

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Fig. 4. A series of PMd average (n = 96) population vectors for one prime-stimulus location in the compatible (top) and incompatible (bottom) conditions. In the trials comprising this average, the first (PS1) and second (PS2) prime stimulus are located 180° from the repetitive movement target. The left series of population vectors are aligned on the onset of PS1, the right series on the onset of PS2. The 10-ms bins are smoothed for length and direction with a five-point, centered moving average. Mvt, movement.

the modulation, M, for each neuron (i) in each 10-ms time bin (j) when the prime stimulus was presented at direction k (where k = 0°, 45°, 90°, 135°, 180°, 225°, 270°, or 315° from the central, fixation stimulus) was defined as the average neuronal discharge rate (A) minus reference-period activity (R) (Mijk = Aijk – Rik). Mijk was computed separately for the compatible and incompatible conditions. As noted above, the population vector was based on the canonical PD, that is the PD during the movement period of the compatible condition. Thus, although a given neuron could have different PDs in different task periods and in different conditions, the population averages were calculated with respect to each cell’s PD in the movement period of the compatible condition. Figure 4 shows a series of population vectors, in 10-ms bins, for the case of 180° incongruence between the locus of spatial attention and the intended movement direction. Note that, in the compatible condition, the population vector pointed more or less directly downward, in the direction of the prime stimulus, from shortly after the onset of the prime stimulus (PS1), and it continued to do so throughout the delay period. It then grew in the same general direction before movement, which occurred, on average, 284 ms after PS2 onset. In contrast, in the incompatible condition, the population vector appears deviated counterclockwise from PS1 throughout most of the delay period, but swung much further counterclockwise just before movement, which occurred, on average, 307 ms after PS2 onset.

Each panel in Fig. 5 shows eight population vectors, one for each prime-stimulus location. For example, the population vectors for the example shown in Fig. 4 are labeled 180° in Fig. 5. In the compatible condition (top row), the population vectors point reasonably directly at the corresponding primestimulus location. In the incompatible condition (bottom row), the direction of 7 of the 8 population vectors appears to be deviated from the direction of the prime stimulus and toward the location of the repetitive target of limb movement (0°). The magnitude (length) of the population vector is also greater in the compatible than in the incompatible condition, which reflects the difference in modulation relative to reference-period discharge that was previously reported for PMd neurons (di Pellegrino and Wise 1993). Figure 6 shows that the amount of vector deviation from the intended movement direction (“Target”) varies in a precisely linear manner with the angular difference between the locus of spatial attention (at the PS location) and the target of intended limb movement. The population vector always seems to deviate about 30% of the angular distance from the locus of spatial attention to the intended limb-movement target, and does so with remarkable precision (r2 > 0.99). As shown in Fig. 4, although the amplitude of the population vector decreases as the phasic, postcue discharge dissipates, it maintains a fairly constant angle during the delay period. However, after the trigger stimulus, the population vector quickly deviates toward the limb-movement target, © 1996 NRC Canada

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“arriving” there in advance of the earliest EMG activity associated with the limb movement (Fig. 7). The amplitude of the population vector seems to decrease for a time after the trigger signal and then increase dramatically in the reaction-time period. The interval from the trigger stimulus until the population vector first points directly toward the limb-movement target varies systematically as a function of attention-movement incongruence, as does reaction time (Fig. 7). The interval between the end of population vector deviation and the earliest prime-mover EMG becomes progressively shorter as the degree of spatial incongruence increases. The correlation between reaction time and the time of population-vector stabilization was significant (r2 = 0.69, p = 0.011), but for each 100 ms that it took for the population vector to stabilize in the direction of movement, reaction time increased by only 13 ms. These findings suggest that a time-consuming process must occur when action is guided by nonstandard mapping, as reflected by increased reaction time and the behavior of the population vector (Lurito et al. 1991), but that this is only one factor slowing response time in nonstandard mapping conditions. Putting these data from PMd together with those from primary motor cortex (Lurito et al. 1991), and neglecting for the sake of discussion the differences in tasks and areas, there is a suggestion that the attentional requirements of our task constitute the most significant factor in maintaining the population vector’s direction toward the prime-stimulus location. The task of Lurito et al. required the monkey to move toward a target that was deviated 90° counterclockwise from the stimulus. The population vector initially deviated about 30% of the angular distance between the stimulus and response. Indeed, the average of all eight of the cue locations used in their experiment leads to a composite population vector indicated by the Lurito et al. data point on Fig. 6. This point falls almost exactly on the line defined by the eight data points in the experiment of di Pellegrino and Wise (1993). However, Lurito et al. observed the population vector to begin rotation (or pseudorotation) toward the limb-movement target immediately after stimulus presentation. Thus, we speculate that if an attentional requirement is persistent, the deviation of the PMd neuronal population vector away from the direction of intended limb movement will be persistent as well, and that if there is no persistent and incongruent attentional requirement, then the effect of attention on the population vector will quickly dissipate (Lurito et al. 1991). Clearly, this suggestion needs to be subjected to rigorous testing in future investigations, involving data from a single set of tasks and the same cortical area. Graded signal combinations in PMd It seems most parsimonious to explain the linear relationship shown in Fig. 6 as a graded combination of two signals. We can rule out the possibility that our apparently mixed-signal population vector simply reflects the average of two, pure populations. If that were the case, one would expect that the single-neuron data would reveal at least some cells with the pattern of activity shown in Fig. 8, which is what would be expected of cells reflecting exclusively “intentional” or motor factors. For all practical purposes, di Pellegrino and Wise observed no individual cells with that pattern. More than 20% of the PMd cells were unaffected by prime-stimulus location in

477 Fig. 5. Six sets of eight PMd population vectors, three from the compatible condition (top panel), three from the incompatible condition (bottom panel). In each circle, there is one population vector for each of the eight prime-stimulus (PS) locations. They correspond to the PS location closest to the vector, as illustrated. The left figures show the eight population vectors, for each condition, averaged over the 500 ms that the PS1 was presented. The middle figures show these averages during the final 300 ms before the onset of the PS2 stimulus. The right figures show the 300-ms movement period, which included the reaction-time period, as well. The scale is the same in all plots.

the incompatible condition, but they were also “untuned” in the compatible condition. We suggest that one of two signals that combine in PMd during the instructed delay period reflects intended limbmovement direction and the preparation for that specific movement (Weinrich and Wise 1982; Wise 1985, 1989; Wise and Mauritz 1985; di Pellegrino and Wise 1993). The other appears to depend, as argued above, on the persistence of selective spatial attention. Thus, the most straightforward interpretation of our results is that PMd reflects mixed motor set – spatial attentional signals during the delay period. Alternatively, the two signals might be either both attentional or both motor. The former notion suggests that the intermediate angle of the population vector reflects divided attention. However, we and others have previously shown that, when spatial attention is controlled, a signal reflecting the preparation for movement can clearly be detected (Weinrich and Wise 1982; Wise 1985, 1989; Wise and Mauritz 1985; di Pellegrino and Wise 1993). Accordingly, the divided attention hypothesis can be rejected. The divided motor set hypothesis remains plausible, however. According to this view, during the delay period PMd reflects competing sets: movement to the prime-stimulus location and movement to the fixed target, with removal of the plan inappropriate set just before movement. Some possible sources of these signals can be contemplated. Figure 9 shows a sketch of the neural pathways to PMd, based on the anatomical analysis presented in Boussaoud et al. (1996). We emphasize that, although the arrows point toward PMd, most of these connections are reciprocal. One source of an attention signal to PMd may be cells in parietal area 7a, © 1996 NRC Canada

478 Fig. 6. Plot showing the angular deviation of the PMd population vector from the repetitive target for the eight prime-stimulus (PS) locations in the incompatible condition (h, PS period; d, end of the delay period). In the compatible condition, vector directions for both the PS period and the end of the delay period are shown as open circles (s). Thus there are two open circles for each PS location. Positive differences indicate counterclockwise incongruencies between PS location and movement target, in contrast with the usual convention. The open cross to which the arrow points shows the mean angle of the population vector, relative to the movement target, for the eight cases of 90° stimulus–movement incongruencies in Lurito et al. (1991). PopVec, population vector.

which show properties like those of PMd in a task formally identical with the incompatible condition described above (Steinmetz et al. 1994). The basal ganglia, which has many neurons active during instructed delay periods (Alexander 1987; Jaeger et al. 1993) and projects via thalamic relays to PMd (Kurata 1994; Inase and Tanji 1994), may be a source of a motor preparatory signal, especially when the selection of action is based on external context (Houk and Wise 1995). This could be the case for nonstandard mapping based on spatial incongruity, as well as for other nonstandard mappings, such as those typified by conditional motor learning (Passingham 1993). Other possibilities for the motor preparatory signal include the primary motor, parietal, and prefrontal cortex. The basal ganglia could also be the source of attentional signals (Kermadi and Boussaoud 1995). After the delay period, there is an indication of a third signal, one reflecting the motor command. It appears from examination of the population vector that a motor command signal becomes dominant during the period immediately prior to the initiation of action. It is interesting to note that the delay-period signals do not merely blend in with an incrementing motor signal during the reaction-time period. Instead, in the incompatible condition (Fig. 4), the population vector decreases in amplitude shortly after the trigger signal, then increases dramatically several tens of milliseconds, at least, before the earliest movement-related EMG activity. The overall impression is that one set of signals is being replaced by another. As noted in Fig. 9, we speculate that this motor com-

Can. J. Physiol. Pharmacol. Vol. 74, 1996 Fig. 7. Reaction times (s), estimated EMG onset times (Œ), and the time that the population vector stabilized in the direction of movement (d), from the incompatible condition. Note the systematic increase in reaction time with greater degrees of incongruity between the locus of spatial attention and the direction of limb action. Data from di Pellegrino and Wise 1993.

Fig. 8. Fictitious plot of a pure “motor” signal. In the incompatible condition, such a cell would have whatever activity was observed for the repetitive movement target (0°) in the compatible condition. Such a pattern was not observed in PMd. The ordinate is in arbitrary units of discharge rate.

mand signal influences PMd through reciprocal, recurrent pathways involving primary motor cortex and the cerebellum (Houk and Wise 1995). There is evidence that these motor and attentional signals are not the only ones converging on the PMd population. Just as various anatomical inputs converge to PM cortex (Fig. 9), other signals have also been reported to be represented in this area. The linear gaze fields of Boussaoud (1995), described © 1996 NRC Canada

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Wise et al. Fig. 9. Summary of some possible sources of signals to PMd. A, amygdala; GP, globus pallidus; Θ, dorsal thalamus; Cb, deep cerebellar nuclei; CM, cingulate motor areas; SM, supplementary motor area; SEF, supplementary eye field; PFv, ventral prefrontal cortex; PMd, dorsal premotor cortex; M1, primary motor cortex; 5, Brodmann’s area 5; VIP, ventral intraparietal area; LIP, lateral intraparietal areas; MIP, medial intraparietal area; PO, parietal–occipital area; MDP, mediodorsal parietal area; Caud, caudate nucleus; Put, putamen; IT, inferior temporal cortex. The broken arrow reflects a relatively indirect projection.

above in the section on single-cell neurophysiology, identify another signal coming to the PMd population. Gaze signals may reach PMd directly from the rostrally adjacent SEF or caudally from parietal visual areas such as area LIP of the parietal visual cortex. Proprioceptive inputs appear to reach PMd, as well. This signal is reflected in the effects on PMd activity caused by variations in the initial position of the limb (Caminiti et al. 1990a, 1990b; Bauswein and Fromm 1992). This signal may arise from parietal area 5. In addition to a motor instructional, attentional, gaze, and limb position signals, the expectation of reinforcement also affects PMd activity (Watanabe 1992). It is interesting to note, in that context, that the amygdala projects to premotor cortex (Avendaño et al. 1983). The advantage of combining signals can only be the subject of speculation at present. It is possible that by combining different sets of signals in different cortical areas, the independent signals could be extracted by simple comparators. For example, if prefrontal cortex carries a sensory–attentional signal and PMd has both sensory–attentional and motor preparatory signals, the pure motor preparatory signal can be obtained by subtraction of the two. Alternatively, one could say that

once the cortex “knows” the location of a stimulus independent of its instructional significance, the relevant neural network can calculate the direction of intended action by “knowing” the angle of the PMd population vector and the highly linear relationship shown in Fig. 6. In at least one sample of prefrontal cortex neurons, its population vector has exactly the property necessary for such a reference signal (G. di Pellegrino and S.P. Wise, unpublished observations).

Role of nonprimary motor areas in nonstandard mapping Much of the literature of the premotor cortex is devoted to understanding information processing in standard-mapping conditions. But PMd, PMv, and SMA are, together, unnecessary for standard mapping behavior (Rea et al. 1987). Lesions of primary motor cortex, in contrast, severely disrupt direct movements to a visible target (Hoffman and Strick 1995). Thus, we suggest that the spatial information processing seen in PMd during standard-mapping conditions serves as a basis for nonstandard computations. This counterintuitive proposal suggests a general role for the nonprimary motor areas in © 1996 NRC Canada

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nonstandard mapping, in contrast with a role for primary motor cortex in certain aspects of standard mapping. PMd seems to be well suited for supporting arbitrary linkages between the nonspatial aspects of sensory cues and motor responses. These conditional motor behaviors comprise one important, and perhaps the most general and flexible, type of nonstandard sensorimotor mapping. In the present context, these conditional motor behaviors might be construed as involving the “nonspatial” guidance of action. As noted above in the discussion of Passingham’s colored-handle task, PMd appears to be most important when motor instructions arise from a source other than the object to be manipulated. Other areas, such as PMv, appear to be more important for objectoriented action (Rizzolatti et al. 1988), perhaps most importantly in prehension movements guided by parts of an object rather than (as in standard mapping) an object as a whole. SMA may contribute to a different type of nonstandard mapping. SMA has long been thought to be involved in internally, as opposed to externally, guided behavior (Passingham 1993). Previous reports contrast neuronal activity in SMA with that in PM during movements involving internally guided versus visually instructed sequences (Mushiake et al. 1991) and show that SMA neurons reflect a planned and remembered motor sequence (Tanji and Shima 1994). Further, lesions of the SMA lead to poor reaching-in-the-dark behavior (Passingham 1993). In contrast to PMd’s “nonspatial” guidance of behavior, SMA might be viewed are subserving “nonsensory” guidance of action, perhaps involving arbitrary temporal patterning or sequences of action (Halsband et al. 1993). This, then, would be SMAs contribution to nonstandard mapping. Finally, with their long-standing link to the limbic system, the multiple CMAs might mediate yet more enigmatic kinds of nonstandard mapping. Our suggestion invokes a role in “affective” guidance of action. Consider the whimsical notion of behavioral guidance by lust. The “standard” lust-action mapping would call, at least in individuals with the most common genetic makeup, for actions that serve to propagate one’s genome. However, the standard mapping could be problematic in most commonplace sociopolitical contexts. Accordingly, one might view nonstandard sensorimotor mapping, in lust and in many other instances, as a matter of survival.

Acknowledgments The authors gratefully acknowledge the contributions of Stephen G. Massaquoi, A. David Redish, and Sohie J. Lee in their discussion and analysis of issues pertinent to this review.

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