Cortical control of reaching movements

Current Opinion in Neurobiology

Volumn 7, Issue 6, 1997, Pages 849-859

  Kalaska, John F ^a   Scott, Stephen H ^a   Cisek, Paul ^a   Sergio, Lauren E ^a  

^a UNIVERSITÉ DE MONTRÉAL   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN CORTEX; HUMAN; HYPOTHESIS; LIMB MOVEMENT; MOTOR ACTIVITY; PRIORITY JOURNAL; REVIEW; SENSORIMOTOR CORTEX;

EID: 0031463488     PISSN: 09594388     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0959-4388(97)80146-8     Document Type: Article

References (86)

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6. Goodale MA: Visuomotor modules in the vertebrate brain. Can J Physiol Pharmacol 1996, 74:390-400. In this follow-up to his influential review published four years earlier [85], Goodale further elaborates the hypothesis that the visual system is modular, with a fundamental division between systems dedicated to perception and to more cognitive functions and those concerned with visuomotor behaviour. In this scheme, key functions of the parietal cortex are to extract information about the structure of the external world, such as the spatial location, distance, physical dimensions, and spatial orientation of objects, and to perform some of the associated visuomotor transformations that are required to organise successful visually guided movements.
7. Jeannerod M, Arbib MA, Rizzolatti G, Sakata H: Grasping objects: the cortical mechanisms of visuomotor transformation. Trends Neurosci 1995, 18:314-320.
8. Kalaska JF: Parietal cortex area 5 and visuomotor behavior. Can J Physiol Pharmacol 1996, 74:483-498. A comprehensive review of neurophysiological studies of superior parietal cortex area 5, and a critical evaluation of several hypotheses about its function.
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11. Bullock D, Cisek P, Grossberg S: Cortical networks for control of voluntary arm movements under variable force conditions. Cereb Cortex 1998, in press. These authors present a computational model of voluntary movement, postural control, and kinaesthesia derived from the results of various psychophysical studies and from neurophysiological data on neuronal activity in pre-central and parietal cortical areas. The model proposes functional interpretations for diverse cell types in these areas, and makes predictions about their activities during novel experimental paradigms.
12. Kertzman C, Schwarz U, Zeffiro TA, Hallett M: The role of posterior parietal cortex in visually guided reaching movements in humans. Exp Brain Res 1997, 114:170-183. A PET study of the distribution of activity during visually guided reaching movements in humans, with special attention as to whether the parietal cortex represents reaching movements according to the visuospatial location of the target or in limb motor co-ordinates. Whereas MI represented the behaviour exclusively in limb-centred co-ordinates, most other task-related cortical areas, including the parietal cortex, processed both visuospatial and limb motor information.
13. Savaki HE, Raos VC, Dalezios Y: Spatial cortical patterns of metabolic activity in monkeys performing a visually guided reaching task with one forelimb. Neuroscience 1997, 76:1007-1034. A rigorous quantitative study of the distribution of metabolic activity across the cerebral cortex of monkeys performing a visually guided reaching task with one arm. Of particular note, the arm regions of the primary motor and somatosensory cortex and parts of area 5 are contralaterally activated, suggesting a direct role in controlling the reaching limb. In contrast, parts of the premotor cortex, area 5, and area 7 are bilaterally activated, implicating a role in higher-order integration of visuomotor information during visually guided reaching behaviour.
14. Clower DM, Hoffman JM, Votaw JR, Faber TL, Woods RP, Alexander GE: Role of the posterior parietal cortex in the recalibration of visually guided reaching. Nature 1996, 383:618-621. The authors used PET techniques to localise the cortical regions implicated in adaptation to laterally displacing prisms during visually guided reaching. After subtracting the activity patterns presumed to reflect sensory, motor, and error-correction aspects of the task, the only remaining differential activation was in a small part of the parietal cortex contralateral to the arm used to reach. This region may correspond to the cortex near the fundus of the intraparietal sulcus in macaque monkeys, but interspecies homologies are often problematic. The authors did not find a differential activation of the cerebellum, even though the latter has also been implicated in prism adaptation. They propose that the cerebellum is implicated in other aspects of the adaptation process, but not to the action-specific realignment of limb and visual reference frames.
15. Martin TA, Keating JG, Goodkin HP, Bastian AJ, Thach WT: Throwing while looking through prisms. II. Specificity and storage of multiple gaze-throw calibrations. Brain 1996, 119:1199-1211. It is well documented that the adaptation of reaching movements to displacing prisms does not transfer well from the practised arm to the unpractised arm. This study demonstrated that the adaptation acquired during overhand throwing of balls at a target also does not transfer well to underhand throws to the same targets using the same arm, indicating that the adaptation process may be specific to the biomechanics of the limb motions.
16. Kitazawa S, Kimura T, Uka T: Prism adaptation of reaching movements: specificity for the velocity of reaching. J Neurosci 1997, 17:1481-1492. Human subjects reached from a fixed starting position to different target locations while wearing displacing prisms. When adaptation was completed with one movement velocity, transfer was progressively poorer for test movements at increasingly different velocities. This indicated that adaptation is not just specific to the form of the limb motions, but also to its time-dependent parameters. The authors concluded that the adaptation did not involve a static shift in either the visual or proprioceptive inputs responsible for a body-centred representation of the spatial location of the hand and target. Instead, the change occurs in a subsequent stage that translates the spatial information into time-dependent parameters describing the kinematics and kinetics of the motor command.
17. ••] illustrates the difficulties confronted by researchers attempting to understand the neuronal mechanisms and functions of nonprimary cortical areas.
18. Ferraina S, Johnson PB, Garasto MR, Battaglia-Mayer A, Ercolani L, Bianchi L, Lacquaniti F, Caminiti R: Combination of hand and gaze signals during reaching: activity in parietal area 7m of the monkey. J Neurophysiol 1997, 77:1034-1038. Cells in parietal cortex area 7m were studied in a combination of tasks meant to dissociate activity related to eye and arm movements and stable positions. Cells showed a wide range of combinations of properties, but the majority of cells showed complex interactions between oculomotor and limb motor behaviour. This study extends the distribution of arm- and eye-movement related activity in the parietal cortex onto the medial surface of the hemisphere.
19. Ferraina S, Garasto MR, Battaglia-Mayer A, Ferraresi P, Johnson PB, Lacquaniti F, Caminiti R: Visual control of hand-reaching movement: activity in parietal area 7m. Eur J Neurosci 1997, 9:1090-1095. Cells in parietal area 7m were tested in an instructed delay task requiring reaching movements of the arm to visual targets in normal ambient light conditions and in the dark. Many cells showed significant differences in activity between light and dark conditions, and showed complex interactions between eye and arm movements at all times during the task, including the delay period. The authors concluded that the directionally tuned activity prior to and during reaching movements in the dark confirm that these cells contribute to the preparation of motor responses.
20. Salinas E, Abbott LF: A model of multiplicative neural responses in parietal cortex. Proc Natl Acad Sci USA 1996, 93:11956-11961. Gain fields imply a multiplicative interaction between inputs in different co-ordinate systems, but single cells are generally assumed to perform only simple additive operations on their synaptic inputs. This study shows that a multiplicative interaction between inputs will arise within a recurrently connected population of simple neurons with excitatory connections between similarly tuned cells and inhibitory connections between differently tuned cells, even though each single cell sums its synaptic inputs linearly. The multiplicative gain field is expressed at the single-cell level, but the cells do not perform a multiplication - it is an emergent property of the dynamical interactions within the network. Multiplicative interactions could also perform co-ordinate transformations in the limb motor system [21], because the network in the motor cortex may have the same recurrent internal organisation [86].
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22. Bracewell RM, Mazzoni P, Barash S, Andersen RA: Motor intention activity in the macaque's lateral intraparietal area. II. Changes of motor plan. J Neurophysiol 1996, 76:1457-1465. If activity during a delay period is related to intentions to make a saccade, that activity should change as new sensory information requires an update in the motor plan. Monkeys were trained to saccade to the last of a variable-length sequence of potential targets presented during an instructed delay period. Because the monkey could not predict which would be the last target, it had to plan a new saccade as each stimulus appeared. Many LIP cells changed their activity after the appearance of each visual target, as expected as the monkey altered his intended motor response.
23. Mazzoni P, Bracewell RM, Barash S, Andersen RA: Motor intention activity in the macaque's lateral intraparietal area. I. Dissociation of motor plan from sensory memory. J Neurophysiol 1996, 76:1439-1457. Using a double-saccade task with an instructed delay period, the authors dissociated the retinal locations of visual stimuli from the metrics of the instructed saccades. They found that whereas some cells signalled the location of visual cues, the majority were related predominantly to the direction of the next saccade, whether or not the visual stimuli fell in their retinal receptive fields. They concluded that much of the LIP activity is related to the planning of overt eye movements, and less to sensory or cognitive processes.
24. Snyder LH, Batista AP, Andersen RA: Coding of intention in the posterior parietal cortex. Nature 1997, 386:167-170. Monkeys were instructed by visual cues to make only eye or arm movements to particular target locations. Many cells were selectively active prior to only eye or only arm movements in specific directions. However, a sizeable minority seemed to be nonspecifically active prior to movements of either the arm or eyes in a particular direction. When tested in a modified task in which the monkeys made simultaneous eye and arm movements in opposite directions, the discharge of most of the 'nonspecific' cells was shown to be correlated to only the eye or arm movements. Without this extra control, those cells might have been interpreted as related to other cognitive operations, such as directed attention.
25. Lacquaniti F, Guigon E, Bianchi L, Ferraina S, Caminiti R: Representing spatial information for limb movement: role of area 5 in the monkey. Cereb Cortex 1995, 5:391-409.
26. Caminiti R, Ferraina S, Johnson PB: The sources of visual information to the primate frontal lobe: a novel role for the superior parietal lobule. Cereb Cortex 1996, 6:319-328. This review article proposes a solution to a long-standing conundrum regarding the fact that although PMd is attributed a role in visuomotor planning, there was no obvious source of visual input. The authors propose that the recently identified visuospatial and visuomotor activity in medial parts of the superior parietal cortex (areas MIP, 7m, MDP and PO) is relayed to PMd via corticocortical projections. The resulting distributed network of parietal and precentral populations is a presumed substrate for the transformation of visual target signals into limb-centred motor commands.
27. Crammond DJ, Kalaska JF: Neuronal activity in primate parietal cortex area 5 varies with intended movement direction during an instructed-delay period. Exp Brain Res 1989, 76:458-462.
28. Ferraina S, Bianchi L: Posterior parietal cortex: functional properties of neurons in area 5 during an instructed-delay reaching task within different parts of space. Exp Brain Res 1994, 99:175-178.
29. Kalaska JF, Crammond DJ: Deciding not to go: neuronal correlates of response selection in a go/nogo task in primate premotor and parietal cortex. Cereb Cortex 1995, 5:410-428.
30. Johnson PB, Ferraina S, Bianchi L, Caminiti R: Cortical networks for visual reaching: physiological and anatomical organization of frontal and parietal lobe arm regions. Cereb Cortex 1996, 6:102-119. A combined neurophysiological-neuroanatomical study of the distribution of response properties of cells in the precentral gyrus and the superior parietal lobule in instructed-delay tasks, and of the corticocortical interconnections between these two regions. The authors found a gradual rostrocaudal change in the relative frequency of so-called 'signal' and 'set' versus 'movement' and 'position' activity across the proximal-arm representation in PMd-MI, with the former more prominent in PMd and the latter stronger in MI. They also found corresponding response patterns and gradients in the medial bank of the intraparietal sulcus, but the orientation of the gradient was opposite, with the 'signal' and 'set' activity more prominent ventrally (caudally) in the sulcus (i.e. MIP). Parts of PMd-MI and the superior parietal lobule displaying similar functional properties tended to be interconnected via corticocortical projections. A superb study.
31. Jackson SR, Husain M: Visuomotor functions of the lateral premotor cortex. Curr Opin Neurobiol 1996, 6:788-795. A concise review of evidence supporting the hypothesis that PMd and PMv fulfil different roles in the planning of visually guided movements, and for the existence of homologues of these areas in the human.
32. Wise SP, Di Pellegrino G, Boussaoud D: The premotor cortex and nonstandard sensorimotor mapping. Can J Physiol Pharmacol 1996, 74:469-482. The authors review many lines of evidence that PMd is critically important when motor behaviour requires nonstandard sensorimotor transformations. Nonstandard mappings involve situations in which the relationship between a stimulus and the response it instructs is arbitrary, or in which the visual stimulus guiding an action does not also serve as the target of the signalled response, or in which gaze, attention, and action are not all directed towards the same spatial location. The ability to form nonstandard mappings endows the organism with rich behavioural flexibility. Of particular note is an elegant 'population-vector' analysis of the effect of dissociating the spatial locus of attention from that of the intended movement target on the directional signal generated by a population of PMd cells in an instructed-delay task with nonstandard mapping.
33. Wise SP, Boussaoud D, Johnson PB, Caminiti R: Premotor and parietal cortex: corticocortical connectivity and combinatorial computations. Annu Rev Neurosci 1997, 20:25-42. A review of the pathways of visual input into PMd, and of the response properties of PMd cells. The authors also consider the role of PMd within the context of several different computational models that perform visuomotor transformations from the spatial co-ordinates of target location to the motor co-ordinates of arm movement.
34. Tanné J, Boussaoud D, Boyer-Zeller N, Rouiller EM: Direct visual pathways for reaching movements in the macaque monkey. Neuroreport 1995, 7:267-272.
35. Fogassi L, Gallese V, Fadiga L, Luppino G, Matelli M, Rizzolatti G: Coding of peripersonal space in inferior premotor cortex (area F4). J Neurophysiol 1996, 76:141-157. This study reported that many PMv cells possess both a somatic receptive field (RF) and a visual RF that is usually located in the peripersonal space immediately adjacent to the somatic RF. The visual RF shifts its spatial location with the somatic RF during body movements, and is independent of the retinal location of visual stimuli. Most cell responses were independent of eye position. The authors concluded that this body-centred hybrid somatic/visual co-ordinate system is useful for organising visually guided arm and head movements. In an interesting discussion, the authors contrasted these properties with the co-ordinate systems for spatial localization in oculomotor areas and concluded that the differences reflect the differing sensorimotor co-ordinate transformations required in the two motor systems.
36. •], they concluded that the visual RFs are body-centred and nonretinotopic. However, they emphasised that the activity level of the majority of cells is modulated by eye, head, or arm position. They proposed that this modulation may reflect a polymodal interaction, similar to that reported for oculomotor cells in parietal cortex, by which a sensory co-ordinate transformation is realised to produce body-fixed visual RFs.
37. Boussaoud D: Primate premotor cortex: modulation of preparatory neuronal activity by gaze angle. J Neurophysiol 1995, 73:886-890.
38. • counterclockwise from limb movement. Using ANOVA analysis, the authors reported evidence in MI of neuronal representations of target location, of limb movement output, and of cell activity reflecting the complex interactions between the two levels of representation. Although there was extensive temporal overlap, there was also a clear serial order in the expression of these different aspects of the task, with a strong trend for early target-related activity, gradually replaced by more limb-centred activity. The complete dissociation between the motion of the cursor and of the limb in the rotated condition provides some of the strongest evidence to date of the existence in MI of higher-order representations of task objectives and constraints independent of peripheral motor output.
39. ••]. They found considerable overlap in the response properties of PMd and MI cells. However, target-centred representations of the task predominated in PMd, unlike in MI, up until the time that movement began. Overall, PMd activity appeared to represent mainly the global extrinsic demands of the task (trajectory of the cursor, not of the limb) and of the behavioural context (rotation condition) in which motions were performed, with a more modest context-independent representation of limb motor output than in MI. This article and its companion both present a clear and focused discussion of the issue of sensorimotor transformations, and are a case study of solid task design and data analysis that should be obligatory reading for all graduate students.
40. Crammond DJ, Kalaska JF: Differential relation of discharge in primary motor cortex and premotor cortex to movements versus actively maintained postures during a reaching task. Exp Brain Res 1996, 108:45-61. A comparison of the cell activity in PMd and MI during a reaction-time task. Of particular note, the authors compared the strength and directionality of activity prior to and during movement to visual targets, with the activity associated with actively maintained postures over the targets after the movements. Many cells in MI were strongly related to both movement and posture, and the directionality of activity during the two phases of the task was generally similar, as was also observed for most muscle activity. In contrast, PMd cells were generally most active before and during movement and less active than MI cells during stable postures, with greater variation in directionality of activity in the two phases of the task. This evidence is consistent with the hypothesis that MI was more strongly implicated in the moment-to-moment control of motor output during both dynamic and static phases of the task, whereas PMd was more conditionally related to movement planning.
41. Zhang J, Riehle A, Requin J, Kornblum S: Dynamics of single neuron activity in monkey primary motor cortex related to sensorimotor transformation. J Neurosci 1997, 17:2227-2246. Monkeys made wrist movements in two opposite directions by moving either towards or away from visual stimuli (as indicated by the colour of the cue), in a reaction-time task without delay period. Using a novel analytic method, LOCUS analysis, the authors attempted to identify the nature of the information being processed in the time-varying discharge of MI cells at different times during the behavioural reaction time. They reported neuronal correlates in MI of three putative processing stages required to perform the task (stimulus encoding, response selection according to current stimulus-response association rule and response encoding independent of association rule). Single cells could show correlates of more than one stage at different times. Although there was overlap, there was also a clear serial order across the population of cells, with activity predominantly related to stimulus location first, followed by activity representing the general mapping rule (e.g. move towards or away from the stimulus) and specific stimulus-response pairings, and, finally, the appropriate direction of response. They also observed that cells in the same vertical penetration (i.e. possibly the same cortical column) tended to show the same task relationship. The implication is that the entire stimulus-response transformation is not expressed within a column, but across ensembles of columns.
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49. Sanger TD: Probability density estimation for the interpretation of neural population codes. J Neurophysiol 1996, 76:2790-2793. Using probability theory, the author outlines an interesting alternative to the population vector method for estimating population signals. Cell activity is expressed as a probability density function that is proportional to the cell's tuning curve for movements in different spatial directions. The population signal is then defined as the product of the tuning curves for all cells active for a given movement.
50. Kettner RE, Marcario JK, Clark-Phelps MC: Control of remembered reaching sequences in monkey. I. Activity during movement in motor and premotor cortex. Exp Brain Res 1996, 112:335-346. Monkeys performed 12 different sequences of three movements in different directions. The three target locations for each sequence were presented during an initial instruction period, followed by a delay before the monkeys made the movements. Cells in MI and PMd were directionally tuned and tended to retain the same tuning throughout the sequence. Using a single set of tuning parameters for each cell derived from its activity across all sequences, the authors generated population vectors that pointed close to the direction of movement for each movement in each sequence. This implicated MI and PMd in the moment-to-moment control of the directionality of movement as the sequences unfolded.
51. Kettner RE, Marcario JK, Port NL: Control of remembered reaching sequences in monkey. II. Storage and preparation before movement in motor and premotor cortex. Exp Brain Res 1996, 112:347-358. The task in this study required memorisation of a sequence of three movements, followed by the recall of each movement in the appropriate order. Whereas many MI and PMd cells were related to the performance of each movement in the sequence, subsets of cells appeared to be more specifically related to the storage and/or recall of particular movements at specific locations in the sequence. This implicates PMd and MI in higher-order cognitive aspects of the motor sequence task, as well as in the execution of each movement in turn.
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54. Georgopoulos AP: On the translation of directional motor cortical commands to activation of muscles via spinal interneuronal systems. Cogn Brain Res 1996, 3:151-155. Based on studies on the motor cortex of monkeys and the spinal cord of frogs, this report describes how directional motor commands could be translated into the co-ordinated patterns of muscle activity required to produce appropriately directed motor output by the limb. This theory suggests that motor cortex regards the limb as a functional whole and that co-ordinated motor patterns are generated only at the spinal level.
55. Lukashin AV, Amirikian BG, Georgopoulos AP: A simulated actuator driven by motor cortical signals. Neuroreport 1996, 7:2597-2601. A neural network is used to control isometric end-point output forces of a two-segment planar model of the human arm. Motor cortical cell activity patterns recorded during an isometric multi-joint task in monkeys are used as input signals for the network, which converts them into a set of muscle 'rest lengths' that generate the desired output force. Only a few cells are necessary to reliably control the limb output forces.
56. Buneo CA, Soechting JF, Flanders M: Postural dependence of muscle actions: implications for neural control. J Neurosci 1997, 17:2128-2142. The effect of arm posture on the mechanical actions of muscles was studied by measuring the changes in direction and magnitude of forces and torques generated by electrical stimulation of muscle bellies while the arm was in a wide range of different postures. With the analytic thoroughness and sophistication characteristic of this team, they showed that force and torque output varied in a systematic and relatively simple manner with arm posture, and also that both arm- and body-fixed reference frames captured this dependence equally well. This study makes readily testable predictions about the response properties of MI cells.
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59. Scott SH, Kalaska JF: Reaching movements with similar hand paths but different arm orientations: I. Activity of individual cells in motor cortex. J Neurophysiol 1997, 77:826-852. Monkeys were trained to make reaching movements using similar hand trajectories but with two different arm orientations, in the natural parasagittal plane and abducted in the horizontal plane. This paradigm dissociated extrinsic variables related to the goal of the task such as target location and hand trajectory, which remained relatively constant, from intrinsic variables related to arm geometry and limb dynamics, which varied across the two conditions. The level of discharge prior to, during and/or after movement changed in a majority of MI cells. Many cells showed a significant change in their relationship to movement direction, reflecting a change in the sharpness of their tuning and/or a change in their directional preference. Mathematical models illustrated that cells encoding intrinsic variables of the task would undergo similar changes when reaching movements were performed in the different arm orientations.
60. •] to two other cortical regions that are implicated in the planning and control of limb movements. Many cells in PMd and area 5 showed a significant change in their relationship to movement direction and/or a change in the level of activity prior to, during and/or after movement when reaching using the different arm orientations. In general, the effect of arm orientation on cell activity was greater in MI than in PMd.
61. Sergio LE, Kalaska JF: Systematic changes in directional tuning of motor cortex cell activity with hand location while generating static isometric forces in constant spatial directions. J Neurophysiol 1997, 78:1170-1174. Monkeys generated static isometric forces at the hand in constant spatial directions, while holding the hand at nine different locations in a horizontal planar workspace. Many MI cells generated tonic activity that varied as a function of the direction of static output forces at a given hand location. The level of activity and its directional tuning also varied with hand location, often showing an arc-like change in directionality across the workspace, even though the spatial direction of output forces at the hand did not vary. The sensitivity of cell activity to arm posture in this isometric task suggests that MI possesses information about the intrinsic posture-dependent mechanical properties of the peripheral skeletomuscular system.
62. Scott SH: Comparison of onset time and magnitude of activity for proximal arm muscles and motor cortical cells prior to reaching movements. J Neurophysiol 1997, 77:1016-1022. This study found that variations in the onset time and magnitude of shoulder and elbow muscle activity to initiate reaching movements in different directions were similar to those for functionally corresponding groups of MI cells. These results suggest an important role for motor cortex in coordinating motor patterns at the shoulder and elbow during reaching movements.
63. Bennett KM, Lemon RN: Corticomotoneuronal contribution to the fractionation of muscle activity during precision grip in the monkey. J Neurophysiol 1996, 75:1826-1842. This study looked at how the activity of Corticomotoneuronal (CM) cells in monkeys may contribute to the coordinated motor patterns of their target muscles during a precision grip task. The activity of CM cells that produced postspike facilitation (PSF) of EMG in two hand muscles were examined during different periods of the motor task. They found that when the muscle with the largest PSF was more active than the other target muscle, the CM cell discharged at a higher rate than when the reverse was true. This suggests that the task-related activity of CM cells often parallels their pattern of facilitation on their target muscles, supporting a role in the fractionation of multi-muscle contractile patterns.
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