Spatial organization of precentral cortex in awake primates. I. Somatosensory inputs.

Wong, Yiu Chung; Kwan, Hon C.; MacKay, William A.; Murphy, John T.

doi:10.1152/jn.1978.41.5.1107

Cited by 137 publications

(62 citation statements)

References 7 publications

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“…These included left M1/PMd, S1, IPL (BA 5 and 7), and SMA/CCZ. Similarly elevated activities were also observed in single-unit recording studies in monkeys during both active and passive movements in M1 Wong et al 1978), PMd , S1 , area 5 , and SMA (Brinkman and Porter 1979;Tanji and Kurata 1979). Passive response to imposed movement has been regarded as a hallmark of those brain regions participating in the optimal feedback control of motor activity (Scott 2004).…”

Section: Optimality Of Wrist Posture Controlmentioning

confidence: 58%

Neural and Electromyographic Correlates of Wrist Posture Control

Suminski

Rao

Mosier

et al. 2007

Journal of Neurophysiology

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Suminski AJ, Rao SM, Mosier KM, Scheidt RA. Neural and electromyographic correlates of wrist posture control. J Neurophysiol 97: 1527Neurophysiol 97: -1545Neurophysiol 97: , 2007. First published November 29, 2006; doi:10.1152/jn.01160.2006. In identical experiments in and out of a MR scanner, we recorded functional magnetic resonance imaging and electromyographic correlates of wrist stabilization against constant and time-varying mechanical perturbations. Positioning errors were greatest while stabilizing random torques. Wrist muscle activity lagged changes in joint angular velocity at latencies suggesting trans-cortical reflex action. Drift in stabilized hand positions gave rise to frequent, accurately directed, corrective movements, suggesting that the brain maintains separate representations of desired wrist angle for feedback control of posture and the generation of discrete corrections. Two patterns of neural activity were evident in the blood-oxygenation-level-dependent (BOLD) time series obtained during stabilization. A cerebello-thalamo-cortical network showed significant activity whenever position errors were present. Here, changes in activation correlated with moment-by-moment changes in position errors (not force), implicating this network in the feedback control of hand position. A second network, showing elevated activity during stabilization whether errors were present or not, included prefrontal cortex, rostral dorsal premotor and supplementary motor area cortices, and inferior aspects of parietal cortex. BOLD activation in some of these regions correlated with positioning errors integrated over a longer timeframe consistent with optimization of feedback performance via adjustment of the behavioral goal (feedback setpoint) and the planning and execution of internally generated motor actions. The finding that nonoverlapping networks demonstrate differential sensitivity to kinematic performance errors over different time scales supports the hypothesis that in stabilizing the hand, the brain recruits distinct neural systems for feedback control of limb position and for evaluation/adjustment of controller parameters in response to persistent errors.

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Section: Optimality Of Wrist Posture Controlmentioning

confidence: 58%

Neural and Electromyographic Correlates of Wrist Posture Control

Suminski

Rao

Mosier

et al. 2007

Journal of Neurophysiology

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“…As might be expected, cutaneous modalities are particularly well represented among motor cortex neurones with inputs from the hand or fingers (Rosen & Asanuma, 1972;Wong et al 1978). From previous samples of area 4 neurones representing input from all parts of the monkey's forelimb, found only 10-6 % ofneurones sensitive to cutaneous stimuli, and Wong et al (1978), 17-8 %.…”

Section: Discussionmentioning

confidence: 74%

Functional properties of monkey motor cortex neurones receiving afferent input from the hand and fingers

Lemon

1981

The Journal of Physiology

162

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SUMMARY1. Records have been made from area 4 of the cerebral cortex in five conscious monkeys. The properties of 216 neurones responsive to natural stimulation of the hand and fingers have been investigated.2. 46 % ofthese neurones responded only to cutaneous stimulation (especially light brushing across the glabrous skin) and a further 38 % responded only to movement of the digits. 4 % responded to brief prods of the hand. 12 % of the sample responded to more than one stimulus modality.3. Many hand-input neurones, including pyramidal tract neurones, responded at short-latency (8-15 msec) to light mechanical stimulation of the hand and to weak electrical stimulation of the median nerve.4. Responsive neurones were found at all depths of the cortical grey matter. Responses ofshortest latency were encountered in neurones probably located in layers IV and V.5. The behaviour of eighty hand-input neurones was analysed during a simple, stereotyped task which involved pulling a lever and collecting a food reward from a small well. For comparison, the activity of 117 neurones with inputs from the wrist, elbow or shoulder was also analysed.6. Nearly all hand-input neurones modulated their activity either before (48/80) or during (29/80) the retrieval of the reward which required precision grip between index finger and thumb. Many were silent during proximal arm movements and some displayed activity patterns independent of these movements.7. By contrast, the activity of many neurones with proximal arm (elbow, shoulder) inputs was unrelated to food retrieval and manipulation, but well related to arm movements.8. Forty-three of the eighty neurones had cutaneous input from the hand. Twenty-seven were active before hand contact. Thirty-five modulated their discharge when contact was made (twenty-one excitation, fourteen inhibition).9. Most hand-input neurones were more active during fractionated movements of the hand or fingers than during power or ball grips requiring simultaneous flexion of all digits. Neurones with glabrous inputs often showed intense activity during small, precise finger movements and during active tactile exploration without the aid of vision. 0022-3751/81/3680-0935 $07.50 (© 1981 The Physiological Society 498 R. N. LEMON 10. Analysis of the discharge frequency of twenty-five hand-input neurones revealed that some (mainly non-pyramidal tract neurones) had a similar mean frequency and range of modulation during both active movement and passive stimulation. Others (mainly pyramidal tract neurones) had a greater frequency range and higher mean frequency during active than during passive movements.

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“…The integration of oculomotor and head-movement feedback on premotor neurons is consistent with the proposal that the gaze control system is designed to guarantee accurate gaze shifts rather than enforce a specific eye or head trajectory. Similarly, for the limb control system, previous studies have shown that neurons in the primary motor cortex (area M1) respond to afferent feedback resulting from passive movements of multiple joints (Wong et al, 1978;Scott and Kalaska, 1997) and cutaneous stimulation (Strick and Preston, 1978;Lemon, 1981). It is likely that these sensory inputs mediate the dynamic sensory feedback required to account for the rapid (i.e., as short as 20 ms) responses of M1 neurons to limb perturbations during hand stabilization (Wolpaw, 1980).…”

Section: Feedback and The Control Of Gaze Shiftsmentioning

confidence: 89%

Premotor Correlates of Integrated Feedback Control for Eye–Head Gaze Shifts

Sylvestre

Cullen

2006

J. Neurosci.

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Simple activities like picking up the morning newspaper or catching a ball require finely coordinated movements of multiple body segments. How our brain readily achieves such kinematically complex yet remarkably precise multijoint movements remains a fundamental and unresolved question in neuroscience. Many prevailing theoretical frameworks ensure multijoint coordination by means of integrative feedback control. However, to date, it has proven both technically and conceptually difficult to determine whether the activity of motor circuits is consistent with integrated feedback coding. Here, we tested this proposal using coordinated eye-head gaze shifts as an example behavior. Individual neurons in the premotor network that command saccadic eye movements were recorded in monkeys trained to make voluntary eye-head gaze shifts. Head-movement feedback was experimentally controlled by unexpectedly and transiently altering the head trajectory midflight during a subset of movements. We found that the duration and dynamics of neuronal responses were appropriately updated following head perturbations to preserve global movement accuracy. Perturbation-induced increases in gaze shift durations were accompanied by equivalent changes in response durations so that neuronal activity remained tightly synchronized to gaze shift offset. In addition, the saccadic command signal was updated on-line in response to head perturbations applied during gaze shifts. Nearly instantaneous updating of responses, coupled with longer latency changes in overall discharge durations, indicated the convergence of at least two levels of feedback. We propose that this strategy is likely to have analogs in other motor systems and provides the flexibility required for fine-tuning goal-directed movements.

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Spatial organization of precentral cortex in awake primates. I. Somatosensory inputs.

Cited by 137 publications

References 7 publications

Neural and Electromyographic Correlates of Wrist Posture Control

Neural and Electromyographic Correlates of Wrist Posture Control

Functional properties of monkey motor cortex neurones receiving afferent input from the hand and fingers

Premotor Correlates of Integrated Feedback Control for Eye–Head Gaze Shifts

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