scholarly journals The primary motor cortex prospectively computes the spinal reflex

2020 ◽  
Author(s):  
Tatsuya Umeda ◽  
Tadashi Isa ◽  
Yukio Nishimura
Keyword(s):  
Motor Cortex ◽  
Muscle Activity ◽  
Muscle Activation ◽  
Primary Motor Cortex ◽  
Linear Models ◽  
Movement Control ◽  
Spinal Reflex ◽  
Afferent Activity ◽  
Precise Movement ◽  
Behaving Monkeys

AbstractThe spinal reflex transforms sensory signals to generate muscle activity. However, it is unknown how the motor cortex (MCx) takes the spinal reflex into account when performing voluntary limb movements. We simultaneously recorded the activity of the MCx, afferent neurons, and forelimb muscles in behaving monkeys. We decomposed muscle activity into subcomponents explained by the MCx or afferent activity using linear models. Long preceding activity in the MCx, which is responsible for subsequent afferent activity, had the same spatiotemporal contribution to muscle activity as afferent activity, indicating that the MCx drives muscle activity not only by direct descending activation but also by trans-afferent descending activation. Therefore, the MCx implements internal models that prospectively estimate muscle activation via the spinal reflex for precise movement control.

scholarly journals Calcium Transient Dynamics of Neural Ensembles in the Primary Motor Cortex of Naturally Behaving Monkeys

Cell Reports ◽  
2018 ◽  
Vol 24 (8) ◽  
pp. 2191-2195.e4 ◽  
Author(s):  
Takahiro Kondo ◽  
Risa Saito ◽  
Masaki Otaka ◽  
Kimika Yoshino-Saito ◽  
Akihiro Yamanaka ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Calcium Transient ◽  
Transient Dynamics ◽  
Neural Ensembles ◽  
Behaving Monkeys

Cathodal transcranial direct current stimulation of the primary motor cortex improves selective muscle activation in the ipsilateral arm

2011 ◽  
Vol 105 (6) ◽  
pp. 2937-2942 ◽  
Author(s):  
Alana B. McCambridge ◽  
Lynley V. Bradnam ◽  
Cathy M. Stinear ◽  
Winston D. Byblow
Keyword(s):  
Motor Cortex ◽  
Upper Limb ◽  
Direct Current ◽  
Transcranial Direct Current Stimulation ◽  
Muscle Activation ◽  
Primary Motor Cortex ◽  
Selectivity Ratio ◽  
Direct Current Stimulation ◽  
Antagonist Muscles ◽  
Stimulation Of

Proximal upper limb muscles are represented bilaterally in primary motor cortex. Goal-directed upper limb movement requires precise control of proximal and distal agonist and antagonist muscles. Failure to suppress antagonist muscles can lead to abnormal movement patterns, such as those commonly experienced in the proximal upper limb after stroke. We examined whether noninvasive brain stimulation of primary motor cortex could be used to improve selective control of the ipsilateral proximal upper limb. Thirteen healthy participants performed isometric left elbow flexion by contracting biceps brachii (BB; agonist) and left forearm pronation (BB antagonist) before and after 20 min of cathodal transcranial direct current stimulation (c-tDCS) or sham tDCS of left M1. During the tasks, motor evoked potentials (MEPs) in left BB were acquired using single-pulse transcranial magnetic stimulation of right M1 150–270 ms before muscle contraction. As expected, left BB MEPs were facilitated before flexion and suppressed before pronation. After c-tDCS, left BB MEP amplitudes were reduced compared with sham stimulation, before pronation but not flexion, indicating that c-tDCS enhanced selective muscle activation of the ipsilateral BB in a task-specific manner. The potential for c-tDCS to improve BB antagonist control correlated with BB MEP amplitude for pronation relative to flexion, expressed as a selectivity ratio. This is the first demonstration that selective muscle activation in the proximal upper limb can be improved after c-tDCS of ipsilateral M1 and that the benefits of c-tDCS for selective muscle activation may be most effective in cases where activation strategies are already suboptimal. These findings may have relevance for the use of tDCS in rehabilitation after stroke.

Motor control: spinal and cortical mechanisms

2016 ◽  
Author(s):  
David Burke
Keyword(s):  
Motor Control ◽  
Motor Cortex ◽  
Voluntary Movement ◽  
Primary Motor Cortex ◽  
Lower Limbs ◽  
Spinal Reflex ◽  
Extensive Literature ◽  
Spinal Level ◽  
Corticospinal System ◽  
The Brain

There is extensive machinery at cerebral and spinal levels to support voluntary movement, but spinal mechanisms are often ignored by clinicians and researchers. For movements of the upper and lower limbs, what the brain commands can be modified or even suppressed completely at spinal level. The corticospinal system is the executive pathway for movement arising largely from primary motor cortex, but movement is not initiated there, and other pathways normally contribute to movement. Greater use of these pathways can allow movement to be restored when the corticospinal system is damaged by, e.g. stroke, but there can be unwanted consequences of this ‘plasticity’. There is an extensive literature on cerebral mechanisms in the control of movement, and an equally large literature on spinal reflex function and the changes that occur during movement, and when pathology results in weakness and/or spasticity.

scholarly journals The motor cortex uses active suppression to sculpt movement

2020 ◽  
Vol 6 (34) ◽  
pp. eabb8395 ◽  
Author(s):  
Darcy M. Griffin ◽  
Peter L. Strick
Keyword(s):  
Motor Cortex ◽  
Muscle Activity ◽  
Primary Motor Cortex ◽  
Spatiotemporal Patterns ◽  
Complex Pattern ◽  
Antagonist Muscle ◽  
Active Suppression ◽  
Antagonist Muscles ◽  
Output Neurons ◽  
Command Signal

Even the simplest movements are generated by a remarkably complex pattern of muscle activity. Fast, accurate movements at a single joint are produced by a stereotyped pattern that includes a decrease in any preexisting activity in antagonist muscles. This premovement suppression is necessary to prevent the antagonist muscle from opposing movement generated by the agonist muscle. Here, we provide evidence that the primary motor cortex (M1) sends a command signal that generates this premovement suppression. Thus, output neurons in M1 sculpt complex spatiotemporal patterns of motor output not only by actively turning on muscles but also by actively turning them off.

scholarly journals Primary motor cortex neurons classified in a postural task predict muscle activation patterns in a reaching task

2016 ◽  
Vol 115 (4) ◽  
pp. 2021-2032 ◽  
Author(s):  
Ethan A. Heming ◽  
Timothy P. Lillicrap ◽  
Mohsen Omrani ◽  
Troy M. Herter ◽  
J. Andrew Pruszynski ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Muscle Activation ◽  
Primary Motor Cortex ◽  
Network Connectivity ◽  
Spatiotemporal Patterns ◽  
Neural Population ◽  
Activation Patterns ◽  
Reaching Task ◽  
Muscle Activation Patterns ◽  
Muscle Groups

Primary motor cortex (M1) activity correlates with many motor variables, making it difficult to demonstrate how it participates in motor control. We developed a two-stage process to separate the process of classifying the motor field of M1 neurons from the process of predicting the spatiotemporal patterns of its motor field during reaching. We tested our approach with a neural network model that controlled a two-joint arm to show the statistical relationship between network connectivity and neural activity across different motor tasks. In rhesus monkeys, M1 neurons classified by this method showed preferred reaching directions similar to their associated muscle groups. Importantly, the neural population signals predicted the spatiotemporal dynamics of their associated muscle groups, although a subgroup of atypical neurons reversed their directional preference, suggesting a selective role in antagonist control. These results highlight that M1 provides important details on the spatiotemporal patterns of muscle activity during motor skills such as reaching.

Task-related changes in intracortical inhibition assessed with paired- and triple-pulse transcranial magnetic stimulation

2015 ◽  
Vol 113 (5) ◽  
pp. 1470-1479 ◽  
Author(s):  
George M. Opie ◽  
Michael C. Ridding ◽  
John G. Semmler
Keyword(s):  
Transcranial Magnetic Stimulation ◽  
Motor Cortex ◽  
Magnetic Stimulation ◽  
Muscle Activation ◽  
Primary Motor Cortex ◽  
Index Finger ◽  
Precision Grip ◽  
Intracortical Inhibition ◽  
Presynaptic Mechanisms ◽  
First Dorsal Interosseous Muscle

Recent research has demonstrated a task-related modulation of postsynaptic intracortical inhibition within primary motor cortex for tasks requiring isolated (abduction) or synergistic (precision grip) muscle activation. The current study sought to investigate task-related changes in pre- and postsynaptic intracortical inhibition in motor cortex. In 13 young adults (22.5 ± 3.5 yr), paired-pulse transcranial magnetic stimulation (TMS) was used to measure short (SICI)- and long-interval intracortical inhibition (LICI) (i.e., postsynaptic motor cortex inhibition) in first dorsal interosseous muscle, and triple-pulse TMS was used to investigate changes in SICI-LICI interactions (i.e., presynaptic motor cortex inhibition). These measurements were obtained at rest and during muscle activation involving isolated abduction of the index finger and during a precision grip using the index finger and thumb. SICI was reduced during abduction and precision grip compared with rest, with greater reductions during precision grip. The modulation of LICI during muscle activation depended on the interstimulus interval (ISI; 100 and 150 ms) but was not different between abduction and precision grip. For triple-pulse TMS, SICI was reduced in the presence of LICI at both ISIs in resting muscle (reflecting presynaptic motor cortex inhibition) but was only modulated at the 150-ms ISI during index finger abduction. Results suggest that synergistic contractions are accompanied by greater reductions in postsynaptic motor cortex inhibition than isolated contractions, but the contribution of presynaptic mechanisms to this disinhibition is limited. Furthermore, timing-dependent variations in LICI provide additional evidence that measurements using different ISIs may not represent activation of the same cortical process.

scholarly journals The primary afferent activity cannot capture the dynamical features of muscle activity during reaching movements

2017 ◽  
Author(s):  
Russell L. Hardesty ◽  
Matthew T. Boots ◽  
Sergiy Yakovenko ◽  
Valeriya Gritsenko
Keyword(s):  
Muscle Activity ◽  
Sensory Feedback ◽  
Muscle Activation ◽  
Activity Patterns ◽  
Afferent Feedback ◽  
Reaching Movements ◽  
Afferent Activity ◽  
Primary Afferent ◽  
Limb Dynamics ◽  
Dynamical Features

AbstractThe stabilizing role of sensory feedback in relation to realistic 3-dimensional movement dynamics remains poorly understood. The objective of this study was to quantify how primary afferent activity contributes to shaping muscle activity patterns during reaching movements. To achieve this objective, we designed a virtual reality task that guided healthy human subjects through a set of planar reaching movements with controlled kinematic and dynamic conditions that minimized inter-subject variability. Next, we integrated human upper-limb models of musculoskeletal dynamics and proprioception to analyze motion and major muscle activation patterns during these tasks. We recorded electromyographic and motion-capture data and used the integrated model to simulate joint kinematics, joint torques due to muscle contractions, muscle length changes, and simulated primary afferent feedback. The parameters of the primary afferent model were altered systematically to evaluate the effect of fusimotor drive. The experimental and simulated data were analyzed with hierarchical clustering. We found that the muscle activity patterns contained flexible task-dependent groups that consisted of co-activating agonistic and antagonistic muscles that changed with the dynamics of the task. The activity of muscles spanning only the shoulder generally grouped into a proximal cluster, while the muscles spanning the wrist grouped into a distal cluster. The bifunctional muscle spanning the shoulder and elbow were flexibly grouped with either proximal or distal cluster based on the dynamical requirements of the task. The composition and activation of these groups reflected the relative contribution of active and passive forces to each motion. In contrast, the simulated primary afferent feedback was most related to joint kinematics rather than dynamics, even though the primary afferent models had nonlinear dynamical components and variable fusimotor drive. Simulated physiological changes to the fusimotor drive were not sufficient to reproduce the dynamical features in muscle activity pattern. Altogether, these results suggest that sensory feedback signals are in a different domain from that of muscle activation signals. This indicates that to solve the neuromechanical problem, the central nervous system controls limb dynamics through task-dependent co-activation of muscles and non-linear modulation of monosynaptic primary afferent feedback.New & NoteworthyHere we answered the fundamental question in sensorimotor transformation of how primary afferent signals can contribute to the compensation for limb dynamics evident in muscle activity. We combined computational and experimental approaches to create a new experimental paradigm that challenges the nervous system with passive limb dynamics that either assists or resists the desired movement. We found that the active dynamical features present in muscle activity are unlikely to arise from direct feedback from primary afferents.

Effects on Muscle Activity From Microstimuli Applied to Somatosensory and Motor Cortex During Voluntary Movement in the Monkey

1997 ◽  
Vol 77 (5) ◽  
pp. 2446-2465 ◽  
Author(s):  
Gail L. Widener ◽  
Paul D. Cheney
Keyword(s):  
Motor Cortex ◽  
Muscle Activity ◽  
Voluntary Movement ◽  
Primary Motor Cortex ◽  
Large Fraction ◽  
Single Pulse ◽  
Motor Output ◽  
Emg Activity ◽  
Spike Triggered Averaging ◽  
Area 3A

Widener, Gail L. and Paul D. Cheney. Effects on muscle activity from microstimuli applied to somatosensory and motor cortex during voluntary movement in the monkey. J. Neurophysiol. 77: 2446–2465, 1997. It is well known that electrical stimulation of primary somatosensory cortex (SI) evokes movements that resemble those evoked from primary motor cortex. These findings have led to the concept that SI may possess motor capabilities paralleling those of motor cortex and speculation that SI could function as a robust relay mediating motor responses from central and peripheral inputs. The purpose of this study was to rigorously examine the motor output capabilities of SI areas with the use of the techniques of spike- and stimulus-triggered averaging of electromyographic (EMG) activity in awake monkeys. Unit recordings were obtained from primary motor cortex and SI areas 3a, 3b, 1, and 2 in three rhesus monkeys. Spike-triggered averaging was used to assess the output linkage between individual cells and motoneurons of the recorded muscles. Cells in motor cortex producing postspike facilitation (PSpF) in spike-triggered averages of rectified EMG activity were designated corticomotoneuronal (CM) cells. Motor output efficacy was also assessed by applying stimuli through the microelectrode and computing stimulus-triggered averages of rectified EMG activity. One hundred seventy-one sites in motor cortex and 68 sites in SI were characterized functionally and tested for motor output effects on muscle activity. The incidence, character, and magnitude of motor output effects from SI areas were in sharp contrast to effects from CM cell sites in primary motor cortex. Of 68 SI cells tested with spike-triggered averaging, only one area 3a cell produced significant PSpF in spike-triggered averages of EMG activity. In comparison, 20 of 171 (12%) motor cortex cells tested produced significant postspike effects. Single-pulse intracortical microstimulation produced effects at all CM cell sites in motor cortex but at only 14% of SI sites. The large fraction of SI effects that was inhibitory represented yet another marked difference between CM cell sites in motor cortex and SI sites (25% vs 93%). The fact that motor output effects from SI were frequently absent or very weak and predominantly inhibitory emphasizes the differing motor capabilities of SI compared with primary motor cortex.

scholarly journals Different contributions of primary motor cortex, reticular formation, and spinal cord to fractionated muscle activation

2018 ◽  
Vol 119 (1) ◽  
pp. 235-250 ◽  
Author(s):  
Boubker Zaaimi ◽  
Lauren R. Dean ◽  
Stuart N. Baker
Keyword(s):  
Spinal Cord ◽  
Motor Cortex ◽  
Reticular Formation ◽  
Upper Limb ◽  
Muscle Activation ◽  
Primary Motor Cortex ◽  
Cervical Spinal Cord ◽  
Motor Output ◽  
Natural Activity ◽  
Limb Muscles

Coordinated movement requires patterned activation of muscles. In this study, we examined differences in selective activation of primate upper limb muscles by cortical and subcortical regions. Five macaque monkeys were trained to perform a reach and grasp task, and electromyogram (EMG) was recorded from 10 to 24 muscles while weak single-pulse stimuli were delivered through microelectrodes inserted in the motor cortex (M1), reticular formation (RF), or cervical spinal cord (SC). Stimulus intensity was adjusted to a level just above threshold. Stimulus-evoked effects were assessed from averages of rectified EMG. M1, RF, and SC activated 1.5 ± 0.9, 1.9 ± 0.8, and 2.5 ± 1.6 muscles per site (means ± SD); only M1 and SC differed significantly. In between recording sessions, natural muscle activity in the home cage was recorded using a miniature data logger. A novel analysis assessed how well natural activity could be reconstructed by stimulus-evoked responses. This provided two measures: normalized vector length L, reflecting how closely aligned natural and stimulus-evoked activity were, and normalized residual R, measuring the fraction of natural activity not reachable using stimulus-evoked patterns. Average values for M1, RF, and SC were L = 119.1 ± 9.6, 105.9 ± 6.2, and 109.3 ± 8.4% and R = 50.3 ± 4.9, 56.4 ± 3.5, and 51.5 ± 4.8%, respectively. RF was significantly different from M1 and SC on both measurements. RF is thus able to generate an approximation to the motor output with less activation than required by M1 and SC, but M1 and SC are more precise in reaching the exact activation pattern required. Cortical, brainstem, and spinal centers likely play distinct roles, as they cooperate to generate voluntary movements. NEW & NOTEWORTHY Brainstem reticular formation, primary motor cortex, and cervical spinal cord intermediate zone can all activate primate upper limb muscles. However, brainstem output is more efficient but less precise in producing natural patterns of motor output than motor cortex or spinal cord. We suggest that gross muscle synergies from the reticular formation are sculpted and refined by motor cortex and spinal circuits to reach the finely fractionated output characteristic of dexterous primate upper limb movements.

Central Representation of Dynamics When Manipulating Handheld Objects

2006 ◽  
Vol 95 (2) ◽  
pp. 893-901 ◽  
Author(s):  
Theodore E. Milner ◽  
David W. Franklin ◽  
Hiroshi Imamizu ◽  
Mitsuo Kawato
Keyword(s):  
Motor Cortex ◽  
Internal Model ◽  
Muscle Activation ◽  
Primary Motor Cortex ◽  
Small Region ◽  
Unstable State ◽  
Moment Control ◽  
Central Representation ◽  
The Stability ◽  
The Moment

To explore the neural mechanisms related to representation of the manipulation dynamics of objects, we performed whole-brain fMRI while subjects balanced an object in stable and highly unstable states and while they balanced a rigid object and a flexible object in the same unstable state, in all cases without vision. In this way, we varied the extent to which an internal model of the manipulation dynamics was required in the moment-to-moment control of the object's orientation. We hypothesized that activity in primary motor cortex would reflect the amount of muscle activation under each condition. In contrast, we hypothesized that cerebellar activity would be more strongly related to the stability and complexity of the manipulation dynamics because the cerebellum has been implicated in internal model-based control. As hypothesized, the dynamics-related activation of the cerebellum was quite different from that of the primary motor cortex. Changes in cerebellar activity were much greater than would have been predicted from differences in muscle activation when the stability and complexity of the manipulation dynamics were contrasted. On the other hand, the activity of the primary motor cortex more closely resembled the mean motor output necessary to execute the task. We also discovered a small region near the anterior edge of the ipsilateral (right) inferior parietal lobule where activity was modulated with the complexity of the manipulation dynamics. We suggest that this is related to imagining the location and motion of an object with complex manipulation dynamics.

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