Neurophysiology of motor control

How does the brain control our movements?

The role of ipsilateral cortical control of the upper limb

We are elucidating the role of ipsilateral motor cortex during unimanual and bimanual movement. In collaboration with Richard Ivry and Robert Knight, we are conducting parallel neurophysiological studies in human and non-human primates. Electrocorticogram, local field potential, and single unit activity neural recordings will be used to analyze neural activity at different levels of integration.

Previous work from our group has demonstrated that distributed activity in primate motor areas reliably represents ipsilateral upper limb kinematics in monkey and human. This information can be decoded by applying linear methods to neural signals at a variety of temporal and spatial scales, and can be successfully incorporated into a closed-loop BMI system. However, the functional contribution of ipsilateral motor cortex to limb movement remains unclear.

We are testing four, possibly overlapping, hypotheses of ipsilateral representation:

  • H1) Activity in ipsilateral motor cortex complements activity in the contralateral hemisphere, providing additional control through the engagement of independent ipsilateral motor pathways.
  • H2) Movements of one arm induce activity patterns within ipsilateral motor cortex that are related to the mirror-symmetric movement of the other hand.
  • H3) Activity in ipsilateral motor cortex reflects the simultaneous, bilateral preparation of unimanual actions.
  • H4) Activity in ipsilateral motor cortex includes a representation of motor commands, or states, from the contralateral hemisphere, information that is especially relevant for coordinating bimanual movements.
Schematics of four hypotheses of movement representation in ipsilateral motor cortex. The participant plans to move the left hand to the right (for simplicity, this goal is represented by the red arrow in right parietal cortex). This goal is translated by right motor cortex into a control signal for the left hand (solid arrow). Dotted arrows indicate potential/primed right hand movements.

The effects of beta oscillations on motor skills

Neural oscillations are a type of rhythmic activity where a large population of neurons synchronize their oscillatory increases in activity. Oscillations are divided into categories based on the frequency of oscillation. Beta oscillations occur at a frequency of 13-30 cycles per second and have been observed in the motor cortex during motor actions such as reaching and grasping.

To test the effects of beta oscillations on behavior, we trained our subjects to control the frequency of their own brain waves through a neurofeedback task, and then asked them to complete an easy reaching task. We found that beta oscillations correlate with slowed onset of movement.

From “Beta band oscillations in motor cortex reflect neural population signals that delay movement onset.” Click to view the article in eLife.

Selected Publications

Cortical representation of ipsilateral arm movements in monkey and man (2009)

Ganguly K., Secundo L., Ranade G., Orsborn A., Chang E.F., Dimitrov D.F., Wallis J.D., Barbaro N.M., Knight R.T. and Carmena J.M. (2009) Cortical representation of ipsilateral arm movements in monkey and man. Journal of Neuroscience 29(41).

Abstract

A fundamental organizational principle of the primate motor system is cortical control of contralateral limb movements. Motor areas also appear to play a role in the control of ipsilateral limb movements. Several studies in monkeys have shown that individual neurons in primary motor cortex (M1) may represent, on average, the direction of movements of the ipsilateral arm. Given the increasing body of evidence demonstrating that neural ensembles can reliably represent information with a high temporal resolution, here we characterize the distributed neural representation of ipsilateral upper limb kinematics in both monkey and man. In two macaque monkeys trained to perform center-out reaching movements, we found that the ensemble spiking activity in M1 could continuously represent ipsilateral limb position. Interestingly, this representation was more correlated with joint angles than hand position. Using bilateral electromyography recordings, we excluded the possibility that postural or mirror movements could exclusively account for these findings. In addition, linear methods could decode limb position from cortical field potentials in both monkeys. We also found that M1 spiking activity could control a biomimetic brain–machine interface reflecting ipsilateral kinematics. Finally, we recorded cortical field potentials from three human subjects and also consistently found evidence of a neural representation for ipsilateral movement parameters. Together, our results demonstrate the presence of a high-fidelity neural representation for ipsilateral movement and illustrates that it can be successfully incorporated into a brain–machine interface.

Microstimulation activates a handful of muscle synergies (2012)

Overduin S.A., d’Avella A., Carmena J.M. and Bizzi E. (2012) Microstimulation activates a handful of muscle synergies. Neuron 76(6), pp. 1071-1077.

Abstract

Muscle synergies have been proposed as a mechanism to simplify movement control. Whether these coactivation patterns have any physiological reality within the nervous system remains unknown. Here we applied electrical microstimulation to motor cortical areas of rhesus macaques to evoke hand movements. Movements tended to converge toward particular postures, driven by synchronous bursts of muscle activity. Across stimulation sites, the muscle activations were reducible to linear sums of a few basic patterns—each corresponding to a muscle synergy evident in voluntary reach, grasp, and transport movements made by the animal. These synergies were represented nonuniformly over the cortical surface. We argue that the brain exploits these properties of synergies—postural equivalence, low dimensionality, and topographical representation—to simplify motor planning, even for complex hand movements.

Cortical representation of muscle synergies in the primate brain (2015)

Overduin S.A., d’Avella A., Roh J., Carmena J.M.* and Bizzi E.* (2015) Cortical representation of muscle synergies in the primate brain. Journal of Neuroscience 35(37), pp. 12615-12624; doi: 10.1523/JNEUROSCI.4302-14.2015.

Abstract

Evidence suggests that the CNS uses motor primitives to simplify movement control, but whether it actually stores primitives instead of computing solutions on the fly to satisfy task demands is a controversial and still-unanswered possibility. Also in contention is whether these primitives take the form of time-invariant muscle coactivations (“spatial” synergies) or time-varying muscle commands (“spatiotemporal” synergies). Here, we examined forelimb muscle patterns and motor cortical spiking data in rhesus macaques (Macaca mulatta) handling objects of variable shape and size. From these data, we extracted both spatiotemporal and spatial synergies using non-negative decomposition. Each spatiotemporal synergy represents a sequence of muscular or neural activations that appeared to recur frequently during the animals’ behavior. Key features of the spatiotemporal synergies (including their dimensionality, timing, and amplitude modulation) were independently observed in the muscular and neural data. In addition, both at the muscular and neural levels, these spatiotemporal synergies could be readily reconstructed as sequential activations of spatial synergies (a subset of those extracted independently from the task data), suggestive of a hierarchical relationship between the two levels of synergies. The possibility that motor cortex may execute even complex skill using spatiotemporal synergies has novel implications for the design of neuroprosthetic devices, which could gain computational efficiency by adopting the discrete and low-dimensional control that these primitives imply.

Neural oscillations: beta band activity across motor networks (2015)

Khanna P. and Carmena J.M. (2015) Neural oscillations: beta band activity across motor networks. Current Opinion in Neurobiology 32, pp. 60-67. [Review]

Abstract

Local field potential (LFP) activity in motor cortical and basal ganglia regions exhibits prominent beta (15-40Hz) oscillations during reaching and grasping, muscular contraction, and attention tasks. While in vitro and computational work has revealed specific mechanisms that may give rise to the frequency and duration of this oscillation, there is still controversy about what behavioral processes ultimately drive it. Here, simultaneous behavioral and large-scale neural recording experiments from non-human primate and human subjects are reviewed in the context of specific hypotheses about how beta band activity is generated. Finally, a new experimental paradigm utilizing operant conditioning combined with motor tasks is proposed as a way to further investigate this oscillation.

Beta band oscillations in motor cortex reflect neural population signals that delay movement onset (2017)

Khanna P. and Carmena J.M. (2017) Beta band oscillations in motor cortex reflect neural population signals that delay movement onset. eLife 6:e24573 DOI: 10.7554/eLife.24573.

Abstract

Motor cortical beta oscillations have been reported for decades, yet their behavioral correlates remain unresolved. Some studies link beta oscillations to changes in underlying neural activity, but the specific behavioral manifestations of these reported changes remain elusive. To investigate how changes in population neural activity, beta oscillations, and behavior are linked, we recorded multi-scale neural activity from motor cortex while three macaques performed a novel neurofeedback task. Subjects volitionally brought their beta oscillatory power to an instructed state and subsequently executed an arm reach. Reaches preceded by a reduction in beta power exhibited significantly faster movement onset times than reaches preceded by an increase in beta power. Further, population neural activity was found to shift farther from a movement onset state during beta oscillations that were neurofeedback-induced or naturally occurring during reaching tasks. This finding establishes a population neural basis for slowed movement onset following periods of beta oscillatory activity.

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