Quantitative comparison of corticospinal tracts arising from different cortical areas in humans

The corticospinal tract (CST), which plays a major role in the control of voluntary limb movements, arises from multiple motor- and somatosensory-related areas in monkeys. Although the cortical origin and quantitative differences in CSTs among the cortical areas are well-documented in monkeys, they are unclear in humans. We quantitatively investigated the CSTs from the cerebral cortex to the cervical cord in healthy volunteers using fiber tractography of diffusion-weighted magnetic resonance imaging. The corticospinal (CS) streamlines arose from nine cortical areas: primary motor area (mean ± SD = 49.71 ± 1.61%), dorsal (16.33 ± 1.37%) and ventral (11.02 ± 0.90%) premotor cortex, supplementary motor area (5.14 ± 0.36%), pre-supplementary motor area (2.46 ± 0.26%), primary somatosensory cortex (11.06 ± 0.91%), Brodmann area 5 (0.88 ± 0.09%), caudal cingulate zone (1.70 ± 0.30%), and posterior part of the rostral cingulate zone (1.70 ± 0.34%). In all cortical areas, the number of CS streamlines gradually decreased from the rostral to caudal spinal segments, but the proportion was maintained throughout the cervical cord. Over 75% of CS streamlines arose from the lateral surface of the frontal lobe, which may explain the voluntary control of dexterous and flexible limb movements in humans. (197/200 words).

Non-human Primate Models to Explore the Adaptive Mechanisms After Stroke

The brain has the ability to reconstruct neural structures and functions to compensate for the brain lesions caused by stroke, although it is highly limited in primates including humans. Animal studies in which experimental lesions were induced in the brain have contributed to the current understanding of the neural mechanisms underlying functional recovery. Here, I have highlighted recent advances in non-human primate models using primate species such as macaques and marmosets, most of which have been developed to study the mechanisms underlying the recovery of motor functions after stroke. Cortical lesion models have been used to investigate motor recovery after lesions to the cortical areas involved in movements of specific body parts. Models of a focal stroke at the posterior internal capsule have also been developed to bridge the gap between the knowledge obtained by cortical lesion models and the development of intervention strategies because the severity and outcome of motor deficits depend on the degree of lesions to the region. This review will also introduce other stroke models designed to study the plastic changes associated with development and recovery from cognitive and sensory impairments. Although further validation and careful interpretation are required, considering the differences between non-human primate brains and human brains, studies using brain-lesioned non-human primates offer promise for improving translational outcomes.

Quantitative analysis of voluntary movement and anticipatory postural adjustments: a functional approach

Daily living activities and tasks like standing forward reaching present complex Anticipatory Postural Adjustments (APAs), and an objective, repeatable, subject- and task-dependent procedure to detect Voluntary Movements (VM) and APAs onsets is still missing. This paper proposes a new approach to the VMs study, based on a functional mechanical interpretation of the movement performing, which allows defining kinematic and dynamic APAs. A protocol for the identification of VMs and APAs onsets in the reaching movement is presented. Acquired data on 9 healthy young subjects enable a preliminary validation of this method suitability as support for an objective quantification of APAs.

Shared internal models for feedforward and feedback control of arm dynamics in non-human primates

Previous work has shown that humans account for and learn novel properties or the arm's dynamics, and that such learning causes changes in both the predictive (i.e., feedforward) control of reaching and reflex (i.e., feedback) responses to mechanical perturbations. Here we show that similar observations hold in old-world monkeys (Macaca fascicularis). Two monkeys were trained to use an exoskeleton to perform a single-joint elbow reaching and to respond to mechanical perturbations that created pure elbow motion. Both of these tasks engaged robust shoulder muscle activity as required to account for the torques that typically arise at the shoulder when the forearm rotates around the elbow joint (i.e., intersegmental dynamics). We altered these intersegmental arm dynamics by having the monkeys generate the same elbow movements with the shoulder joint either free to rotate, as normal, or fixed by the robotic manipulandum, which eliminates the shoulder torques caused by forearm rotation. After fixing the shoulder joint, we found a systematic reduction in shoulder muscle activity. In addition, after releasing the shoulder joint again, we found evidence of kinematic aftereffects (i.e., reach errors) in the direction predicted if failing to compensate for normal arm dynamics. We also tested whether such learning transfers to feedback responses evoked by mechanical perturbations and found a reduction in shoulder feedback responses, as appropriate for these altered arm intersegmental dynamics. Demonstrating this learning and transfer in non-human primates will allow the investigation of the neural mechanisms involved in feedforward and feedback control of the arm's dynamics.

Generalizing movement patterns following shoulder fixation

Generalizing newly learned movement patterns beyond the training context is challenging for most motor learning situations. Here we tested whether learning of a new physical property of the arm during self-initiated reaching generalizes to new arm configurations. Human participants performed a single-joint elbow reaching task and/or countered mechanical perturbations that created pure elbow motion with the shoulder joint free to rotate or locked by the manipulandum. With the shoulder free, we found activation of shoulder extensor muscles for pure elbow extension trials, appropriate for countering torques that arise at the shoulder due to forearm rotation. After locking the shoulder joint, we found a partial reduction in shoulder muscle activity, appropriate because locking the shoulder joint cancels the torques that arise at the shoulder due to forearm rotation. In our first three experiments, we tested whether and to what extent this partial reduction in shoulder muscle activity generalizes when reaching in different situations: 1) different initial shoulder orientation, 2) different initial elbow orientation, and 3) different reach distance/speed. We found generalization for the different shoulder orientation and reach distance/speed as measured by a reliable reduction in shoulder activity in these situations but no generalization for the different elbow orientation. In our fourth experiment, we found that generalization is also transferred to feedback control by applying mechanical perturbations and observing reflex responses in a distinct shoulder orientation. These results indicate that partial learning of new intersegmental dynamics is not sufficient for modifying a general internal model of arm dynamics.NEW & NOTEWORTHY Here we show that partially learning to reduce shoulder muscle activity following shoulder fixation generalizes to other movement conditions, but it does not generalize globally. These findings suggest that the partial learning of new intersegmental dynamics is not sufficient for modifying a general internal model of the arm's dynamics.

Feedforward and Feedback Control Share an Internal Model of the Arm's Dynamics

Recent work has shown that, when countering external forces, the nervous system adjusts not only predictive (i.e., feedforward) control of reaching but also reflex (i.e., feedback) responses to mechanical perturbations. Here we show that altering the physical properties of the arm (i.e., intersegmental dynamics) causes the nervous system to adjust feedforward control and that this learning transfers to feedback responses even though the latter were never directly trained. Forty-five human participants (30 females) performed a single-joint elbow reaching task and countered mechanical perturbations that created pure elbow motion. In our first experiment, we altered intersegmental dynamics by asking participants to generate pure elbow movements when the shoulder joint was either free to rotate or locked by the robotic manipulandum. With the shoulder unlocked, we found robust activation of shoulder flexor muscles for pure elbow flexion trials, as required to counter the interaction torques that arise at the shoulder because of forearm rotation. After locking the shoulder joint, which cancels these interaction torques, we found a substantial reduction in shoulder muscle activity over many trials. In our second experiment, we tested whether such learning transfers to feedback control. Mechanical perturbations applied to the arm with the shoulder unlocked revealed that feedback responses also account for intersegmental dynamics. After locking the shoulder joint, we found a substantial reduction in shoulder feedback responses, as appropriate for the altered intersegmental dynamics. Our work suggests that feedforward and feedback control share an internal model of the arm's dynamics.SIGNIFICANCE STATEMENT Here we show that altering the physical properties of the arm causes people to learn new motor commands and that this learning transfers to their reflex responses to unexpected mechanical perturbations, even though the reflex responses were never directly trained. Our results suggest that feedforward motor commands and reflex responses share an internal model of the arm's dynamics.

Space-Time Dynamics of Membrane Currents Evolve to Shape Excitation, Spiking, and Inhibition in the Cortex at Small and Large Scales

In the cerebral cortex, membrane currents, i.e., action potentials and other membrane currents, express many forms of space-time dynamics. In the spontaneous asynchronous irregular state, their space-time dynamics are local non-propagating fluctuations and sparse spiking appearing at unpredictable positions. After transition to active spiking states, larger structured zones with active spiking neurons appear, propagating through the cortical network, driving it into various forms of widespread excitation, and engaging the network from microscopic scales to whole cortical areas. At each engaged cortical site, the amount of excitation in the network, after a delay, becomes matched by an equal amount of space-time fine-tuned inhibition that might be instrumental in driving the dynamics toward perception and action.

Compensating for intersegmental dynamics across the shoulder, elbow, and wrist joints during feedforward and feedback control

Moving the arm is complicated by mechanical interactions that arise between limb segments. Such intersegmental dynamics cause torques applied at one joint to produce movement at multiple joints, and in turn, the only way to create single joint movement is by applying torques at multiple joints. We investigated whether the nervous system accounts for intersegmental limb dynamics across the shoulder, elbow, and wrist joints during self-initiated planar reaching and when countering external mechanical perturbations. Our first experiment tested whether the timing and amplitude of shoulder muscle activity account for interaction torques produced during single-joint elbow movements from different elbow initial orientations and over a range of movement speeds. We found that shoulder muscle activity reliably preceded movement onset and elbow agonist activity, and was scaled to compensate for the magnitude of interaction torques arising because of forearm rotation. Our second experiment tested whether elbow muscles compensate for interaction torques introduced by single-joint wrist movements. We found that elbow muscle activity preceded movement onset and wrist agonist muscle activity, and thus the nervous system predicted interaction torques arising because of hand rotation. Our third and fourth experiments tested whether shoulder muscles compensate for interaction torques introduced by different hand orientations during self-initiated elbow movements and to counter mechanical perturbations that caused pure elbow motion. We found that the nervous system predicted the amplitude and direction of interaction torques, appropriately scaling the amplitude of shoulder muscle activity during self-initiated elbow movements and rapid feedback control. Taken together, our results demonstrate that the nervous system robustly accounts for intersegmental dynamics and that the process is similar across the proximal to distal musculature of the arm as well as between feedforward (i.e., self-initiated) and feedback (i.e., reflexive) control.NEW & NOTEWORTHY Intersegmental dynamics complicate the mapping between applied joint torques and the resulting joint motions. We provide evidence that the nervous system robustly predicts these intersegmental limb dynamics across the shoulder, elbow, and wrist joints during reaching and when countering external perturbations.

Parallel processing of internal and external feedback in the spinocerebellar system of primates

Cerebellar control of voluntary movements is achieved by the integration of external and internal feedback information to adjust and correct properly ongoing actions. In the forelimb of primates, rostral-spinocerebellar tract (RSCT) neurons are thought to integrate segmental, descending, and afferent sources and relay upstream a compound signal that contains both an efference copy of the spinal-level motor command and the state of the periphery. We tested this hypothesis by implanting stimulating electrodes in the superior cerebellar peduncle and recording the activity of cervical spinal neurons in primates. To dissociate motor commands and proprioceptive signals, we used a voluntary wrist task and applied external perturbations to the movement. We identified a large group of antidromically activated RSCT neurons located in deep dorsal sites and a smaller fraction of postsynaptically activated (PSA) cells located in intermediate and ventral laminae. RSCT cells received sensory input from broad, proximally biased receptive fields (RFs) and were not affected by applied wrist perturbations. PSA cells received sensory information from distal RFs and were more strongly related to active and passive movements. The anatomical and functional properties of RSCT and PSA cells suggest that descending signals converging on PSA cells contribute to both motor preparation and motor control. In parallel, RSCT neurons relay upstream an integrated signal that encodes the state of working muscles and can contribute to distal-to-proximal coordination of action. Thus the rostral spinocerebellar system sends upstream an efference copy of the motor command but does not signal abrupt errors in the performed movement.NEW & NOTEWORTHY Cerebellar coordination of voluntary movements relies on integrating feedback information to update motor output. With the use of a novel protocol, we identified spinal neurons constituting the ascending and descending components of the forelimb spinocerebellar system in behaving primates. The data suggest that descending information contributes to both motor preparation and execution, whereas ascending information conveys the spinal level motor command, such that internal and external feedback is relayed through parallel pathways.

GPi Oscillatory Activity Differentiates Tics from the Resting State, Voluntary Movements, and the Unmedicated Parkinsonian State

Background: Deep brain stimulation (DBS) is an emerging treatment strategy for severe, medication-refractory Tourette syndrome (TS). Thalamic (Cm-Pf) and pallidal (including globus pallidus interna, GPi) targets have been the most investigated. While the neurophysiological correlates of Parkinson's disease (PD) in the GPi and subthalamic nucleus (STN) are increasingly recognized, these patterns are not well characterized in other disease states. Recent findings indicate that the cross-frequency coupling (CFC) between beta band and high frequency oscillations (HFOs) within the STN in PD patients is pathologic.

Methods: We recorded intraoperative local field potentials (LFPs) from the postero-ventrolateral GPi in three adult patients with TS at rest, during voluntary movements, and during tic activity and compared them to the intraoperative GPi-LFP activity recorded from four unmedicated PD patients at rest.

Results: In all PD patients, we noted excessive beta band activity (13–30 Hz) at rest which consistently modulated the amplitude of the co-existent HFOs observed between 200 and 400 Hz, indicating the presence of beta-HFO CFC. In all 3TS patients at rest, we observed theta band activity (4–7 Hz) and HFOs. Two patients had beta band activity, though at lower power than theta oscillations. Tic activity was associated with increased high frequency (200–400 Hz) and gamma band (35–200 Hz) activity. There was no beta-HFO CFC in TS patients at rest. However, CFC between the phase of 5–10 Hz band activity and the amplitude of HFOs was found in two TS patients. During tics, this shifted to CFC between the phase of beta band activity and the amplitude of HFOs in all subjects.

Conclusions: To our knowledge this is the first study that shows that beta-HFO CFC exists in the GPi of TS patients during tics and at rest in PD patients, and suggests that this pattern might be specific to pathologic/involuntary movements. Furthermore, our findings suggest that during tics, resting state 5–10 Hz-HFO CFC shifts to beta-HFO CFC which can be used to trigger stimulation in a closed loop system when tics are present.

Noninvasive Reactivation of Motor Descending Control after Paralysis

The present prognosis for the recovery of voluntary control of movement in patients diagnosed as motor complete is generally poor. Herein we introduce a novel and noninvasive stimulation strategy of painless transcutaneous electrical enabling motor control and a pharmacological enabling motor control strategy to neuromodulate the physiological state of the spinal cord. This neuromodulation enabled the spinal locomotor networks of individuals with motor complete paralysis for 2-6 years American Spinal Cord Injury Association Impairment Scale (AIS) to be re-engaged and trained. We showed that locomotor-like stepping could be induced without voluntary effort within a single test session using electrical stimulation and training. We also observed significant facilitation of voluntary influence on the stepping movements in the presence of stimulation over a 4-week period in each subject. Using these strategies we transformed brain-spinal neuronal networks from a dormant to a functional state sufficiently to enable recovery of voluntary movement in five out of five subjects. Pharmacological intervention combined with stimulation and training resulted in further improvement in voluntary motor control of stepping-like movements in all subjects. We also observed on-command selective activation of the gastrocnemius and soleus muscles when attempting to plantarflex. At the end of 18 weeks of weekly interventions the mean changes in the amplitude of voluntarily controlled movement without stimulation was as high as occurred when combined with electrical stimulation. Additionally, spinally evoked motor potentials were readily modulated in the presence of voluntary effort, providing electrophysiological evidence of the re-establishment of functional connectivity among neural networks between the brain and the spinal cord.

How capable is non-invasive EEG data of predicting the next movement? A mini review

In this study we summarize the features that characterize the pre-movements and pre-motor imageries (before imagining the movement) electroencephalography (EEG) data in humans from both Neuroscientists' and Engineers' point of view. We demonstrate what the brain status is before a voluntary movement and how it has been used in practical applications such as brain computer interfaces (BCIs). Usually, in BCI applications, the focus of study is on the after-movement or motor imagery potentials. However, this study shows that it is possible to develop BCIs based on the before-movement or motor imagery potentials such as the Bereitschaftspotential (BP). Using the pre-movement or pre-motor imagery potentials, we can correctly predict the onset of the upcoming movement, its direction and even the limb that is engaged in the performance. This information can help in designing a more efficient rehabilitation tool as well as BCIs with a shorter response time which appear more natural to the users.

Detection of self-paced reaching movement intention from EEG signals

Future neuroprosthetic devices, in particular upper limb, will require decoding and executing not only the user's intended movement type, but also when the user intends to execute the movement. This work investigates the potential use of brain signals recorded non-invasively for detecting the time before a self-paced reaching movement is initiated which could contribute to the design of practical upper limb neuroprosthetics. In particular, we show the detection of self-paced reaching movement intention in single trials using the readiness potential, an electroencephalography (EEG) slow cortical potential (SCP) computed in a narrow frequency range (0.1–1 Hz). Our experiments with 12 human volunteers, two of them stroke subjects, yield high detection rates prior to the movement onset and low detection rates during the non-movement intention period. With the proposed approach, movement intention was detected around 500 ms before actual onset, which clearly matches previous literature on readiness potentials. Interestingly, the result obtained with one of the stroke subjects is coherent with those achieved in healthy subjects, with single-trial performance of up to 92% for the paretic arm. These results suggest that, apart from contributing to our understanding of voluntary motor control for designing more advanced neuroprostheses, our work could also have a direct impact on advancing robot-assisted neurorehabilitation.

Stop-event-related potentials from intracranial electrodes reveal a key role of premotor and motor cortices in stopping ongoing movements

In humans, the ability to withhold manual motor responses seems to rely on a right-lateralized frontal–basal ganglia–thalamic network, including the pre-supplementary motor area and the inferior frontal gyrus (IFG). These areas should drive subthalamic nuclei to implement movement inhibition via the hyperdirect pathway. The output of this network is expected to influence those cortical areas underlying limb movement preparation and initiation, i.e., premotor (PMA) and primary motor (M1) cortices. Electroencephalographic (EEG) studies have shown an enhancement of the N200/P300 complex in the event-related potentials (ERPs) when a planned reaching movement is successfully stopped after the presentation of an infrequent stop-signal. PMA and M1 have been suggested as possible neural sources of this ERP complex but, due to the limited spatial resolution of scalp EEG, it is not yet clear which cortical areas contribute to its generation. To elucidate the role of motor cortices, we recorded epicortical ERPs from the lateral surface of the fronto-temporal lobes of five pharmacoresistant epileptic patients performing a reaching version of the countermanding task while undergoing presurgical monitoring. We consistently found a stereotyped ERP complex on a single-trial level when a movement was successfully cancelled. These ERPs were selectively expressed in M1, PMA, and Brodmann's area (BA) 9 and their onsets preceded the end of the stop process, suggesting a causal involvement in this executive function. Such ERPs also occurred in unsuccessful-stop (US) trials, that is, when subjects moved despite the occurrence of a stop-signal, mostly when they had long reaction times (RTs). These findings support the hypothesis that motor cortices are the final target of the inhibitory command elaborated by the frontal–basal ganglia–thalamic network.

Spatiotemporal mapping of cortical activity accompanying voluntary movements using an event-related beamforming approach

We describe a novel spatial filtering approach to the localization of cortical activity accompanying voluntary movements. The synthetic aperture magnetometry (SAM) minimum-variance beamformer algorithm was used to compute spatial filters three-dimensionally over the entire brain from single trial neuromagnetic recordings of subjects performing self-paced index finger movements. Images of instantaneous source power ("event-related SAM") computed at selected latencies revealed activation of multiple cortical motor areas prior to and following left and right index finger movements in individual subjects, even in the presence of low-frequency noise (e.g., eye movements). A slow premovement motor field (MF) reaching maximal amplitude approximately 50 ms prior to movement onset was localized to the hand area of contralateral precentral gyrus, followed by activity in the contralateral postcentral gyrus at 40 ms, corresponding to the first movement-evoked field (MEFI). A novel finding was a second activation of the precentral gyrus at a latency of approximately 150 ms, corresponding to the second movement-evoked field (MEFII). Group averaging of spatially normalized images indicated additional premovement activity in the ipsilateral precentral gyrus and the left inferior parietal cortex for both left and right finger movements. Weaker activations were also observed in bilateral premotor areas and the supplementary motor area. These results show that event-related beamforming provides a robust method for studying complex patterns of time-locked cortical activity accompanying voluntary movements, and offers a new approach for the localization of multiple cortical sources derived from neuromagnetic recordings in single subject and group data.

Increased synchronization of cortical oscillatory activities between human supplementary motor and primary sensorimotor areas during voluntary movements

In human, both primary and nonprimary motor areas are involved in the control of voluntary movements. However, the dynamics of functional coupling among different motor areas has not been fully clarified yet. Because it has been proposed that the functional coupling among cortical areas might be achieved by the synchronization of oscillatory activity, we investigated the electrocorticographic coherence between the supplementary motor and primary sensorimotor areas (SMA and S1-M1) by means of event-related partial coherence analysis in 11 intractable epilepsy patients. We found premovement increase of coherence between the SMA proper and S1-M1 at the frequency of 0-33 Hz and between the pre-SMA and S1-M1 at 0-18 Hz. Coherence between the SMA proper and M1 started to increase 0.9 sec before the movement onset and peaked 0.3 sec after the movement. There was no systematic difference within the SMA (SMA proper vs pre-SMA) or within the S1-M1, in terms of the time course as well as the peak value of coherence. The phase spectra revealed near-zero phase difference in 57% (20 of 35) of region pairs analyzed, and the remaining pairs showed inconsistent results. This increase of synchronization between multiple motor areas in the preparation and execution of voluntary movements may reflect the multiregional functional interactions in human motor behavior.