Forelimb force direction and magnitude independently controlled by spinal modules in the macaque.

Modular organization of the spinal motor system is thought to reduce the cognitive complexity of simultaneously controlling the large number of muscles and joints in the human body. Although modular organization has been confirmed in the hindlimb control system of several animal species, it has yet to be established in the forelimb motor system or in primates. Expanding upon experiments originally performed in the frog lumbar spinal cord, we examined whether costimulation of two sites in the macaque monkey cervical spinal cord results in motor activity that is a simple linear sum of the responses evoked by stimulating each site individually. Similar to previous observations in the frog and rodent hindlimb, our analysis revealed that in most cases (77% of all pairs) the directions of the force fields elicited by costimulation were highly similar to those predicted by the simple linear sum of those elicited by stimulating each site individually. A comparable simple summation of electromyography (EMG) output, especially in the proximal muscles, suggested that this linear summation of force field direction was produced by a spinal neural mechanism whereby the forelimb motor output recruited by costimulation was also summed linearly. We further found that the force field magnitudes exhibited supralinear (amplified) summation, which was also observed in the EMG output of distal forelimb muscles, implying a novel feature of primate forelimb control. Overall, our observations support the idea that complex movements in the primate forelimb control system are made possible by flexibly combined spinal motor modules.

Visual Feedback Processing of the Limb Involves Two Distinct Phases.

Muscle responses to mechanical disturbances exhibit two distinct phases: a response starting at ~20 ms that is fairly stereotyped, and a response starting at ~60 ms modulated by many behavioral contexts including goal-redundancy and environmental obstacles. Muscle responses to disturbances of visual feedback of the hand arise within ~90 ms. However, little is known whether these muscle responses are sensitive to behavioral contexts. We had 49 human participants (27 male) execute goal-directed reaches with visual feedback of their hand presented as a cursor. On random trials, the cursor jumped laterally to the reach direction, and thus, required a correction to attain the goal. The first experiment demonstrated that the response amplitude starting at 90 ms scaled with jump magnitude, but only for jumps <2 cm. For larger jumps, the duration of the muscle response scaled with the jump size starting after 120 ms. The second experiment demonstrated that the early response was sensitive to goal redundancy as wider targets evoked a smaller corrective response. The third experiment demonstrated that the early response did not consider the presence of obstacles, as this response routinely drove participants directly to the goal even though this path was blocked by an obstacle. Instead, the appropriate muscle response to navigate around the obstacle started after 120 ms. Our findings highlight that visual feedback of the limb involves two distinct phases: a response starting at 90 ms with limited sensitivity to jump magnitude and sensitive to goal-redundancy, and a response starting at 120 ms with increased sensitivity to jump magnitude and environmental factors.SIGNIFICANCE STATEMENT The motor system can integrate proprioceptive feedback to guide an ongoing action in ~60 ms and is flexible to a broad range of behavioral contexts. In contrast, the present study identified that the motor response to a visual disturbance exhibits two distinct phases: an early response starting at 90 ms with limited scaling with disturbance size and sensitivity to goal-redundancy, and a slower response starting after 120 ms with increased sensitivity to disturbance size and sensitive to environmental obstacles. These data suggest visual feedback of the hand is processed through two distinct feedback processes.

Neural basis for hand muscle synergies in the primate spinal cord.

Grasping is a highly complex movement that requires the coordination of multiple hand joints and muscles. Muscle synergies have been proposed to be the functional building blocks that coordinate such complex motor behaviors, but little is known about how they are implemented in the central nervous system. Here we demonstrate that premotor interneurons (PreM-INs) in the primate cervical spinal cord underlie the spatiotemporal patterns of hand muscle synergies during a voluntary grasping task. Using spike-triggered averaging of hand muscle activity, we found that the muscle fields of PreM-INs were not uniformly distributed across hand muscles but rather distributed as clusters corresponding to muscle synergies. Moreover, although individual PreM-INs have divergent activation patterns, the population activity of PreM-INs reflects the temporal activation of muscle synergies. These findings demonstrate that spinal PreM-INs underlie the muscle coordination required for voluntary hand movements in primates. Given the evolution of neural control of primate hand functions, we suggest that spinal premotor circuits provide the fundamental coordination of multiple joints and muscles upon which more fractionated control is achieved by superimposed, phylogenetically newer, pathways.

[Efficacy of Olaparib Treatment for Platinum-Sensitive Recurrent Ovarian, Fallopian Tube, and Primary Peritoneal Cancers].

We reviewed our clinical experience of olaparib treatment for patients with platinum-sensitive recurrent ovarian, fallopian tube, and peritoneal cancer. Of the 10 cases, the primary sites of cancer were the ovaries, fallopian tubes, and peritoneum in 7, 1 and 2 cases, respectively. The median period of treatment administration was 10 months. The observed Grade 3 or 4 adverse events as per the Common Terminology Criteria for Adverse Events version 4.0 were: anemia, leukopenia and neut r openia in 4, 4 and 3 cases, respectively. Eight cases needed treatment to be interrupted, and 5 cases required a reduction in dose. Three patients were treated for more than 12 months, while the others had to discontinue due to disease progression. However, none of the patients had to discontinue treatment due to adverse events. Therefore, it appears that olaparib can be safely used despite some patients requiring a withdrawal or reduction in treatment.

Correlations Between Primary Motor Cortex Activity with Recent Past and Future Limb Motion During Unperturbed Reaching.

Many studies highlight that human movements are highly successful yet display a surprising amount of variability from trial to trial. There is a consistent pattern of variability throughout movement: initial motor errors are corrected by the end of movement, suggesting the presence of a powerful online control process. Here, we analyze the trial-by-trial variability of goal-directed reaching in nonhuman primates (five male Rhesus monkeys) and demonstrate that they display a similar pattern of variability during reaching, including a strong negative correlation between initial and late hand motion. We then demonstrate that trial-to-trial neural variability of primary motor cortex (M1) is positively correlated with variability of future hand motion (τ = ∼160 ms) during reaching. Furthermore, the variability of M1 activity is also correlated with variability of past hand motion (τ = ∼90 ms), but in the opposite polarity (i.e., negative correlation). Partial correlation analysis demonstrated that M1 activity independently reflects the variability of both past and future hand motions. These findings provide support for the hypothesis that M1 activity is involved in online feedback control of motor actions.SIGNIFICANCE STATEMENT Previous studies highlight that primary motor cortex (M1) rapidly responds to either visual or mechanical disturbances, suggesting its involvement in online feedback control. However, these studies required external disturbances to the motor system and it is not clear whether a similar feedback process addresses internal noise/errors generated by the motor system itself. Here, we introduce a novel analysis that evaluates how variations in the activity of M1 neurons covary with variations in hand motion on a trial-to-trial basis. The analyses demonstrate that M1 activity is correlated with hand motion in both the near future and the recent past, but with opposite polarity. These results suggest that M1 is involved in online feedback motor control to address errors/noise within the motor system.

Nerve-Specific Input Modulation to Spinal Neurons during a Motor Task in the Monkey.

If not properly regulated, the large amount of reafferent sensory signals generated by our own movement could destabilize the CNS. We investigated how input from peripheral nerves to spinal cord is modulated during behavior. We chronically stimulated the deep radial nerve (DR; proprioceptive, wrist extensors), the median nerve (M; mixed, wrist flexors and palmar skin) and the superficial radial nerve (SR; cutaneous, hand dorsum) while four monkeys performed a delayed wrist flexion-extension task. Spinal neurons putatively receiving direct sensory input were defined based on their evoked response latency following nerve stimulation. We compared the influence of behavior on the evoked response (responsiveness to a specific peripheral input) and firing rate of 128 neuron-nerve pairs based on their source nerve. Firing rate increased during movement regardless of source nerve, whereas evoked response modulation was strikingly nerve-dependent. In SR (n = 47) and M (n = 27) neurons (cutaneous or mixed input), the evoked response was suppressed during wrist flexion and extension. In contrast, in DR neurons (n = 54, pure proprioceptive input), the evoked response was facilitated exclusively during movements corresponding to the contraction of DR spindle-bearing muscles (i.e., wrist extension). Furthermore, modulations of firing rate and evoked response were uncorrelated in SR and M neurons, whereas they tended to be positively comodulated in DR neurons. Our results suggest that proprioceptive and cutaneous inputs to the spinal cord are modulated differently during voluntary movements, suggesting a refined gating mechanism of sensory signals according to behavior.SIGNIFICANCE STATEMENT Voluntary movements produce copious sensory signals, which may overwhelm the CNS if not properly regulated. This regulation is called "gating" and occurs at several levels of the CNS. To evaluate the specificity of sensory gating, we investigated how different sources of somatosensory inputs to the spinal cord were modulated while monkeys performed wrist movements. We recorded activity from spinal neurons that putatively received direct connections from peripheral nerves while stimulating their source nerves, and measured the evoked responses. Whereas cutaneous inputs were suppressed regardless of the type of movement, muscular inputs were specifically facilitated during relevant movements. We conclude that, even at the spinal level, sensory gating is a refined and input-specific process.

Modulation of spinal motor output by initial arm postures in anesthetized monkeys.

Proper execution of voluntary movement requires a sensorimotor transformation based on the initial limb state. For example, successfully reaching to a stable target requires the recruitment of different muscle groups depending on limb position at movement initiation. To test whether this transformation could occur at the spinal level, we stimulated the cervical spinal cord of anesthetized monkeys while systematically changing initial posture and examined the modulation of the twitch response induced in the upper limb muscles. In three monkeys, a multichannel microelectrode array was implanted into the C6 segment of the spinal cord and electromyographic electrodes were implanted in 12 limb muscles (five hand, four elbow, and three shoulder muscles). The magnitude and onset latency of the evoked response in each electrode-muscle pair were examined by systematically changing the hand position through nine positions in a horizontal plane with the monkey prone. Among 330 electrode-muscle pairs examined, 61% of pairs exhibited significant modulation of either magnitude or latency of twitch responses across different hand/arm configurations (posture dependency). We found that posture dependency occurred preferentially in the distal rather than proximal muscles and was not affected by the location of the electrode within the stimulated spinal segment. Importantly, this posture dependency was not affected by spinalization at the C2 level. These results suggest that excitability in the cervical spinal cord is affected by initial arm posture through spinal reflex pathways. This posture dependency of spinal motor output could affect voluntary arm movement by adjusting descending motor commands relative to the initial arm posture.

Measurement of membrane tension of free standing lipid bilayers via laser-induced surface deformation spectroscopy.

Non-invasive measurement of the membrane tension of free-standing black lipid membranes (BLMs), with sensitivity on the order of µN m(-1), was achieved using laser-induced surface deformation (LISD) spectroscopy. A BLM was vertically formed via the folding method and aqueous phases with different refractive indices were added on each side in order to induce radiation pressure by a laser beam. The dynamic response of the deformed BLMs was measured under periodic intensity modulation and their tensions could be estimated. The dependence of membrane tension on the cholesterol concentration of BLMs composed of phosphatidylcholine and phosphatidylethanolamine was investigated, with the membrane tension increasing from 1.3 µN m(-1) to 68.1 µN m(-1) when the cholesterol concentration increased from zero to 33%. These tension values are much smaller than some of those previously reported, because this method does not suppress membrane fluctuation unlike other conventional methods. Our LISD system can be a promising tool for the measurement of membrane tension in BLMs.

Spinal premotor interneurons mediate dynamic and static motor commands for precision grip in monkeys.

The extent of spinal interneuron (IN) contribution to dexterous hand movements is unclear. Here, we studied the response patterns and force relationships of spinal premotor INs (PreM-INs) in three awake, behaving monkeys performing a precision grip task. We recorded activity from the cervical spinal cord (C5-T1) simultaneously with electromyographic (EMG) activity from hand and arm muscles during the task. Spike-triggered averaging of EMGs showed that 25 PreM-INs had postspike effects on EMG activity. Most PreM-INs (23/25) displayed movement-related firing rate modulations: 11 had phasic followed by tonic facilitation (p+t+); 4 were pure phasic; 4 were pure tonic; and 4 were deactivated, while their target muscles consistently had p+t+ activity (65/66 muscles). PreM-IN phasic activity started earlier than target muscle activity (49 ± 81.4 ms, mean ± SD), and the peak amplitude was correlated with the peak amplitude of the rate of change of grip force (4/17, p < 0.05), suggesting that they contributed to force initiation. In contrast, PreM-IN tonic activity started at almost the same time as the target muscle activity and the mean firing rate was correlated with the mean grip force during the hold period (4/15, p < 0.05), suggesting that they contributed to force maintenance. These results indicated that the neural pathway mediated by the spinal PreM-INs makes a significant contribution to the control of precision grip in primates.

Neural Network Models for Spinal Implementation of Muscle Synergies.

Muscle synergies have been proposed as functional modules to simplify the complexity of body motor control; however, their neural implementation is still unclear. Converging evidence suggests that output projections of the spinal premotor interneurons (PreM-INs) underlie the formation of muscle synergies, but they exhibit a substantial variation across neurons and exclude standard models assuming a small number of unitary "modules" in the spinal cord. Here we compared neural network models for muscle synergies to seek a biologically plausible model that reconciles previous clinical and electrophysiological findings. We examined three neural network models: one with random connections (non-synergy model), one with a small number of spinal synergies (simple synergy model), and one with a large number of spinal neurons representing muscle synergies with a certain variation (population synergy model). We found that the simple and population synergy models emulate the robustness of muscle synergies against cortical stroke observed in human stroke patients. Furthermore, the size of the spinal variation of the population synergy matched well with the variation in spinal PreM-INs recorded in monkeys. These results suggest that a spinal population with moderate variation is a biologically plausible model for the neural implementation of muscle synergies.

Spinal interneurons facilitate coactivation of hand muscles during a precision grip task in monkeys.

Grasping is a highly complex movement requiring coordination of a number of hand joints and muscles. In contrast to cortical descending systems, the contribution of the subcortical system for coordinating this higher degree of freedom is largely unknown. Here we explore how spinal interneurons (INs) contribute to the coordination of hand muscles by recording their activity from the cervical spinal cord (C5-T1) simultaneously with electromyographic (EMG) activity from hand and arm muscles in three monkeys performing a precision grip task. Spike-triggered averages of the rectified EMGs were compiled for 255 neurons (4821 neuron-muscle pairs). Twenty-six neurons produced 68 significant postspike effects in hand and arm muscles and were identified as premotor interneurons (PreM-INs), which presumably have relatively direct synaptic effects on spinal motoneurons. The majority of the PreM-INs (22/26 neurons) produced postspike effects in finger muscles (intrinsic and extrinsic hand muscles) compared with wrist (9/26 neurons) and elbow muscles (1/26 neurons). The effects in finger muscles were mostly facilitative [postspike facilitations (PSFs), 19/22 neurons], and few had suppressive effects (postspike suppressions, 3/22 neurons). Moreover, PreM-INs produced more divergent PSFs in intrinsic hand muscles (2.5 ± 1.9 muscles/neuron) than in wrist muscles (1.2 ± 0.4 muscles/neurons). We conclude that spinal PreM-INs produce divergent facilitations preferentially in intrinsic hand muscles. These results suggest that spinal interneurons contribute to the control of hand grasping in primates by combining and coordinating multiple finger muscles.

Musculoskeletal Modeling and Inverse Dynamic Analysis of Precision Grip in the Japanese Macaque.

Toward clarifying the biomechanics and neural mechanisms underlying coordinated control of the complex hand musculoskeletal system, we constructed an anatomically based musculoskeletal model of the Japanese macaque (Macaca fuscata) hand, and then estimated the muscle force of all the hand muscles during a precision grip task using inverse dynamic calculation. The musculoskeletal model was constructed from a computed tomography scan of one adult male macaque cadaver. The hand skeleton was modeled as a chain of rigid links connected by revolute joints. The path of each muscle was defined as a series of points connected by line segments. Using this anatomical model and a model-based matching technique, we constructed 3D hand kinematics during the precision grip task from five simultaneous video recordings. Specifically, we collected electromyographic and kinematic data from one adult male Japanese macaque during the precision grip task and two sequences of the precision grip task were analyzed based on inverse dynamics. Our estimated muscular force patterns were generally in agreement with simultaneously measured electromyographic data. Direct measurement of muscle activations for all the muscles involved in the precision grip task is not feasible, but the present inverse dynamic approach allows estimation for all the hand muscles. Although some methodological limitations certainly exist, the constructed model analysis framework has potential in clarifying the biomechanics and neural control of manual dexterity in macaques and humans.

Transient deactivation of dorsal premotor cortex or parietal area 5 impairs feedback control of the limb in macaques.

We can generate goal-directed motor corrections with surprising speed, but their neural basis is poorly understood. Here, we show that temporary cooling of dorsal premotor cortex (PMd) impaired both spatial accuracy and the speed of corrective responses, whereas cooling parietal area 5 (A5) impaired only spatial accuracy. Simulations based on optimal feedback control (OFC) models demonstrated that "deactivation" of the control policy (reduction in feedback gain) and state estimation (reduction in Kalman gain) caused impairments similar to that observed for PMd and A5 cooling, respectively. Furthermore, combined deactivation of both cortical regions led to additive impairments of individual deactivations, whereas reducing the amount of cooling to PMd led to impairments in response speed but not spatial accuracy, both also predicted by OFC models. These results provide causal support that frontoparietal circuits beyond primary somatosensory and motor cortices are involved in generating goal-directed motor corrections.

Distinct sensorimotor feedback loops for dynamic and static control of primate precision grip.

Volitional limb motor control involves dynamic and static muscle actions. It remains elusive how such distinct actions are controlled through separated or shared neural circuits. Here we explored the potential separation for dynamic and static controls in primate hand actions, by investigating the neuronal coherence between local field potentials (LFPs) of the spinal cord and the forelimb electromyographic activity (EMGs), and LFPs of the motor cortex and the EMGs during the performance of a precision grip in macaque monkeys. We observed the emergence of beta-range coherence with EMGs at spinal cord and motor cortex in the separated phases; spinal coherence during the grip phase and cortical coherence during the hold phase. Further, both of the coherences were influenced by bidirectional interactions with reasonable latencies as beta oscillatory cycles. These results indicate that dedicated feedback circuits comprising spinal and cortical structures underlie dynamic and static controls of dexterous hand actions.

Independent representations of ipsilateral and contralateral limbs in primary motor cortex.

Several lines of research demonstrate that primary motor cortex (M1) is principally involved in controlling the contralateral side of the body. However, M1 activity has been correlated with both contralateral and ipsilateral limb movements. Why does ipsilaterally-related activity not cause contralateral motor output? To address this question, we trained monkeys to counter mechanical loads applied to their right and left limbs. We found >50% of M1 neurons had load-related activity for both limbs. Contralateral loads evoked changes in activity ~10ms sooner than ipsilateral loads. We also found corresponding population activities were distinct, with contralateral activity residing in a subspace that was orthogonal to the ipsilateral activity. Thus, neural responses for the contralateral limb can be extracted without interference from the activity for the ipsilateral limb, and vice versa. Our results show that M1 activity unrelated to downstream motor targets can be segregated from activity related to the downstream motor output.

Activity in the posterior parietal cortex mediates visual dominance over kinesthesia.

When both visual and kinesthetic information of a limb are available, vision is usually the dominant source of information used to perceive the spatial location. In this study, we conducted behavioral and functional magnetic resonance imaging (fMRI) experiments to examine the brain mechanisms underlying the visual dominance over kinesthesia in perceiving the position of a hand. We used tendon vibration to induce an illusory percept of flexion movement of an immobile hand, while the participants viewed a live image of either the vibrated or nonvibrated static hand through an on-line video camera. The intensity of illusory movement was significantly attenuated (for both the left and right hands) only when the participants viewed the static image of the vibrated hand. The fMRI study showed that the posterior parietal cortex (PPC) is specifically involved in the attenuation of illusory movement and that the activity of the PPC was associated with the degree of attenuation. This indicates that PPC is involved in the multisensory processing that occurs when vision overrules simultaneously available kinesthetic information for estimating the spatial location of a limb. It is thus suggested that the human parietal cortex may play a critical role in the maintenance of a coherent body image when the brain receives potentially conflicting multisensory information from the body.

Representation of Afferent Signals from Forearm Muscle and Cutaneous Nerves in the Primary Somatosensory Cortex of the Macaque Monkey.

Proprioception is one's overall sense of the relative positions and movements of the various parts of one's body. The primary somatosensory cortex (SI) is involved in generating the proprioception by receiving peripheral sensory inputs from both cutaneous and muscle afferents. In particular, area 3a receives input from muscle afferents and areas 3b and 1 from cutaneous afferents. However, segregation of two sensory inputs to these cortical areas has not been evaluated quantitatively because of methodological difficulties in distinguishing the incoming signals. To overcome this, we applied electrical stimulation separately to two forearm nerves innervating muscle (deep radial nerve) and skin (superficial radial nerve), and examined the spatiotemporal distribution of sensory evoked potentials (SEPs) in SI of anaesthetized macaques. The SEPs arising from the deep radial nerve were observed exclusively at the bottom of central sulcus (CS), which was identified as area 3a using histological reconstruction. In contrast, SEPs evoked by stimulation of the superficial radial nerve were observed in the superficial part of SI, identified as areas 3b and 1. In addition to these earlier, larger potentials, we also found small and slightly delayed SEPs evoked by cutaneous nerve stimulation in area 3a. Coexistence of the SEPs from both deep and superficial radial nerves suggests that area 3a could integrate muscle and cutaneous signals to shape proprioception.

Reduction of cortico-spinal excitability by transcranial magnetic stimulation at predictable timing.

Electrophysiological studies have shown that cortico-spinal excitability increases during the motor preparation period in reaction time (RT) paradigms. However, there is a line of contradictory evidence with transcranial magnetic stimulation (TMS) showing that its excitability is reduced during the preparation period. In these studies, the subjects can predict the TMS timings. Thus we investigated how the predictability of TMS timing affects cortico-spinal excitability. A single-pulse TMS was delivered to the hand section of the left motor cortex while seven right-handed subjects relaxed their hands in a flexed position. We prepared three conditions: (i) in the semi-PREDICTABLE condition, two visual stimuli at 500 ms interval were presented and the TMS was delivered either 0, 125, 250, 375, or 500 ms after the first stimulus; (ii) in the PREDICTABLE condition, the TMS was provided only at 500 ms after the first stimulus; (iii) in the UNPREDICTABLE condition, no visual cue preceded the TMS. We recorded motor evoked potentials (MEPs) from the wrist flexor and extensor muscles. We found a significant reduction of MEP amplitude in the flexor muscles in both the PREDICTABLE and semi-PREDICTABLE conditions, but not in the UNPREDICTABLE condition. These results showed that the predictability of TMS per se, without the preparation of motor outputs, can reduce cortico-spinal excitability.

Neurons in red nucleus and primary motor cortex exhibit similar responses to mechanical perturbations applied to the upper-limb during posture.

Primary motor cortex (M1) and red nucleus (RN) are brain regions involved in limb motor control. Both structures are highly interconnected with the cerebellum and project directly to the spinal cord, although the contribution of RN is smaller than M1. It remains uncertain whether RN and M1 serve similar or distinct roles during posture and movement. Many neurons in M1 respond rapidly to mechanical disturbances of the limb, but it remains unclear whether RN neurons also respond to such limb perturbations. We have compared discharges of single neurons in RN (n = 49) and M1 (n = 109) of one monkey during a postural perturbation task. Neural responses to whole-limb perturbations were examined by transiently applying (300 ms) flexor or extensor torques to the shoulder and/or elbow while the monkeys attempted to maintain a static hand posture. Relative to baseline discharges before perturbation onset, perturbations evoked rapid (<100 ms) changes of neural discharges in many RN (28 of 49, 57%) and M1 (43 of 109, 39%) neurons. In addition to exhibiting a greater proportion of perturbation-related neurons, RN neurons also tended to exhibit higher peak discharge frequencies in response to perturbations than M1 neurons. Importantly, neurons in both structures exhibited similar response latencies and tuning properties (preferred torque directions and tuning widths) in joint-torque space. Proximal arm muscles also displayed similar tuning properties in joint-torque space. These results suggest that RN is more sensitive than M1 to mechanical perturbations applied during postural control but both structures may play a similar role in feedback control of posture.

Feedback control during voluntary motor actions.

Humans possess an impressive ability to generate goal-oriented motor actions to move and interact with the environment. The planning and initiation of these body movements is supported by highly distributed cortical and subcortical circuits. Recent studies, inspired by advanced control theory, highlight similar sophistication when we make online corrections to counter small disturbances of the limb or altered visual feedback. Such goal-directed feedback is likely generated by the same neural circuits associated with motor planning and initiation. These common neural substrates afford a highly responsive system to maintain goal-directed control and rapidly select new motor actions as required to deftly move and interact in a complex world.