Mounting evidence suggests that both α and γ motoneurons are active during movement and posture, but how does the central motor system coordinate the α-γ controls in these tasks remains sketchy due to lack of in vivo data. Here a computational model of α-γ control of muscles and spindles was used to investigate α-γ integration and coordination for movement and posture. The model comprised physiologically realistic spinal circuitry, muscles, proprioceptors, and skeletal biomechanics. In the model, we divided the cortical descending commands into static and dynamic sets, where static commands (α_s and γ_s) were for posture maintenance and dynamic commands (α_d and γ_d) were responsible for movement. We matched our model to human reaching movement data by straightforward adjustments of descending commands derived from either minimal-jerk trajectories or human EMGs. The matched movement showed smooth reach-to-hold trajectories qualitatively close to human behaviors, and the reproduced EMGs showed the classic tri-phasic patterns. In particular, the function of γ_d was to gate the α_d command at the propriospinal neurons (PN) such that antagonistic muscles can accelerate or decelerate the limb with proper timing. Independent control of joint position and stiffness could be achieved by adjusting static commands. Deefferentation in the model indicated that accurate static commands of α_s and γ_s are essential to achieve stable terminal posture precisely, and that the γ_d command is as important as the α_d command in controlling antagonistic muscles for desired movements. Deafferentation in the model showed that losing proprioceptive afferents mainly affected the terminal position of movement, similar to the abnormal behaviors observed in human and animals. Our results illustrated that tuning the simple forms of α-γ commands can reproduce a range of human reach-to-hold movements, and it is necessary to coordinate the set of α-γ descending commands for accurate and stable control of movement and posture.

The past decades have witnessed remarkable progress in neural technologies such as functional electrical stimulation (FES) and their applications in neurorehabilitation and neuromodulation. These advances are powered by new neuroscientific understandings of the organization and compositionality of neuromuscular control illuminating how muscle groups may be activated together as discrete units known as muscle synergies. These parallel developments have promoted novel approaches to clinical rehabilitation for neurological disorders that are insurmountable to current treatments. One such breakthrough is the evolution of FES as a therapeutic tool in poststroke rehabilitation with an interventional strategy particularly inspired by the concept that muscles in humans may be purposefully coordinated through neuromotor modules represented as muscle synergies. This paper will review recent advances in multichannel FES technology, its potential applications in poststroke rehabilitation, new findings that support the neurological basis of the muscle synergies for generating natural motor tasks, and the application of the muscle-synergy concept in poststroke assessment and rehabilitation of motor impairment. Finally, we will recommend future directions of development in relation to assistive FES and synergy-driven adaptive training for poststroke rehabilitation.

This study assessed the feasibility to restore finger-specific sensory feedback in transradial amputees with electrical stimulation of evoked tactile sensation (ETS). Here we investigated primary somatosensory cortical (SI) responses of ETS using Magnetoencephalography. SI activations revealed a causal correlation with peripheral stimulation of projected finger regions on the stump skin. Peak latency was accountable to neural transmission from periphery to SI. Peak intensity of SI response was proportional to the strength of peripheral stimulation, manifesting a direct neural pathway from skin receptors to SI neurons. Active regions in SI at the amputated side were consistent to the finger/hand map of homunculus, forming a mirror imaging to that of the contralateral hand. With sensory feedback, amputees can recognize a pressure at prosthetic fingers as that at the homonymous lost fingers. Results confirmed that the direct neural pathway from periphery to SI allows communication of finger-specific sensory information to these amputees.

Integrating a prosthetic hand to amputees with seamless neural compatibility presents a grand challenge to neuroscientists and neural engineers for more than half century. Mimicking anatomical structure or appearance of human hand does not lead to improved neural connectivity to the sensorimotor system of amputees. The functions of modern prosthetic hands do not match the dexterity of human hand due primarily to lack of sensory awareness and compliant actuation. Lately, progress in restoring sensory feedback has marked a significant step forward in improving neural continuity of sensory information from prosthetic hands to amputees. However, little effort has been made to replicate the compliant property of biological muscle when actuating prosthetic hands. Furthermore, a full-fledged biorealistic approach to designing prosthetic hands has not been contemplated in neuroprosthetic research. In this perspective article, we advance a novel view that a prosthetic hand can be integrated harmoniously with amputees only if neural compatibility to the sensorimotor system is achieved. Our ongoing research supports that the next-generation prosthetic hand must incorporate biologically realistic actuation, sensing, and reflex functions in order to fully attain neural compatibility.

Recent study suggests that tremor signals are transmitted by way of multi-synaptic corticospinal pathway. Neurophysiological studies have also demonstrated that cutaneous afferents exert potent inhibition to descending motor commands by way of spinal interneurons. We hypothesize in this study that cutaneous afferents could also affect the transmission of tremor signals, thus, inhibit tremor in patients with PD. We tested this hypothesis by activating cutaneous afferents in the dorsal hand skin innervated by superficial radial nerve using transcutaneous electrical nerve stimulation (TENS). Eight patients with PD having tremor dominant symptom were recruited to participate in this study using a consistent experimental protocol for tremor inhibition. Resting tremor and electromyogram (EMG) of muscles in the upper extremity of these subjects with PD were recorded, while surface stimulation was applied to the dorsal skin of the hand. Fifteen seconds of data were recorded for 5 s prior to, during and post stimulation. Power spectrum densities (PSDs) of tremor and EMG signals were computed for each data segment. The peak values of PSDs in three data segments were compared to detect evidence of tremor inhibition. At stimulation intensity from 1.5 to 1.75 times of radiating sensation threshold, apparent suppressions of tremor at wrist, forearm and upper arm and in the EMGs were observed immediately at the onset of stimulation. After termination of stimulation, tremor and rhythmic EMG bursts reemerged gradually. Statistical analysis of peak spectral amplitudes showed a significant difference in joint tremors and EMGs during and prior to stimulation in all 8 subjects with PD. The average percentage of suppression was 61.56% in tremor across all joints of all subjects, and 47.97% in EMG of all muscles. The suppression appeared to occur mainly in distal joints and muscles. There was a slight, but inconsistent effect on tremor frequency in the 8 patients with PD tested. Our results provide direct evidence that tremor in the upper extremity of patients with PD can be inhibited to a large extent with evoked cutaneous reflexes via surface stimulation of the dorsal hand skin area innervated by the superficial radial nerve.

Prosthetic and therapeutic devices have been developed to ameliorate the quality of daily living for people with amputation or neurological disorders. However, many of them fall short of functional benefits, and therefore, are frequently rejected by users due to awkward control, or no awareness of interaction during tasks. Traditional wisdom in the design of prosthetic and therapeutic devices may have emphasized the need to provide users with apparatus that replace or assist motor ability. Rather, the notion to achieve neural compatibility with the existing sensorimotor system has not been well recognized. We argue that providing biomimetic control and sensing capacity to prosthetic and therapeutic devices can enhance their neural compatibility, and therefore, can yield greater functionality in performing activities of daily lives, or in rehabilitation training. In this paper, the authors will present a range of neural technologies that may allow implementation of biomimetic sensorimotor control, including natural sensory feedback, neuromuscular like compliant control, natural module of synergy-based control, as well as advanced neural signal processing techniques. Based on the evidence in our research and in literature, we propose that achieving NEURAL COMPATIBILITY with the existing human sensorimotor system should be the ultimate goal of prosthetic and therapeutic devices.