Giby Raphael

Spinal-Like Regulator Facilitates Control of a Two-Degree-of-Freedom Wrist

The performance of motor tasks requires the coordinated control and continuous adjustment of myriad individual muscles. The basic commands for the successful performance of a sensorimotor task originate in “higher” centers such as the motor cortex, but the actual muscle activation and resulting torques and motion are considerably shaped by the integrative function of the spinal interneurons. The relative contributions of brain and spinal cord are less clear for reaching movements than for automatic tasks such as locomotion. We have modeled a two-axis, four-muscle wrist joint with realistic musculoskeletal mechanics and proprioceptors and a network of regulatory circuitry based on the classical types of spinal interneurons (propriospinal, monosynaptic Ia-excitatory, reciprocal Ia-inhibitory, Renshaw inhibitory, and Ib-inhibitory pathways) and their supraspinal control (via biasing activity, presynaptic inhibition, and fusimotor gain). The modeled system has a very large number of control inputs, not unlike the real spinal cord that the brain must learn to control to produce desired behaviors. It was surprisingly easy to program this model to emulate actual performance in four very different but well described behaviors: (1) stabilizing responses to force perturbations; (2) rapid movement to position target; (3) isometric force to a target level; and (4) adaptation to viscous curl force fields. Our general hypothesis is that, despite its complexity, such regulatory circuitry substantially simplifies the tasks of learning and producing complex movements.

Computationally efficient models of neuromuscular recruitment and mechanics.

We have improved the stability and computational efficiency of a physiologically realistic, virtual muscle (VM 3.*) model (Cheng et al 2000 J. Neurosci. Methods 101 117-30) by a simpler structure of lumped fiber types and a novel recruitment algorithm. In the new version (VM 4.0), the mathematical equations are reformulated into state-space representation and structured into a CMEX S-function in SIMULINK. A continuous recruitment scheme approximates the discrete recruitment of slow and fast motor units under physiological conditions. This makes it possible to predict force output during smooth recruitment and derecruitment without having to simulate explicitly a large number of independently recruited units. We removed the intermediate state variable, effective length (Leff), which had been introduced to model the delayed length dependency of the activation-frequency relationship, but which had little effect and could introduce instability under physiological conditions of use. Both of these changes greatly reduce the number of state variables with little loss of accuracy compared to the original VM. The performance of VM 4.0 was validated by comparison with VM 3.1.5 for both single-muscle force production and a multi-joint task. The improved VM 4.0 model is more suitable for the analysis of neural control of movements and for design of prosthetic systems to restore lost or impaired motor functions. VM 4.0 is available via the internet and includes options to use the original VM model, which remains useful for detailed simulations of single motor unit behavior.

Modeling the potentiality of spinal-like circuitry for stabilization of a planar arm system.

The design of control systems for limb prostheses seems likely to benefit from an understanding of how sensorimotor integration is achieved in the intact system. Traditional BMIs guess what movement parameters are encoded by brain activity and then decode them to drive prostheses directly. Modeling the known structure and emergent properties of the biological decoder itself is likely to be more effective in bridging from normal brain activity to functionally useful limb movement. In this study, we have extended a model of spinal circuitry (termed SLR for spinal-like regulator; see Raphael, G., Tsianos, G. A., & Loeb G. E. 2010, Spinal-like regulator facilitates control of a two-degree-of-freedom wrist. The Journal of Neuroscience, 30(28), 9431-9444.) to a planar elbow-shoulder system to investigate how the spinal cord contributes to the control of a musculoskeletal system with redundant and multiarticular musculature and interaction (Coriolis) torques, which are common control problems for multisegment linkages throughout the body. The SLR consists of a realistic set of interneuronal pathways (monosynaptic Ia-excitatory, reciprocal Ia-inhibitory, Renshaw inhibitory, Ib-inhibitory, and propriospinal) that are driven by unmodulated step commands with learned amplitudes. We simulated the response of a planar arm to a brief, oblique impulse at the hand and investigated the role of cocontraction in learning to resist it. Training the SLR without cocontraction led to generally poor performance that was significantly worse than training with cocontraction. Further, removing cocontraction from the converged solutions and retraining the system achieved better performance than the SLR responses without cocontraction. Cocontraction appears to reshape the solution space, virtually eliminating the probability of entrapment in poor local minima. The local minima that are entered during learning with cocontraction are favorable starting points for learning to perform the task when cocontraction is abruptly removed. Given the control systems ability to learn effectively and rapidly, we hypothesize that it will generalize more readily to the wider range of tasks that subjects must learn to perform, as opposed to BMIs mapped to outputs of the musculoskeletal system.

Neurotechnology to Accelerate Learning: During Marksmanship Training

This article explores the psychophysiological metrics during expert and novice performances in marksmanship, combat deadly force judgment and decision making (DFJDM), and interactions of teams. Electroencephalography (EEG) and electrocardiography (ECG) are used to characterize the psychophysiological profiles within all categories. Closed-loop biofeedback was administered to accelerate learning during marksmanship training in which the results show a difference in groups that received feedback compared with the control. During known distance marksmanship and DFJDM scenarios, experts show superior ability to control physiology to meet the demands of the task. Expertise in teaming scenarios is characterized by higher levels of cohesiveness than those seen in novices.

Peak Performance Trainer (PPTTM): Interactive Neuro-educational Technology to Increase the Pace and Efficiency of Rifle Marksmanship Training

Marksmanship training involves a combination of classroom instructional learning and field practice involving the instantiation of a well-defined set of sensory, motor and cognitive skills. Current training procedures rely heavily on conventional classroom instruction often with qualitative assessment based on observation (i.e. coaching). We have developed a novel device called the Peak Performance Trainer (PPTTM) which can accelerate the progression from novice-to-expert based on automated inferences from neurophysiological measurements. Our previous work has revealed specific EEG correlates to stages of skill acquisition in simple learning and memory tasks. We have incorporated this knowledge as well as an array of other physiological metrics to develop a field-deployable training technology with continuous physiological monitoring in combination with simultaneous measures of performance, workload, engagement and distraction, accuracy, speed and efficiency. This paper outlines the features of the PPT and the preliminary results of its use in marksmanship training.

Interactive Neuro-Educational Technologies (I-NET): Enhanced training of threat detection for airport luggage screeners

Interactive Neuro-Educational Technologies (I-NET) are designed to increase the pace and efficiency of skill learning by adapting training environments to the skill levels and needs of the individuals. Advanced Brain Monitoring (ABM) explored the feasibility of integrating physiological measures into an interactive adaptive computer-based training system to facilitate mitigations, accelerate skill acquisition and provide quantitative evidence of successful training in tasks relating to airport luggage screening and threat detection. A small pilot study was conducted (N=23) to assess electroencephalographic measures of learning and performance during a threat identification task using X-Ray images designed to be representative of those typically viewed by baggage screeners. Linear regression analysis of trends in EEG Alpha (8–12 Hz) and Theta (3–7 Hz) from stimulus presentation to response for each image revealed effects for Threat Type, Task Order, Stimulus Difficulty and Response Type. Correlation between EEG engagement and workload levels with performance and heart rate and heart rate variability measures in relation to performance were explored. In addition, fixation locked event related potentials (FLERPS) in relation to user responses were investigated by interfacing a commercial eye tracker to the experimental setup.

I-NET ® : Interactive neuro-educational technology to accelerate skill learning

The learning of a novel task currently rely heavily on conventional classroom instruction with qualitative assessment and observation. Introduction of individualized tutorials with integrated neuroscience-based evaluation techniques could significantly accelerate skill acquisition and provide quantitative evidence of successful training. We have created a suite of adaptive and interactive neuro-educational technologies (I-NET) to increase the pace and efficiency of skill learning. It covers four major themes: 1) Integration of brain monitoring into paced instructional tutorials, 2) Identifying psychophysiological characteristics of expertise using a model population, 3) Developing sensor-based feedback to accelerate novice-to-expert transition, 4) Identifying neurocognitive factors that are predictive of skill acquisition to allow early triage and interventions. We selected rifle marksmanship training as the field of application. Rifle marksmanship is a core skill for the Army and Marine Corps and it involves a combination of classroom instructional learning and field practice involving instantiation of a well-defined set of sensory, motor and cognitive skills. The instrumentation that incorporates the I-NET technologies is called the Adaptive Peak Performance Trainer (APPT®). Preliminary analysis of pilot study data for performance data from a novice population that used this device revealed an improved learning trajectory.

Wearable Modular Device for Facilitation of Napping and Optimization of Post-nap Performance

Sleep deprivation-induced deficiencies in performance can be associated with high financial and human costs. Napping is an effective countermeasure, but the effects depend on previously accumulated sleep debt and timing, duration and sleep architecture of the naps. Long-term assessment of sleep architecture of nap/sleep episodes could yield an estimate of the accumulated sleep debt and help optimize the napping schedule. Moreover, sensory stimulation coupled with real-time assessment of sleep states could optimize sleep architecture and duration of each nap. With these goals in mind we designed a wearable device, dubbed Nap Cap, which integrates real-time EEG analysis with audio, visual and thermal stimulation. The prototype was evaluated on seven subjects (fully rested vs. sleep-deprived). While the prototype provided high quality EEG and comfort, sensory stimulation did not significantly influence sleep architecture. Evaluation of more paradigms of sensory stimulation on larger samples is warranted before final conclusions can be made.