Profound dysfunctional reorganization of spinal networks and extensive loss of functional continuity after spinal cord injury (SCI) has not precluded individuals from achieving coordinated voluntary activity and gaining multi-systemic autonomic control. Bladder function is enhanced by approaches, such as spinal cord epidural stimulation (scES) that modulates and strengthens spared circuitry, even in cases of clinically complete SCI. It is unknown whether scES parameters specifically configured for modulating the activity of the lower urinary tract (LUT) could improve both bladder storage and emptying. Functional bladder mapping studies, conducted during filling cystometry, identified specific scES parameters that improved bladder compliance, while maintaining stable blood pressure, and enabled the initiation of voiding in seven individuals with motor complete SCI. Using high-resolution magnetic resonance imaging and finite element modeling, specific neuroanatomical structures responsible for modulating bladder function were identified and plotted as heat maps. Data from this pilot clinical trial indicate that scES neuromodulation that targets bladder compliance reduces incidences of urinary incontinence and provides a means for mitigating autonomic dysreflexia associated with bladder distention. The ability to initiate voiding with targeted scES is a key step towards regaining volitional control of LUT function, advancing the application and adaptability of scES for autonomic function.
Electrical stimulation of the diaphragm muscle or phrenic nerve, or ventilatory pacing, serves as an alternative to mechanical ventilation. Currently available ventilatory pacing systems are open-loop, requiring long set-up sessions and frequent tuning. A neuromorphic closed-loop bioelectronic controller capable of autonomously adapting current amplitude to achieve a desired breath volume profile has been developed. The controller was able to achieve a desired volume profile in intact animals and restore tidal volume to values observed prior to injury in spinal cord hemisected animals. This controller architecture allows for ventilatory pacing that requires minimal technician input during setup and constantly adapts to account for changes such as those induced by muscle fatigue. The adaptive control system could be used as a respiratory rehabilitation tool to strengthen inspiratory muscles and for automated weaning from mechanical ventilation.
Cervical spinal cord injury can disrupt connections between the brain respiratory network and the respiratory muscles which can lead to partial or complete loss of ventilatory control and require ventilatory assistance. Unlike current open-loop technology, a closed-loop diaphragmatic pacing system could overcome the drawbacks of manual titration as well as respond to changing ventilation requirements. We present an original bio-inspired assistive technology for real-time ventilation assistance, implemented in a digital configurable Field Programmable Gate Array (FPGA). The bio-inspired controller, which is a spiking neural network (SNN) inspired by the medullary respiratory network, is as robust as a classic controller while having a flexible, low-power and low-cost hardware design. The system was simulated in MATLAB with FPGA-specific constraints and tested with a computational model of rat breathing; the model reproduced experimentally collected respiratory data in eupneic animals. The open-loop version of the bio-inspired controller was implemented on the FPGA. Electrical test bench characterizations confirmed the system functionality. Open and closed-loop paradigm simulations were simulated to test the FPGA system real-time behavior using the rat computational model. The closed-loop system monitors breathing and changes in respiratory demands to drive diaphragmatic stimulation. The simulated results inform future acute animal experiments and constitute the first step toward the development of a neuromorphic, adaptive, compact, low-power, implantable device. The bio-inspired hardware design optimizes the FPGA resource and time costs while harnessing the computational power of spike-based neuromorphic hardware. Its real-time feature makes it suitable for in vivo applications.
It has been suggested that neuroplasticity-promoting neuromodulation can restore sensory-motor pathways after spinal cord injury (SCI), reactivating the dormant locomotor neuronal circuitry. We introduce a neuro-rehabilitative approach that leverages locomotor training with multi-segmental spinal cord transcutaneous electrical stimulation (scTS). We hypothesized that scTS neuromodulates spinal networks, complementing the neuroplastic effects of locomotor training, result in a functional progression toward recovery of locomotion. We conducted a case-study to test this approach on a 27-year-old male classified as AIS A with chronic SCI. The training regimen included task-driven non-weight-bearing training (1 month) followed by weight-bearing training (2 months). Training was paired with multi-level continuous and phase-dependent scTS targeting function-specific motor pools. Results suggest a convergence of cross-lesional networks, improving kinematics during voluntary non-weight-bearing locomotor-like stepping. After weight-bearing training, coordination during stepping improved, suggesting an important role of afferent feedback in further improvement of voluntary control and reorganization of the sensory-motor brain-spinal connectome.
Functional Electrical Stimulation can be used to restore motor functions loss consecutive to spinal cord injury, such as respiratory deficiency due to paralysis of ventilatory muscles. This paper presents a fully configurable IC-centered stimulator designed to investigate muscle stimulation paradigms. It provides 8 current stimulation channels with high-voltage compliance and real-time operation capabilities, to enable a wide range of FES applications. The stimulator can be used in a standalone mode, or within a closed-loop setup. Primary in vivo results show successful drive of respiratory muscles stimulation using a computer-based dedicated controller.
People with cervical spinal cord injury have partial or complete loss of ventilatory control and require ventilator assist. Open-loop diaphragmatic pacing can be utilized to provide this assist. A closed-loop diaphragmatic pacing system could overcome the drawbacks for manual titration of the stimulation and respond to changing ventilatory requirements. We have developed a versatile custom hardware platform dubbed "Multimed" for biosignal acquisition and parallel real-time computation, data display and storage. We have also developed a new rodent model for diaphragmatic pacing. Using these we illustrate, to our knowledge for the firsttime, the successful ability to perform respiratory flow-phase triggered closed-loop diaphragmatic stimulation with resultant changes in respiratory flow and tidal volume.
Mechanical ventilation is the standard treatment when volitional breathing is insufficient, but drawbacks include muscle atrophy, alveolar damage, and reduced mobility. Respiratory pacing is an alternative approach using electrical stimulation-induced diaphragm contraction to ventilate the lung. Oxygenation and acid–base homeostasis are maintained by matching ventilation to metabolic needs; however, current pacing technology requires manual tuning and does not respond to dynamic user-specific metabolic demand, thus requiring re-tuning of stimulation parameters as physiological changes occur. Here, we describe respiratory pacing using a closed-loop adaptive controller that can self-adjust in real-time to meet metabolic needs. The controller uses an adaptive Pattern Generator Pattern Shaper (PG/PS) architecture that autonomously generates a desired ventilatory pattern in response to dynamic changes in arterial CO2 levels and, based on a learning algorithm, modulates stimulation intensity and respiratory cycle duration to evoke this ventilatory pattern. In vivo experiments in rats with respiratory depression and in those with a paralyzed hemidiaphragm confirmed that the controller can adapt and control ventilation to ameliorate hypoventilation and restore normocapnia regardless of the cause of respiratory dysfunction. This novel closed-loop bioelectronic controller advances the state-of-art in respiratory pacing by demonstrating the ability to automatically personalize stimulation patterns and adapt to achieve adequate ventilation.
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