A novel CNN-based image segmentation pipeline for individualized feline spinal cord stimulation modeling.

Objective. Spinal cord stimulation (SCS) is a well-established treatment for managing certain chronic pain conditions. More recently, it has also garnered attention as a means of modulating neural activity to restore lost autonomic or sensory-motor function. Personalized modeling and treatment planning are critical aspects of safe and effective SCS (Rowald and Amft 2022 Front. Neurorobotics 16 983072, Wagneret al2018 Nature 563 65-71). However, the generation of spine models at the required level of detail and accuracy requires time and labor intensive manual image segmentation by human experts. This study aims to develop a maximally automated segmentation routine capable of producing high-quality anatomical models, even with limited data, to facilitate safe and effective personalized SCS treatment planning.Approach. We developed an automated image segmentation and model generation pipeline based on a novel convolutional neural network (CNN) architecture trained on feline spinal cord magnetic resonance imaging data. The pipeline includes steps for image preprocessing, data augmentation, transfer learning, and cleanup. To assess the relative importance of each step in the pipeline and our choice of CNN architecture, we systematically dropped steps or substituted architectures, quantifying the downstream effects in terms of tissue segmentation quality (Jaccard index and Hausdorff distance) and predicted nerve recruitment (estimated axonal depolarization).Main results. The leave-one-out analysis demonstrated that each pipeline step contributed a small but measurable increment to mean segmentation quality. Surprisingly, minor differences in segmentation accuracy translated to significant deviations (ranging between 4% and 13% for each pipeline step) in predicted nerve recruitment, highlighting the importance of careful workflow design. Additionally, transfer learning techniques enhanced segmentation metric consistency and allowed generalization to a completely different spine region with minimal additional training data.Significance. To our knowledge, this work is the first to assess the downstream impacts of segmentation quality differences on neurostimulation predictions. It highlights the role of each step in the pipeline and paves the way towards fully automated, personalized SCS treatment planning in clinical settings.

An open-source MRI compatible frame for multimodal presurgical mapping in macaque and capuchin monkeys.

BACKGROUND: High-precision neurosurgical targeting in nonhuman primates (NHPs) often requires presurgical anatomical mapping with noninvasive neuroimaging techniques (MRI, CT, PET), allowing for translation of individual anatomical coordinates to surgical stereotaxic apparatus. Given the varied tissue contrasts that these imaging techniques produce, precise alignment of imaging-based coordinates to surgical apparatus can be cumbersome. MRI-compatible stereotaxis with radiopaque fiducial markers offer a straight-forward and reliable solution, but existing commercial options do not fit in conformal head coils that maximize imaging quality. NEW METHOD: We developed a compact MRI-compatible stereotaxis suitable for a variety of NHP species (Macaca mulatta, Macaca fascicularis, and Cebus apella) that allows multimodal alignment through technique-specific fiducial markers. COMPARISON WITH EXISTING METHODS: With the express purpose of compatibility with clinically available MRI, CT, and PET systems, the frame is no larger than a human head, while allowing for imaging NHPs in the supinated position. This design requires no marker implantation, special software, or additional knowledge other than the operation of a common large animal stereotaxis. RESULTS: We demonstrated the applicability of this 3D-printable apparatus across a diverse set of experiments requiring presurgical planning: 1) We demonstrate the accuracy of the fiducial system through a within-MRI cannula insertion and subcortical injection of a viral vector. 2) We also demonstrated accuracy of multimodal (MRI and CT) alignment and coordinate transfer to guide a surgical robot electrode implantation for deep-brain electrophysiology. CONCLUSIONS: The computer-aided design files and engineering drawings are publicly available, with the modular design allowing for low cost and manageable manufacturing.

Supraspinal control of motoneurons after paralysis enabled by spinal cord stimulation.

Spinal cord stimulation (SCS) restores motor control after spinal cord injury (SCI) and stroke. This evidence led to the hypothesis that SCS facilitates residual supraspinal inputs to spinal motoneurons. Instead, here we show that SCS does not facilitate residual supraspinal inputs but directly triggers motoneurons action potentials. However, supraspinal inputs can shape SCS-mediated activity, mimicking volitional control of motoneuron firing. Specifically, by combining simulations, intraspinal electrophysiology in monkeys and single motor unit recordings in humans with motor paralysis, we found that residual supraspinal inputs transform subthreshold SCS-induced excitatory postsynaptic potentials into suprathreshold events. We then demonstrated that only a restricted set of stimulation parameters enables volitional control of motoneuron firing and that lesion severity further restricts the set of effective parameters. Our results explain the facilitation of voluntary motor control during SCS while predicting the limitations of this neurotechnology in cases of severe loss of supraspinal axons.

Neural population dynamics reveals disruption of spinal circuits' responses to proprioceptive input during electrical stimulation of sensory afferents.

While neurostimulation technologies are rapidly approaching clinical applications for sensorimotor disorders, the impact of electrical stimulation on network dynamics is still unknown. Given the high degree of shared processing in neural structures, it is critical to understand if neurostimulation affects functions that are related to, but not targeted by, the intervention. Here, we approach this question by studying the effects of electrical stimulation of cutaneous afferents on unrelated processing of proprioceptive inputs. We recorded intraspinal neural activity in four monkeys while generating proprioceptive inputs from the radial nerve. We then applied continuous stimulation to the radial nerve cutaneous branch and quantified the impact of the stimulation on spinal processing of proprioceptive inputs via neural population dynamics. Proprioceptive pulses consistently produce neural trajectories that are disrupted by concurrent cutaneous stimulation. This disruption propagates to the somatosensory cortex, suggesting that electrical stimulation can perturb natural information processing across the neural axis.

SUPRASPINAL CONTROL OF MOTONEURONS AFTER PARALYSIS ENABLED BY SPINAL CORD STIMULATION.

Spinal cord stimulation (SCS) restores motor control after spinal cord injury (SCI) and stroke. This evidence led to the hypothesis that SCS facilitates residual supraspinal inputs to spinal motoneurons. Instead, here we show that SCS does not facilitate residual supraspinal inputs but directly triggers motoneurons action potentials. However, supraspinal inputs can shape SCS-mediated activity, mimicking volitional control of motoneuron firing. Specifically, by combining simulations, intraspinal electrophysiology in monkeys and single motor unit recordings in humans with motor paralysis, we found that residual supraspinal inputs transform subthreshold SCS-induced excitatory postsynaptic potentials into suprathreshold events. We then demonstrated that only a restricted set of stimulation parameters enables volitional control of motoneuron firing and that lesion severity further restricts the set of effective parameters. Our results explain the facilitation of voluntary motor control during SCS while predicting the limitations of this neurotechnology in cases of severe loss of supraspinal axons.

POTENTIATION OF CORTICO-SPINAL OUTPUT VIA TARGETED ELECTRICAL STIMULATION OF THE MOTOR THALAMUS.

Cerebral white matter lesions prevent cortico-spinal descending inputs from effectively activating spinal motoneurons, leading to loss of motor control. However, in most cases, the damage to cortico-spinal axons is incomplete offering a potential target for new therapies aimed at improving volitional muscle activation. Here we hypothesized that, by engaging direct excitatory connections to cortico-spinal motoneurons, stimulation of the motor thalamus could facilitate activation of surviving cortico-spinal fibers thereby potentiating motor output. To test this hypothesis, we identified optimal thalamic targets and stimulation parameters that enhanced upper-limb motor evoked potentials and grip forces in anesthetized monkeys. This potentiation persisted after white matter lesions. We replicated these results in humans during intra-operative testing. We then designed a stimulation protocol that immediately improved voluntary grip force control in a patient with a chronic white matter lesion. Our results show that electrical stimulation targeting surviving neural pathways can improve motor control after white matter lesions.

A systematic review of computational models for the design of spinal cord stimulation therapies: from neural circuits to patient-specific simulations.

Seventy years ago, Hodgkin and Huxley published the first mathematical model to describe action potential generation, laying the foundation for modern computational neuroscience. Since then, the field has evolved enormously, with studies spanning from basic neuroscience to clinical applications for neuromodulation. Computer models of neuromodulation have evolved in complexity and personalization, advancing clinical practice and novel neurostimulation therapies, such as spinal cord stimulation. Spinal cord stimulation is a therapy widely used to treat chronic pain, with rapidly expanding indications, such as restoring motor function. In general, simulations contributed dramatically to improve lead designs, stimulation configurations, waveform parameters and programming procedures and provided insight into potential mechanisms of action of electrical stimulation. Although the implementation of neural models are relentlessly increasing in number and complexity, it is reasonable to ask whether this observed increase in complexity is necessary for improved accuracy and, ultimately, for clinical efficacy. With this aim, we performed a systematic literature review and a qualitative meta-synthesis of the evolution of computational models, with a focus on complexity, personalization and the use of medical imaging to capture realistic anatomy. Our review showed that increased model complexity and personalization improved both mechanistic and translational studies. More specifically, the use of medical imaging enabled the development of patient-specific models that can help to transform clinical practice in spinal cord stimulation. Finally, we combined our results to provide clear guidelines for standardization and expansion of computational models for spinal cord stimulation.

GABA Increases Sensory Transmission In Monkeys.

Sensory input flow is central to voluntary movements. For almost a century, GABA was believed to modulate this flow by inhibiting sensory axons in the spinal cord to sculpt neural inputs into skilled motor output. Instead, here we show that GABA can also facilitate sensory transmission in monkeys and consequently increase spinal and cortical neural responses to sensory inputs challenging our understanding of generation and perception of movement.

Robot Assisted Neurosurgery for High-Accuracy, Minimally-Invasive Deep Brain Electrophysiology in Monkeys.

Traditional methods to access subcortical structures involve the use of anatomical atlases and high precision stereotaxic frames but suffer from significant variations in implantation accuracy. Here, we leveraged the use of the ROSA One(R) Robot Assistance Platform in non-human primates to study electrophysiological interactions of the corticospinal tract with spinal cord circuits. We were able to target and stimulate the corticospinal tract within the internal capsule with high accuracy and efficiency while recording spinal local field potentials and multi-unit spikes. Our method can be extended to any subcortical structure and allows implantation of multiple deep brain stimulation probes at the same time. Clinical Relevance- Our method will allow us to elucidate further roles of the corticospinal tract and its interactions with other processing centers in intact animals and in motor syndromes in the future.

A Computational Study of Lower Urinary Tract Nerve Recruitment with Epidural Stimulation of the Lumbosacral Spinal Cord.

Bladder dysfunction is a major health risk for people with spinal cord injury. Recently, we have demonstrated that epidural sacral spinal cord stimulation (SCS) can be used to activate lower urinary tract nerves and provide both major components of bladder control: voiding and continence. To effectively control these functions, it is necessary to selectively recruit the afferents of the pudendal nerve that evoke these distinct bladder reflexes. Translation of this innovation to clinical practice requires an understanding of optimal electrode placements and stimulation parameters to guide surgical practice and therapy design. Computational modeling is an important tool to address many of these experimentally intractable stimulation optimization questions. Here, we built a realistic MRI-based finite element computational model of the feline sacral spinal cord which included realistic axon trajectories in the dorsal and ventral roots. We coupled the model with biophysical simulations of membrane dynamics of afferent and efferent axons that project to the lower urinary tract through the pelvic and pudendal nerves. We simulated the electromagnetic fields arising from stimulation through SCS electrodes and calculated the expected recruitment of pelvic and pudendal fibers. We found that SCS can selectively recruit pudendal afferents, in agreement with our experimental data in cats. Our results suggest that SCS is a promising technology to improve bladder function after spinal cord injury, and computational modeling unlocks the potential for highly optimized, selective stimulation. Clinical Relevance - This model provides a method to non-invasively establish electrode placement and stimulation parameters for improving bladder function with epidural spinal cord stimulation.

Calorimetric Measurements of Magnetic-Field-Induced Inhomogeneous Superconductivity Above the Paramagnetic Limit.

We report the first magnetocaloric and calorimetric observations of a magnetic-field-induced phase transition within a superconducting state to the long-sought exotic Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) superconducting state, first predicted over 50 years ago. Through the combination of bulk thermodynamic calorimetric and magnetocaloric measurements in the organic superconductor κ-(BEDT-TTF)_{2}Cu(NCS)_{2} as a function of temperature, magnetic field strength, and magnetic field orientation, we establish for the first time that this field-induced first-order phase transition at the paramagnetic limit H_{p} is a transition to a higher-entropy superconducting phase, uniquely characteristic of the FFLO state. We also establish that this high-field superconducting state displays the bulk paramagnetic ordering of spin domains required of the FFLO state. These results rule out the alternate possibility of spin-density wave ordering in the high-field superconducting phase. The phase diagram determined from our measurements-including the observation of a phase transition into the FFLO phase at H_{p}-is in good agreement with recent NMR results and our own earlier tunnel-diode magnetic penetration depth experiments but is in disagreement with the only previous calorimetric report.