High-frequency amplitude-modulated sinusoidal stimulation induces desynchronized yet controllable neural firing.

Regaining sensory feedback is pivotal for people living with limb amputation. Electrical stimulation of sensory fibers in peripheral nerves has been shown to restore focal percepts in the missing limb. However, conventional rectangular current pulses induce sensations often described as unnatural. This is likely due to the synchronous and periodic nature of activity evoked by these pulses. Here we introduce a fast-oscillating amplitude-modulated sinusoidal (FAMS) stimulation waveform that desynchronizes evoked neural activity. We used a computational model to show that sinusoidal waveforms evoke asynchronous and irregular firing and that firing patterns are frequency dependent. We designed the FAMS waveform to leverage both low- and high-frequency effects and found that membrane non-linearities enhance neuron-specific differences when exposed to FAMS. We implemented this waveform in a feline model of peripheral nerve stimulation and demonstrated that FAMS-evoked activity is more asynchronous than activity evoked by rectangular pulses, while being easily controllable with simple stimulation parameters. These results represent an important step towards biomimetic stimulation strategies useful for clinical applications to restore sensory feedback.

Model-based analysis of subthreshold mechanisms of spinal cord stimulation for pain.

Objective.Spinal cord stimulation (SCS) is a common treatment for chronic pain. For decades, SCS maximized overlap between stimulation-induced paresthesias and the patient's painful areas. Recently developed SCS paradigms relieve pain at sub-perceptible amplitudes, yet little is known about the neural response to these new waveforms or their analgesic mechanisms of action. Therefore, in this study, we investigated the neural response to multiple forms of paresthesia-free SCS.Approach.We used computational modeling to investigate the neurophysiological effects and the plausibility of commonly proposed mechanisms of three paresthesia-free SCS paradigms: burst, 1 kHz, and 10 kHz SCS. Specifically, in C- and Aß-fibers, we investigated the effects of different SCS waveforms on spike timing and activation thresholds, as well as how stochastic ion channel gating affects the response of dorsal column axons. Finally, we characterized membrane polarization of superficial dorsal horn neurons.Main results.We found that none of the SCS waveforms activate nor modulate spike timing in C-fibers. Spike timing was modulated in Aß-fibers only at suprathreshold amplitudes. Ion channel stochasticity had little effect on Aß-fiber activation thresholds but produced heterogeneous spike timings at suprathreshold amplitudes. Finally, local cells were preferentially polarized in their axon terminals, and the magnitude of this polarization was dependent on cellular morphology and position relative to the stimulation electrodes.Significance.Overall, the mechanisms of action of subparesthetic SCS remain unclear. Our results suggest that no SCS waveforms directly activate C-fibers, and modulation of spike timing is unlikely at subthreshold amplitudes. We conclude that potential subthreshold neuromodulatory effects of SCS on local cells are likely to be presynaptic in nature, as axons are preferentially depolarized during SCS.

An optimization framework for targeted spinal cord stimulation.

Objective. Spinal cord stimulation (SCS) is a common neurostimulation therapy to manage chronic pain. Technological advances have produced new neurostimulation systems with expanded capabilities in an attempt to improve the clinical outcomes associated with SCS. However, these expanded capabilities have dramatically increased the number of possible stimulation parameters and made it intractable to efficiently explore this large parameter space within the context of standard clinical programming procedures. Therefore, in this study, we developed an optimization approach to define the optimal current amplitudes or fractions across individual contacts in an SCS electrode array(s).Approach. We developed an analytic method using the Lagrange multiplier method along with smoothing approximations. To test our optimization framework, we used a hybrid computational modeling approach that consisted of a finite element method model and multi-compartment models of axons and cells within the spinal cord. Moreover, we extended our approach to multi-objective optimization to explore the trade-off between activating regions of interest (ROIs) and regions of avoidance (ROAs).Main results. For simple ROIs, our framework suggested optimized configurations that resembled simple bipolar configurations. However, when we considered multi-objective optimization, our framework suggested nontrivial stimulation configurations that could be selected from Pareto fronts to target multiple ROIs or avoid ROAs.Significance. We developed an optimization framework for targeted SCS. Our method is analytic, which allows for the fast calculation of optimal solutions. For the first time, we provided a multi-objective approach for selective SCS. Through this approach, we were able to show that novel configurations can provide neural recruitment profiles that are not possible with conventional stimulation configurations (e.g. bipolar stimulation). Most importantly, once integrated with computational models that account for sources of interpatient variability (e.g. anatomy, electrode placement), our optimization framework can be utilized to provide stimulation settings tailored to the needs of individual patients.

Structural and functional integration of human forebrain organoids with the injured adult rat visual system.

Brain organoids created from human pluripotent stem cells represent a promising approach for brain repair. They acquire many structural features of the brain and raise the possibility of patient-matched repair. Whether these entities can integrate with host brain networks in the context of the injured adult mammalian brain is not well established. Here, we provide structural and functional evidence that human brain organoids successfully integrate with the adult rat visual system after transplantation into large injury cavities in the visual cortex. Virus-based trans-synaptic tracing reveals a polysynaptic pathway between organoid neurons and the host retina and reciprocal connectivity between the graft and other regions of the visual system. Visual stimulation of host animals elicits responses in organoid neurons, including orientation selectivity. These results demonstrate the ability of human brain organoids to adopt sophisticated function after insertion into large injury cavities, suggesting a translational strategy to restore function after cortical damage.

Molecular Determinants of Mechanical Itch Sensitization in Chronic Itch.

Chronic itch is associated with sensitization of the somatosensory nervous system. Recent studies have identified the neural circuits transmitting acute itch; however, the mechanisms by which itch transforms into a pathological state remain largely unknown. We have previously shown that Aß low-threshold mechanoreceptors, together with spinal urocortin 3-positive (Ucn3+) excitatory interneurons and neuropeptide Y-positive (NPY+) inhibitory interneurons, form a microcircuit that transmits and gates acute mechanical itch. Here, using whole-cell patch-clamp recordings, we observed increased excitability in spinal Ucn3+ neurons under chronic itch conditions. In contrast to Ucn3+ neurons, the excitability of spinal NPY+ neurons was largely reduced under chronic itch conditions. To explore the molecular mechanisms underlying sensitization of this microcircuit, we examined the mRNA expression levels of voltage-gated ion channels in recorded spinal Ucn3+ and NPY+ neurons by single-cell quantitative real-time PCR (qRT-PCR). We found that the expression levels of Nav1.6 and Cav2.3 channels were increased in spinal Ucn3+ neurons in chronic itch mice, while the expression level of SK3 channels was decreased. By contrast, the expression levels of Nav1.6 and BK channels were decreased in spinal NPY+ neurons in chronic itch mice. To determine the contribution of different ion channels in chronic itch sensitization, we then used a Markov Chain Monte Carlo method to parameterize a large number of biophysically distinct multicompartment models of Ucn3+ and NPY+ neurons. These models included explicit representations of the ion channels that we found to be up- or down-regulated under chronic itch conditions. Our models demonstrated that changes in Nav1.6 conductance are predominantly responsible for the changes in excitability of both Ucn3+ and NPY+ neurons during chronic itch pathogenesis. Furthermore, when simulating microcircuits of our Ucn3+ and NPY+ models, we found that reduced Nav1.6 conductance in NPY+ models played a major role in opening the itch gate under chronic itch conditions. However, changing SK, BK, or R-type calcium channel conductance had negligible effects on the sensitization of this circuit. Therefore, our results suggest that Nav1.6 channels may play an essential role in mechanical itch sensitization. The findings presented here may open a new avenue for developing pharmaceutical strategies to treat chronic itch.

Real-Time Optimization of Retinal Ganglion Cell Spatial Activity in Response to Epiretinal Stimulation.

Retinal prostheses aim to improve visual perception in patients blinded by photoreceptor degeneration. However, shape and letter perception with these devices is currently limited due to low spatial resolution. Previous research has shown the retinal ganglion cell (RGC) spatial activity and phosphene shapes can vary due to the complexity of retina structure and electrode-retina interactions. Visual percepts elicited by single electrodes differ in size and shapes for different electrodes within the same subject, resulting in interference between phosphenes and an unclear image. Prior work has shown that better patient outcomes correlate with spatially separate phosphenes. In this study we use calcium imaging, in vitro retina, neural networks (NN), and an optimization algorithm to demonstrate a method to iteratively search for optimal stimulation parameters that create focal RGC activation. Our findings indicate that we can converge to stimulation parameters that result in focal RGC activation by sampling less than 1/3 of the parameter space. A similar process implemented clinically can reduce time required for optimizing implant operation and enable personalized fitting of retinal prostheses.

Quantitative Sensory Testing of Spinal Cord and Dorsal Root Ganglion Stimulation in Chronic Pain Patients.

BACKGROUND/OBJECTIVES: The physiological mechanisms underlying the pain-modulatory effects of clinical neurostimulation therapies, such as spinal cord stimulation (SCS) and dorsal root ganglion stimulation (DRGS), are only partially understood. In this pilot prospective study, we used patient-reported outcomes (PROs) and quantitative sensory testing (QST) to investigate the physiological effects and possible mechanisms of action of SCS and DRGS therapies. MATERIALS AND METHODS: We tested 16 chronic pain patients selected for SCS and DRGS therapy, before and after treatment. PROs included pain intensity, pain-related symptoms (e.g., pain interference, pain coping, sleep interference) and disability, and general health status. QST included assessments of vibration detection theshold (VDT), pressure pain threshold (PPT) and tolerance (PPToL), temporal summation (TS), and conditioned pain modulation (CPM), at the most painful site. RESULTS: Following treatment, all participants reported significant improvements in PROs (e.g., reduced pain intensity [p < 0.001], pain-related functional impairment [or pain interference] and disability [p = 0.001 for both]; better pain coping [p = 0.03], sleep [p = 0.002]), and overall health [p = 0.005]). QST showed a significant treatment-induced increase in PPT (p = 0.002) and PPToL (p = 0.011), and a significant reduction in TS (p = 0.033) at the most painful site, but showed no effects on VDT and CPM. We detected possible associations between a few QST measures and a few PROs. Notably, higher TS was associated with increased pain interference scores at pre-treatment (r = 0.772, p = 0.009), and a reduction in TS was associated with the reduction in pain interference (r = 0.669, p = 0.034) and pain disability (r = 0.690, p = 0.027) scores with treatment. CONCLUSIONS: Our preliminary findings suggest significant clinical and therapeutic benefits associated with SCS and DRGS therapies, and the possible ability of these therapies to modulate pain processing within the central nervous system. Replication of our pilot findings in future, larger studies is necessary to characterize the physiological mechanisms of SCS and DRGS therapies.

Biophysics of Temporal Interference Stimulation.

Temporal interference (TI) is a non-invasive neurostimulation technique that utilizes high-frequency external electric fields to stimulate deep neuronal structures without affecting superficial, off-target structures. TI represents a potential breakthrough for treating conditions, such as Parkinson's disease and chronic pain. However, early clinical work on TI stimulation was met with mixed outcomes challenging its fundamental mechanisms and applications. Here, we apply established physics to study the mechanisms of TI with the goal of optimizing it for clinical use. We argue that TI stimulation cannot work via passive membrane filtering, as previously hypothesized. Instead, TI stimulation requires an ion-channel mediated signal rectification process. Unfortunately, this mechanism is also responsible for high-frequency conduction block in off-target tissues, thus challenging clinical applications of TI. In consequence, we propose a set of experimental controls that should be performed in future experiments to refine our understanding and practice of TI stimulation. A record of this paper's transparent peer review process is included in the Supplemental Information.

A mathematical and computational model of the calcium dynamics in Caenorhabditis elegans ASH sensory neuron.

We propose a mathematical and computational model that captures the stimulus-generated Ca2+ transients in the C. elegans ASH sensory neuron. The rationale is to develop a tool that will enable a cross-talk between modeling and experiments, using modeling results to guide targeted experimental efforts. The model is built based on biophysical events and molecular cascades known to unfold as part of neurons' Ca2+ homeostasis mechanism, as well as on Ca2+ signaling events. The state of ion channels is described by their probability of being activated or inactivated, and the remaining molecular states are based on biochemically defined kinetic equations or known biochemical motifs. We estimate the parameters of the model using experimental data of hyperosmotic stimulus-evoked Ca2+ transients detected with a FRET sensor in young and aged worms, unstressed and exposed to oxidative stress. We use a hybrid optimization method composed of a multi-objective genetic algorithm and nonlinear least-squares to estimate the model parameters. We first obtain the model parameters for young unstressed worms. Next, we use these values of the parameters as a starting point to identify the model parameters for stressed and aged worms. We show that the model, in combination with experimental data, corroborates literature results. In addition, we demonstrate that our model can be used to predict ASH response to complex combinations of stimulation pulses. The proposed model includes for the first time the ASH Ca2+ dynamics observed during both "on" and "off" responses. This mathematical and computational effort is the first to propose a dynamic model of the Ca2+ transients' mechanism in C. elegans neurons, based on biochemical pathways of the cell's Ca2+ homeostasis machinery. We believe that the proposed model can be used to further elucidate the Ca2+ dynamics of a key C. elegans neuron, to guide future experiments on C. elegans neurobiology, and to pave the way for the development of more mathematical models for neuronal Ca2+ dynamics.

Synaptic Impairment and Robustness of Excitatory Neuronal Networks with Different Topologies.

Synaptic deficiencies are a known hallmark of neurodegenerative diseases, but the diagnosis of impaired synapses on the cellular level is not an easy task. Nonetheless, changes in the system-level dynamics of neuronal networks with damaged synapses can be detected using techniques that do not require high spatial resolution. This paper investigates how the structure/topology of neuronal networks influences their dynamics when they suffer from synaptic loss. We study different neuronal network structures/topologies by specifying their degree distributions. The modes of the degree distribution can be used to construct networks that consist of rich clubs and resemble small world networks, as well. We define two dynamical metrics to compare the activity of networks with different structures: persistent activity (namely, the self-sustained activity of the network upon removal of the initial stimulus) and quality of activity (namely, percentage of neurons that participate in the persistent activity of the network). Our results show that synaptic loss affects the persistent activity of networks with bimodal degree distributions less than it affects random networks. The robustness of neuronal networks enhances when the distance between the modes of the degree distribution increases, suggesting that the rich clubs of networks with distinct modes keep the whole network active. In addition, a tradeoff is observed between the quality of activity and the persistent activity. For a range of distributions, both of these dynamical metrics are considerably high for networks with bimodal degree distribution compared to random networks. We also propose three different scenarios of synaptic impairment, which may correspond to different pathological or biological conditions. Regardless of the network structure/topology, results demonstrate that synaptic loss has more severe effects on the activity of the network when impairments are correlated with the activity of the neurons.