Dynamic detection and reversal of myocardial ischemia using an artificially intelligent bioelectronic medicine.

Myocardial ischemia is spontaneous, frequently asymptomatic, and contributes to fatal cardiovascular consequences. Importantly, myocardial sensory networks cannot reliably detect and correct myocardial ischemia on their own. Here, we demonstrate an artificially intelligent and responsive bioelectronic medicine, where an artificial neural network (ANN) supplements myocardial sensory networks, enabling reliable detection and correction of myocardial ischemia. ANNs were first trained to decode spontaneous cardiovascular stress and myocardial ischemia with an overall accuracy of ~92%. ANN-controlled vagus nerve stimulation (VNS) significantly mitigated major physiological features of myocardial ischemia, including ST depression and arrhythmias. In contrast, open-loop VNS or ANN-controlled VNS following a caudal vagotomy essentially failed to reverse cardiovascular pathophysiology. Last, variants of ANNs were used to meet clinically relevant needs, including interpretable visualizations and unsupervised detection of emerging cardiovascular stress. Overall, these preclinical results suggest that ANNs can potentially supplement deficient myocardial sensory networks via an artificially intelligent bioelectronic medicine system.

Sources of off-target effects of vagus nerve stimulation using the helical clinical lead in domestic pigs.

Objective: Clinical data suggest that efficacious vagus nerve stimulation (VNS) is limited by side effects such as cough and dyspnea that have stimulation thresholds lower than those for therapeutic outcomes. VNS side effects are putatively caused by activation of nearby muscles within the neck, via direct muscle activation or activation of nerve fibers innervating those muscles. Our goal was to determine the thresholds at which various VNS-evoked effects occur in the domestic pig­an animal model with vagus anatomy similar to human­using the bipolar helical lead deployed clinically. Approach: Intrafascicular electrodes were placed within the vagus nerve to record electroneurographic (ENG) responses, and needle electrodes were placed in the vagal-innervated neck muscles to record electromyographic (EMG) responses. Main results: Contraction of the cricoarytenoid muscle occurred at low amplitudes (~0.3 mA) and resulted from activation of motor nerve fibers in the cervical vagus trunk within the electrode cuff which bifurcate into the recurrent laryngeal branch of the vagus. At higher amplitudes (~1.4 mA), contraction of the cricoarytenoid and cricothyroid muscles was generated by current leakage outside the cuff to activate motor nerve fibers running within the nearby superior laryngeal branch of the vagus. Activation of these muscles generated artifacts in the ENG recordings that may be mistaken for compound action potentials representing slowly conducting Aδ-, B-, and C-fibers. Significance: Our data resolve conflicting reports of the stimulation amplitudes required for C-fiber activation in large animal studies (>10 mA) and human studies (<250 µA). After removing muscle-generated artifacts, ENG signals with post-stimulus latencies consistent with Aδ- and B-fibers occurred in only a small subset of animals, and these signals had similar thresholds to those that caused bradycardia. By identifying specific neuroanatomical pathways that cause off-target effects and characterizing the stimulation dose-response curves for on- and off-target effects, we hope to guide interpretation and optimization of clinical VNS.

Spatial Arrangement Drastically Changes the Neural Representation of Multiple Visual Stimuli That Compete in More Than One Feature Domain.

Natural scenes often contain multiple objects and surfaces. However, how neurons in the visual cortex represent multiple visual stimuli is not well understood. Previous studies have shown that, when multiple stimuli compete in one feature domain, the evoked neuronal response is biased toward the stimulus that has a stronger signal strength. We recorded from two male macaques to investigate how neurons in the middle temporal cortex (MT) represent multiple stimuli that compete in more than one feature domain. Visual stimuli were two random-dot patches moving in different directions. One stimulus had low luminance contrast and moved with high coherence, whereas the other had high contrast and moved with low coherence. We found that how MT neurons represent multiple stimuli depended on the spatial arrangement. When two stimuli were overlapping, MT responses were dominated by the stimulus component that had high contrast. When two stimuli were spatially separated within the receptive fields, the contrast dominance was abolished. We found the same results when using contrast to compete with motion speed. Our neural data and computer simulations using a V1-MT model suggest that the contrast dominance found with overlapping stimuli is due to normalization occurring at an input stage fed to MT, and MT neurons cannot overturn this bias based on their own feature selectivity. The interaction between spatially separated stimuli can largely be explained by normalization within MT. Our results revealed new rules on stimulus competition and highlighted the impact of hierarchical processing on representing multiple stimuli in the visual cortex.SIGNIFICANCE STATEMENT Previous studies have shown that the neural representation of multiple visual stimuli can be accounted for by a divisive normalization model. By using multiple stimuli that compete in more than one feature domain, we found that luminance contrast has a dominant effect in determining competition between multiple stimuli when they are overlapping but not spatially separated. Our results revealed that neuronal responses to multiple stimuli in a given cortical area cannot be simply predicted by the population neural responses elicited in that area by the individual stimulus components. To understand the neural representation of multiple stimuli, rather than considering response normalization only within the area of interest, one must consider the computations including normalization occurring along the hierarchical visual pathway.

An Injectable Neural Stimulation Electrode Made from an In-Body Curing Polymer/Metal Composite.

Implanted neural stimulation and recording devices hold vast potential to treat a variety of neurological conditions, but the invasiveness, complexity, and cost of the implantation procedure greatly reduce access to an otherwise promising therapeutic approach. To address this need, a novel electrode that begins as an uncured, flowable prepolymer that can be injected around a neuroanatomical target to minimize surgical manipulation is developed. Referred to as the Injectrode, the electrode conforms to target structures forming an electrically conductive interface which is orders of magnitude less stiff than conventional neuromodulation electrodes. To validate the Injectrode, detailed electrochemical and microscopy characterization of its material properties is performed and the feasibility of using it to stimulate the nervous system electrically in rats and swine is validated. The silicone-metal-particle composite performs very similarly to pure wire of the same metal (silver) in all measures, including exhibiting a favorable cathodic charge storage capacity (CSCC ) and charge injection limits compared to the clinical LivaNova stimulation electrode and silver wire electrodes. By virtue of its simplicity, the Injectrode has the potential to be less invasive, more robust, and more cost-effective than traditional electrode designs, which could increase the adoption of neuromodulation therapies for existing and new indications.