Background: Cervical vagus nerve stimulation (VNS) is an emerging bioelectronic treatment for brain, metabolic, cardiovascular and immune disorders. Its desired and off-target effects are mediated by different nerve fiber populations and knowledge of their engagement could guide calibration and monitoring of VNS therapies. Objective: Stimulus-evoked compound action potentials (eCAPs) directly provide fiber engagement information but are currently not feasible in humans. A method to estimate fiber engagement through common, noninvasive physiological readouts could be used in place of eCAP measurements. Methods: In anesthetized rats, we recorded eCAPs while registering acute physiological response markers to VNS: cervical electromyography (EMG), changes in heart rate (DHR) and breathing interval (DBI). Quantitative models were established to capture the relationship between A-, Band C-fiber type activation and those markers, and to quantitatively estimate fiber activation from physiological markers and stimulation parameters. Results: In bivariate analyses, we found that EMG correlates with A-fiber, DHR with B-fiber and DBI with C-fiber activation, in agreement with known physiological functions of the vagus. We compiled multivariate models for quantitative estimation of fiber engagement from these markers and stimulation parameters. Finally, we compiled frequency gain models that allow estimation of fiber engagement at a wide range of VNS frequencies. Our models, after calibration in humans, could provide noninvasive estimation of fiber engagement in current and future therapeutic applications of VNS.

Vagus nerve stimulation (VNS) suppresses inflammation and autoimmune diseases in preclinical and clinical studies. The underlying molecular, neurological, and anatomical mechanisms have been well characterized using acute electrophysiological stimulation of the vagus. However, there are several unanswered mechanistic questions about the effects of chronic VNS, which require solving numerous technical challenges for a long-term interface with the vagus in mice. Here, we describe a scalable model for long-term VNS in mice developed and validated in 4 research laboratories. We observed significant heart rate responses for at least 4 weeks in 60-90% of animals. Device implantation did not impair vagus-mediated reflexes. VNS using this implant significantly suppressed TNF levels in endotoxemia. Histological examination of implanted nerves revealed fibrotic encapsulation without axonal pathology. This model may be useful to study the physiology of the vagus and provides a tool to systematically investigate long-term VNS as therapy for chronic diseases modeled in mice.

Anxiety disorders, including generalized anxiety disorder (GAD), social anxiety disorder (SAD), and panic anxiety disorder (PAD), are a group of common psychiatric conditions. They are characterized by excessive worrying, uneasiness, and fear of future events, such that they affect social and occupational functioning. Anxiety disorders can alter behavior and cognition as well, yet little is known about the particular domains they affect. In this study, we tested the cognitive correlates of medication-free patients with GAD, SAD, and PAD, along with matched healthy participants using a probabilistic category-learning task that allows the dissociation between positive and negative feedback learning. We also fitted all participants' data to a Q-learning model and various actor-critic models that examine learning rate parameters from positive and negative feedback to investigate effects of valence vs. action on performance. SAD and GAD patients were more sensitive to negative feedback than either PAD patients or healthy participants. PAD, SAD, and GAD patients did not differ in positive-feedback learning compared to healthy participants. We found that Q-learning models provide the simplest fit of the data in comparison to other models. However, computational analysis revealed that groups did not differ in terms of learning rate or exploration values. These findings argue that (a) not all anxiety spectrum disorders share similar cognitive correlates, but are rather different in ways that do not link them to the hallmark of anxiety (higher sensitivity to negative feedback); and (b) perception of negative consequences is the core feature of GAD and SAD, but not PAD. Further research is needed to examine the similarities and differences between anxiety spectrum disorders in other cognitive domains and potential implementation of behavioral therapy to remediate cognitive deficits.

Interfaces between the nervous and immune systems have been shown essential for the coordination and regulation of immune responses. Non-invasive ultrasound stimulation targeted to the spleen has recently been shown capable of activating one such interface, the splenic cholinergic anti-inflammatory pathway (CAP). Over the past decade, CAP and other neuroimmune pathways have been activated using implanted nerve stimulators and tested to prevent cytokine release and inflammation. However, CAP studies have typically been performed in models of severe, systemic (e.g., endotoxemia) or chronic inflammation (e.g., collagen-induced arthritis or DSS-induced colitis). Herein, we examined the effects of activation of the splenic CAP with ultrasound in a model of local bacterial infection by lung instillation of 105 CFU of Streptococcus pneumoniae. We demonstrate a time-dependent effect of CAP activation on the cytokine response assay during infection progression. CAP activation-induced cytokine suppression is absent at intermediate times post-infection (16 hours following inoculation), but present during the early (4 hours) and later phases (48 hours). These results indicate that cytokine inhibition associated with splenic CAP activation is not observed at all timepoints following bacterial infection and highlights the importance of further studying neuroimmune interfaces within the context of different immune system and inflammatory states.