RESUMO
Spatially selective vagus nerve stimulation (sVNS) offers a promising approach for addressing heart disease with enhanced precision. Despite its therapeutic potential, VNS is limited by off-target effects and the need for time-consuming titration. Our research aimed to determine the spatial organization of cardiac afferent and efferent fibres within the vagus nerve of pigs to achieve targeted neuromodulation. Using trial-and-error sVNS in vivo and ex vivo micro-computed tomography fascicle tracing, we found significant spatial separation between cardiac afferent and cardiac efferent fibres at the mid-cervical level and they were localized on average on opposite sides of the nerve cross-section. This was consistent between both in vivo and ex vivo methods. Specifically, cardiac afferent fibres were located near pulmonary fibres, consistent with findings of cardiopulmonary convergent circuits and, notably, cardiac efferent fascicles were exclusive. These cardiac efferent regions were located in close proximity to the recurrent laryngeal regions. This is consistent with the roughly equitable spread across the nerve of the afferent and efferent fibres. Our study demonstrated that targeted neuromodulation via sVNS could achieve scalable heart rate decreases without eliciting cardiac afferent-related reflexes; this is desirable for reducing sympathetic overactivation associated with heart disease. These findings indicate that understanding the spatial organization of cardiac-related fibres within the vagus nerve can lead to more precise and effective VNS therapy, minimizing off-target effects and potentially mitigating the need for titration. KEY POINTS: Spatially selective vagus nerve stimulation (sVNS) presents a promising approach for addressing chronic heart disease with enhanced precision. Our study reveals significant spatial separation between cardiac afferent and efferent fibres in the vagus nerve, particularly at the mid-cervical level. Utilizing trial-and-error sVNS in vivo and micro-computed tomography fascicle tracing, we demonstrate the potential for targeted neuromodulation, achieving therapeutic effects such as scalable heart rate decrease without stimulating cardiac afferent-related reflexes. This spatial understanding opens avenues for more effective VNS therapy, minimizing off-target effects and potentially eliminating the need for titration, thereby expediting therapeutic outcomes in myocardial infarction and related conditions.
RESUMO
Brain-machine Interfaces (BMI) hold great potential for treating neurological disorders such as epilepsy. Technological progress is allowing for a shift from open-loop, pacemaker-class, intervention towards fully closed-loop neural control systems. Low power programmable processing systems are therefore required which can operate within the thermal window of 2° C for medical implants and maintain long battery life. In this work, we have developed a low power neural engine with an optimized set of algorithms which can operate under a power cycling domain. We have integrated our system with a custom-designed brain implant chip and demonstrated the operational applicability to the closed-loop modulating neural activities in in-vitro and in-vivo brain tissues: the local field potentials can be modulated at required central frequency ranges. Also, both a freely-moving non-human primate (24-hour) and a rodent (1-hour) in-vivo experiments were performed to show system reliable recording performance. The overall system consumes only 2.93 mA during operation with a biological recording frequency 50 Hz sampling rate (the lifespan is approximately 56 hours). A library of algorithms has been implemented in terms of detection, suppression and optical intervention to allow for exploratory applications in different neurological disorders. Thermal experiments demonstrated that operation creates minimal heating as well as battery performance exceeding 24 hours on a freely moving rodent. Therefore, this technology shows great capabilities for both neuroscience in-vitro/in-vivo applications and medical implantable processing units.