Selective stimulation of the ferret abdominal vagus nerve with multi-contact nerve cuff electrodes.

Dysfunction and diseases of the gastrointestinal (GI) tract are a major driver of medical care. The vagus nerve innervates and controls multiple organs of the GI tract and vagus nerve stimulation (VNS) could provide a means for affecting GI function and treating disease. However, the vagus nerve also innervates many other organs throughout the body, and off-target effects of VNS could cause major side effects such as changes in blood pressure. In this study, we aimed to achieve selective stimulation of populations of vagal afferents using a multi-contact cuff electrode wrapped around the abdominal trunks of the vagus nerve. Four-contact nerve cuff electrodes were implanted around the dorsal (N = 3) or ventral (N = 3) abdominal vagus nerve in six ferrets, and the response to stimulation was measured via a 32-channel microelectrode array (MEA) inserted into the left or right nodose ganglion. Selectivity was characterized by the ability to evoke responses in MEA channels through one bipolar pair of cuff contacts but not through the other bipolar pair. We demonstrated that it was possible to selectively activate subpopulations of vagal neurons using abdominal VNS. Additionally, we quantified the conduction velocity of evoked responses to determine what types of nerve fibers (i.e., Aδ vs. C) responded to stimulation. We also quantified the spatial organization of evoked responses in the nodose MEA to determine if there is somatotopic organization of the neurons in that ganglion. Finally, we demonstrated in a separate set of three ferrets that stimulation of the abdominal vagus via a four-contact cuff could selectively alter gastric myoelectric activity, suggesting that abdominal VNS can potentially be used to control GI function.

Kranion, an open-source environment for planning transcranial focused ultrasound surgery: technical note.

Transcranial focused ultrasound (FUS) ablation is an emerging incision-less treatment for neurological disorders. The factors affecting FUS treatment efficiency are not well understood. Kranion is open-source software that allows the user to simulate the planning stages of FUS treatment and to "replay" previous treatments for off-line analysis. This study aimed to investigate the relationship between skull parameters and treatment efficiency and to create a metric to estimate temperature rise during FUS. CT images from 28 patients were analyzed to validate the use of Kranion. For stereotactic targets within each patient, individual transducer element incident angles, skull density ratio, and skull thickness measurements were recorded. A penetration metric (the "beam index") was calculated by combining the energy loss from incident angles and the skull thickness. Kranion accurately estimated the patient's skull and treatment parameters. The authors observed significant changes in incident angles with different targets in the brain. Using the beam index as a predictor of temperature rise in a linear-mixed-effects model, they were able to predict the average temperature rise at the focal point during ablation with < 21% error (55°C ± 3.8°C) in 75% of sonications, and with < 44% (55°C ± 7.9°C) in 97% of sonications. This research suggests that the beam index can improve the prediction of temperature rise during FUS. Additional work is required to study the relationship between temperature rise and lesion shape and clinical outcomes.