Publications

A common-mode interference rejection algorithm based on an impedance matching approach was developed for bipolar cuff electrodes. Two unipolar channels were recorded from the two electrode contacts of a bipolar cuff, and the impedance mismatch was estimated and used to correct one of the two channels. Using the impedance adjustment algorithm, ECG artifacts were significantly suppressed relative to the simple subtraction method by an additional 9.2 dB on average. The algorithm successfully reduced the common-mode interference from ECG artifacts, stimulation artifacts, and evoked EMG interference while retaining neural signals.

The objective was to determine if it is possible to model the response of the carotid blood flow to different chest compression waveforms as a function of time during resuscitation from cardiac arrest. Several approaches were tested to predict the carotid blood flow generated by the next chest compression based on knowledge of the duration of resuscitation, the chest compression rate, and the last compression's carotid blood flow. A single physiological metric, carotid blood flow, combined with information about the duration of resuscitation and the compression rate was sufficient to model and predict carotid blood flow in the next compression. This suggests that closed loop mechanical CPR is a viable medical device target.

Recently developed methods were used to isolate and decode specific neural signals acquired from the surface of the vagus nerve in BALB/c wild type mice to identify those that respond robustly to hypoglycemia. Neural signals in the vagus nerve respond significantly to insulin-induced hypoglycemia and correlate with dropping blood glucose levels. A decoding algorithm was able to reconstruct blood glucose levels with high accuracy (median error 18.6 mg/dl). Hyperglycemia did not induce robust vagus nerve responses, and deletion of TRPV1 nociceptors attenuated the hypoglycemia-dependent vagus nerve signals. These results provide insight to the sensory vagal signaling that encodes hypoglycemic states and suggest a method to measure blood glucose levels by decoding nerve signals.

The bodies have built-in neural reflexes that continuously monitor organ function and maintain physiological homeostasis. While the field of bioelectronic medicine has mainly focused on the stimulation of neural circuits to treat various conditions, recent studies have started to investigate the possibility of leveraging the sensory arm of these reflexes to diagnose disease states. Neural signals emanating from the body's built-in biosensors and propagating through peripheral nerves must be recorded and decoded to identify the presence or levels of relevant biomarkers of disease. This review outlines studies decoding vagus nerve activity as it related to inflammatory, metabolic, and cardiopulmonary biomarkers to enable the development of real-time diagnostic devices and help advance truly closed-loop neuromodulation technologies.

Recent advances reveal that neural reflexes modulate the immune system, but it was previously unknown whether cytokine mediators of immunity mediate specific neural signals. Methods were developed to isolate and decode specific neural signals recorded from the vagus nerve to discriminate between the cytokines IL-1β and TNF. A bipolar cuff electrode recording activity from the surface of the cervical vagus nerve of mice was used. The methodological waveform successfully detects and discriminates between specific cytokine exposures using neural signals, demonstrating that the nervous system maintains physiological homeostasis through reflex pathways that modulate organ function.

Applying transcranial direct current stimulation (tDCS) to the right prefrontal cortex improves monkeys' performance on an associative learning task. While firing rates do not change within the targeted area, tDCS induces large low-frequency oscillations in the underlying tissue. These oscillations alter functional connectivity, both locally and between distant brain areas, and these long-range changes correlate with tDCS's effects on behavior. The data suggest that tDCS may act by altering long-range connectivity between PFC and other brain areas. The research employed a macaque model of tDCS that allows simultaneous examination of the effects of tDCS on brain activity and behavior.

We present a novel 3D self-adaptive nerve electrode for high density nerve signal recording and site-specific stimulation. A new pre-shaped flexible spiral structure has been developed in order to achieve tight contact with small nerves without any additional mechanical locking structure or force. This unique structure enables the nerve electrode to adapt and maintain close contact with the nerve without compressing it or restricting its movement. The spiral nerve electrodes (inner diameter = 310 um) with 8 recording channels (electrode diameter = 50 um) were fabricated and successfully applied to the rat vagus nerve (approximate diameter of 350 um) in order to record compound action potentials.