Implantable bioelectronic systems that stimulate the nervous system are an effective adjunct therapy for Parkinson’s disease, epilepsy, heart arrhythmia/failure, and chronic pain. Clinical studies are underway currently for inflammation, sleep apnea, and mixed urinary incontinence.
Advances in audio technologies are opening new frontiers in human-human and human-machine communications both for normal users and those with communication disorders. Yet, intelligent processing of our auditory surrounds is a nontrivial feat that has to balance the state of the system (e.g., pathophysiology), with the observed sensory signal as well as our goals, expectations, and attentional state (what we hear, what we want to hear, what we expect to hear).
The administration of a photocontrolled ligand in combination with illumination that is patterned in space and time can provide a novel degree of control and regulation of receptor activity. This method would allow precisely focusing the action of the ligand controlling the location and the temporal extension of its effects. When applied in vivo, the use of photoregulation can reduce side effects by targeting receptors located in target tissues, establishing personalized drug schedules to patient needs.
Miniature implanted devices capable of manipulating and recording biological signals promise to improve the way we study biology and the way we diagnose and treat disease; however, to create an effective bioelectronic network we must overcome a myriad of engineering challenges. In this talk, I will describe how we can leverage unique device physics and material properties to overcome some of these challenges. Specifically, I will show how magnetoelectric materials allow us to effectively transmit data and power to mm-sized devices deep inside the body. I will also describe how we can create compact wearable and implantable fluorescent imaging systems by combining photonic technology with computational imaging. Overall, these technologies provide a suite of miniature magnetic and optical neural interfaces that could support next-generation brain-computer interfaces and closed-loop electronic medicine.
