Information, energy, and entropy: Design principles for adaptive, therapeutic modulation of neural circuits

This paper discusses the challenges and opportunities designing technology for deep brain stimulation (DBS). DBS is currently approved for the treatment of movement disorders such as Parkinson Disease, essential tremor and dystonia, and a number of studies are underway to determine its clinical efficacy for the treatment of epilepsy, treatment resistant depression, and obsessive compulsive disorder (OCD). Designing a DBS system is a complex system engineering problem, drawing on such diverse fields as applied physics, circuit design, algorithms and biology. But fundamental to device design is the neurophysiology of the dasiabrain circuitspsila affected by the disease, and how they can be modulated for therapeutic affect. Recent activities are drawing on information theory to help better understand the operation of brain circuits. From that understanding, we hope to clarify the mechanisms by which existing DBS therapy works. In addition, considerations from information theory, and the relationships between concepts like entropy, energy and information flow, can help guide the design of more advanced therapy systems. We briefly review these concepts as applied to brain circuits and disease. We then describe our recent work in designing research tools that allow for exploration of adaptive circuit modulation based on measured electrical biomarkers, which are believed to represent compromised information processing in the brain. Future opportunities are discussed to highlight that electrical engineering, from MEMS to circuits to signal processing, is crucial to enabling the next generation of neurological therapies.