A memristor-based neuromodulation device for real-time monitoring and adaptive control of in vitro neuronal populations

Abstract

Neurons are specialized cells in information transmission and information processing. Following this, many neurologic disorders are directly linked not to cellular viability/homeostasis issues but rather to specific anomalies in electrical activity dynamics. Acknowledging this fact, therapeutic strategies based on direct modulation of neuronal electrical activity have been producing remarkable results, with successful examples ranging from cochlear implants to deep brain stimulation. Development on these implantable devices are hindered, however, by important challenges: power requirements, size factor, signal transduction, and adaptability/computational capabilities. Memristors, nanoscale electronic components able to emulate natural synapses, provide unique properties to address these constraints and their use in neuroprosthetic devices is being actively explored. Here we demonstrate for the first time the use of memristive devices in a clinically relevant setting where communication between two neuronal populations is conditioned to specific activity patterns in the source population. In our approach, the memristor device performs a simple pattern detection computation and acts as a synapstor capable of reversible short-term plasticity. Using in vitro hippocampal neuronal cultures, we show real-time adaptive control with a high degree of reproducibility using our monitor-compute-actuate paradigm. We envision very similar systems being used for automatic detection and suppression of seizures in epileptic patients.