The current state-of-the-art neural recording technology is limited by the ability to remotely and continuously deliver power to the implanted sensors. The implants have to maintain a continuous telemetry link (electromagnetic, optical or ultrasonic) to an external power source which restricts the mobility of the animal and in many instances the setup is too cumbersome for long-term experimentation and for use in small-sized animals. In this project we propose to investigate the feasibility of a self-powered neural activity recorder that senses and stores statistics of in-vivo neural ensemble activity by harvesting energy from ambient thermal- fluctuations and extracellular action-potentials. The project will leverage our previous work in the area of zero- power timers that exploits the physics of quantum-mechanical tunneling of electrons through thin-oxide layers. Because these devices are thermodynamically driven and the recorder based on this principle will be able to operate at power levels below 10-18-10-16 W which is less than the power extracted by a microelectrode from a single action-potential. Our objective will be to interface the recording microelectrodes with the zero-power timer structures such that the device can continuously monitor ensemble activity for durations greater than a year. The key aspect in this project will be to achieve synchronization between the different self-powered devices such that the ensemble activity events could be accurately time-stamped within a certain degree of tolerance. As a pilot study, we propose to benchmark the performance of the sensors for recording ensemble activity in locust olfactory system. We also propose to investigate event reconstruction algorithms that can accurately time-stamp the onset of the neural activity evoked by odor stimulus and validate these results using independent recordings done using conventional approaches. Thus, upon successful completion of this study, we will have demonstrated a method for self-powered in-vivo monitoring of neural activity and the ability to reconstruct and analyze salient events. Such a powerful experimental tool would permit large-scale and long- term monitoring of neural activity in awake and behaving animals with sizes ranging from insects to mammals.
Investigating interactions between populations of neurons in awake and behaving animals requires a large- scale and scalable approach for recording neural activity. Current technology is limited by the ability to remotely deliver power to the implanted sensors. We propose to investigate the feasibility of a self-powered neural activity recorder that operates by harvesting energy from ambient thermal-fluctuations and extracellular action-potentials.
