Listening to Brain Microcircuits for Interfacing With External World—Progress in Wireless Implantable Microelectronic Neuroengineering Devices

Abstract

Acquiring neural signals at high spatial and temporal resolution directly from brain microcircuits and decoding their activity to interpret commands and/or prior planning activity, such as motion of an arm or a leg, is a prime goal of modern neurotechnology. Its practical aims include assistive devices for subjects whose normal neural information pathways are not functioning due to physical damage or disease. On the fundamental side, researchers are striving to decipher the code of multiple neural microcircuits which collectively make up nature’s amazing computing machine, the brain. By implanting biocompatible neural sensor probes directly into the brain, in the form of microelectrode arrays, it is now possible to extract information from interacting populations of neural cells with spatial and temporal resolution at the single cell level. With parallel advances in application of statistical and mathematical techniques tools for deciphering the neural code, extracted populations or correlated neurons, significant understanding has been achieved of those brain commands that control, e.g., the motion of an arm in a primate (monkey or a human subject). These developments are accelerating the work on neural prosthetics where brain derived signals may be employed to bypass, e.g., an injured spinal cord. One key element in achieving the goals for practical and versatile neural prostheses is the development of fully implantable wireless microelectronic “brain-interfaces” within the body, a point of special emphasis of this paper.

Brain-Machine Interfaces: From Macro- to Microcircuits

“…The normal decision making signal follows a temporal pattern characterized by a rising to threshold when the preferred option is selected or a temporal decay for non-preferred option. Signals are recorded, decoded and interpreted so that the optimal selection is made (Nurmikko et al 2010). When the decision signal is not optimal, predicting that a failed choice will occur soon, an error signal instructs the microstimulator to apply a microcurrent in the appropriate brain region (for example, prefrontal cortical layer 2/3 if the accumulation of sensory evidence is weak, layer 5 if the selection signal is weak, or caudate nucleus if the decision bias is weak) and the decision signal will be corrected in real time.…”

Integrated neural interfaces

“…Neural interfaces that connect electronic systems with biological neurons have emerged as a major topic of research in the last decade [1], impacting fields ranging from electrical and biomedical engineering to neuroscience and medical practice. Our capability to record from and stimulate individual neurons has progressed from single-cell experiments to interfacing with a few hundred neurons simultaneously, largely driven by microfabrication of neural recording and stimulation devices comprising arrays of sensors and/or actuators arranged in separate channels [2].…”

Tunnel FET RF Rectifier Design for Energy Harvesting Applications

“…applications, such as implantable medical devices [1], [2] and wearable bio-activity monitoring platforms [3]- [5], etc. In these applications, the battery replacement with highly efficient radio-frequency (RF) power harvesters offers many advantages, which reduces the weight and cost of the system, and also eliminates the charging inconvenience and the risk of replacing the batteries [1]- [6].…”