An asynchronous wireless network for capturing event-driven data from large populations of autonomous sensors.

Networks of spatially distributed radiofrequency identification sensors could be used to collect data in wearable or implantable biomedical applications. However, the development of scalable networks remains challenging. Here we report a wireless radiofrequency network approach that can capture sparse event-driven data from large populations of spatially distributed autonomous microsensors. We use a spectrally efficient, low-error-rate asynchronous networking concept based on a code-division multiple-access method. We experimentally demonstrate the network performance of several dozen submillimetre-sized silicon microchips and complement this with large-scale in silico simulations. To test the notion that spike-based wireless communication can be matched with downstream sensor population analysis by neuromorphic computing techniques, we use a spiking neural network machine learning model to decode prerecorded open source data from eight thousand spiking neurons in the primate cortex for accurate prediction of hand movement in a cursor control task.

Versatile On-Chip Programming of Circuit Hardware for Wearable and Implantable Biomedical Microdevices.

Wearable and implantable microscale electronic sensors have been developed for a range of biomedical applications. The sensors, typically millimeter size silicon microchips, are sought for multiple sensing functions but are severely constrained by size and power. To address these challenges, a hardware programmable application-specific integrated circuit design is proposed and post-process methodology is exemplified by the design of battery-less wireless microchips. Specifically, both mixed-signal and radio frequency circuits are designed by incorporating metal fuses and anti-fuses on the top metal layer to enable programmability of any number of features in hardware of the system-on-chip (SoC) designs. This is accomplished in post-foundry editing by combining laser ablation and focused ion beam processing. The programmability provided by the technique can significantly accelerate the SoC chip development process by enabling the exploration of multiple internal circuit parameters without the requirement of additional programming pads or extra power consumption. As examples, experimental results are described for sub-millimeter size complementary metal-oxide-semiconductor microchips being developed for wireless electroencephalogram sensors and as implantable microstimulators for neural interfaces. The editing technique can be broadly applicable for miniaturized biomedical wearables and implants, opening up new possibilities for their expedited development and adoption in the field of smart healthcare.

Wireless Addressable Cortical Microstimulators Powered by Near-Infrared Harvesting.

Ensembles of autonomous, spatially distributed wireless stimulators can offer a versatile approach to patterned microstimulation of biological circuits such as the cortex. Here, we demonstrate the concept of a distributed, untethered, and addressable microstimulator, integrating an ultraminiaturized ASIC with a custom-designed GaAs photovoltaic (PV) microscale energy harvester, dubbed as an "optical neurograin (ONG)". An on-board Manchester-encoded near-infrared downlink delivers incident IR power and provides a synchronous clock across an ensemble of microdevices, triggering stimulus events by remote command. Each ONG has a unique device address and, when an incoming downlink bit sequence matches with this device identification (ID), the implant delivers a charge-balanced current stimulus to the target cortex. Present devices use 7-bit metal fuses fabricated during the CMOS process for their device ID, laser-scribed in post-processing, allowing in principle for a stimulator network of up to 128 nodes. We have characterized small ensembles of ONGs and shown a proof of concept of the system both on benchtop and in vivo rat rodent model.

A Scalable and Low Stress Post-CMOS Processing Technique for Implantable Microsensors.

Implantable active electronic microchips are being developed as multinode in-body sensors and actuators. There is a need to develop high throughput microfabrication techniques applicable to complementary metal-oxide-semiconductor (CMOS)-based silicon electronics in order to process bare dies from a foundry to physiologically compatible implant ensembles. Post-processing of a miniature CMOS chip by usual methods is challenging as the typically sub-mm size small dies are hard to handle and not readily compatible with the standard microfabrication, e.g., photolithography. Here, we present a soft material-based, low chemical and mechanical stress, scalable microchip post-CMOS processing method that enables photolithography and electron-beam deposition on hundreds of micrometers scale dies. The technique builds on the use of a polydimethylsiloxane (PDMS) carrier substrate, in which the CMOS chips were embedded and precisely aligned, thereby enabling batch post-processing without complication from additional micromachining or chip treatments. We have demonstrated our technique with 650 µm × 650 µm and 280 µm × 280 µm chips, designed for electrophysiological neural recording and microstimulation implants by monolithic integration of patterned gold and PEDOT:PSS electrodes on the chips and assessed their electrical properties. The functionality of the post-processed chips was verified in saline, and ex vivo experiments using wireless power and data link, to demonstrate the recording and stimulation performance of the microscale electrode interfaces.

Multivalent Traptavidin-DNA Conjugates for the Programmable Assembly of Nanostructures.

Here, we explore the extended utility of two important functional biomolecules, DNA and protein, by hybridizing them through avidin-biotin conjugation. We report a simple yet scalable technique of successive magnetic separations to synthesize traptavidin-DNA conjugates with four distinct DNA binding sites that can be used as a supramolecular building block for programmable assembly of nanostructures. Using this nanoassembly platform, we fabricate several different plasmonic nanostructures with various metallic as well as semiconductor nanoparticles in predetermined ways. We also use the platform to construct dendrimer nanostructures using valency-controlled traptavidin-DNA conjugates in a programmable manner. These results suggest that our protein-DNA supramolecular building blocks would make a significant contribution to the assembly of multicomponent and complex nanostructures for numerous contemporary and future applications from molecular imaging to drug delivery.

A Distributed Wireless Network of Implantable Sub-mm Cortical Microstimulators for Brain-Computer Interfaces.

Scalability of implantable neural interface devices is a critical bottleneck in enhancing the performance of cortical Brain-Computer Interfaces (BCIs) through access to high density and multi-areal cortical signals. This is challenging to achieve through current monolithic constructs with 100-200 channels, often with bulky tethering and packaging, and a spatially distributed sensor approach has recently been explored by a few groups, including our laboratories [1]. In this paper, we describe a microscale (500 µm) programmable neural stimulator in the context of an epicortical wireless networked system of sub-mm "Neurograins" with wireless energy harvesting (near 1 GHz) and bidirectional telemetry. Stimulation neurograins are post-processed to integrate poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) planar electrodes or intracortical penetrating microwires, and ensembles of microdevices are hermetically encapsulated using liquid-crystal polymer (LCP) thermocompression for chronic implantability. Radio-frequency power and telecommunications management are handled by a wearable external "Epidermal Skinpatch" unit to cater to chronic clinical implant considerations. We describe the stimulation neurograin performance specifications and proof-of-concept in bench top and ex vivo rodent platforms.