A Neuromorphic Brain Interface based on RRAM Crossbar Arrays for High Throughput Real-time Spike Sorting.

Real-time spike sorting and processing are crucial for closed-loop brain-machine interfaces and neural prosthetics. Recent developments in high-density multi-electrode arrays with hundreds of electrodes have enabled simultaneous recordings of spikes from a large number of neurons. However, the high channel count imposes stringent demands on real-time spike sorting hardware regarding data transmission bandwidth and computation complexity. Thus, it is necessary to develop a specialized real-time hardware that can sort neural spikes on the fly with high throughputs while consuming minimal power. Here, we present a real-time, low latency spike sorting processor that utilizes high-density CuOx resistive crossbars to implement in-memory spike sorting in a massively parallel manner. We developed a fabrication process which is compatible with CMOS BEOL integration. We extensively characterized switching characteristics and statistical variations of the CuOx memory devices. In order to implement spike sorting with crossbar arrays, we developed a template matching-based spike sorting algorithm that can be directly mapped onto RRAM crossbars. By using synthetic and in vivo recordings of extracellular spikes, we experimentally demonstrated energy efficient spike sorting with high accuracy. Our neuromorphic interface offers substantial improvements in area (~1000× less area), power (~200× less power), and latency (4.8µs latency for sorting 100 channels) for real-time spike sorting compared to other hardware implementations based on FPGAs and microcontrollers.

All-Passive Hardware Implementation of Multilayer Perceptron Classifiers.

Bottom-up-fabricated crossbars promise superior circuit density and 3-D integrability compared with the traditional CMOS-based implementations. However, their inherent stochasticity presents difficulties in building complex circuits from components that demand precise patterning and high registration accuracies. With fewer terminals than active devices, passive components offer higher device densities and registration tolerances, making them amenable to bottom-up synthesized nanocrossbars. Motivated by this preference for passivity, we explore, in this article, neuromorphic classifiers based on passive neurons and passive synapses. We demonstrate via SPICE simulations how a shallow network of the diode-resistor-based passive rectifier neurons and resistive voltage summers, despite its inherent inability to buffer, amplify, and negate signals, can recognize MNIST digits with 95.4% accuracy. We introduce weight-to-conductance mappings that enable negative weights to be implemented in hardware without excessive memory overheads. The influences of soft and hard defects on the classification performance are evaluated, and the methods to boost fault-tolerance are proposed. The first-order evaluation of the area, speed, and power consumption of the passive multilayer perceptron classifiers is undertaken, and the results are compared with a benchmark study in neuromorphic hardware.

Microfabricated intracortical extracellular matrix-microelectrodes for improving neural interfaces.

Intracortical neural microelectrodes, which can directly interface with local neural microcircuits with high spatial and temporal resolution, are critical for neuroscience research, emerging clinical applications, and brain computer interfaces (BCI). However, clinical applications of these devices remain limited mostly by their inability to mitigate inflammatory reactions and support dense neuronal survival at their interfaces. Herein we report the development of microelectrodes primarily composed of extracellular matrix (ECM) proteins, which act as a bio-compatible and an electrochemical interface between the microelectrodes and physiological solution. These ECM-microelectrodes are batch fabricated using a novel combination of micro-transfer-molding and excimer laser micromachining to exhibit final dimensions comparable to those of commercial silicon-based microelectrodes. These are further integrated with a removable insertion stent which aids in intracortical implantation. Results from electrochemical models and in vivo recordings from the rat's cortex indicate that ECM encapsulations have no significant effect on the electrochemical impedance characteristics of ECM-microelectrodes at neurologically relevant frequencies. ECM-microelectrodes are found to support a dense layer of neuronal somata and neurites on the electrode surface with high neuronal viability and exhibited markedly diminished neuroinflammation and glial scarring in early chronic experiments in rats.

Biomimetic extracellular matrix coatings improve the chronic biocompatibility of microfabricated subdural microelectrode arrays.

Intracranial electrodes are a vital component of implantable neurodevices, both for acute diagnostics and chronic treatment with open and closed-loop neuromodulation. Their performance is hampered by acute implantation trauma and chronic inflammation in response to implanted materials and mechanical mismatch between stiff synthetic electrodes and pulsating, natural soft host neural tissue. Flexible electronics based on thin polymer films patterned with microscale conductive features can help alleviate the mechanically induced trauma; however, this strategy alone does not mitigate inflammation at the device-tissue interface. In this study, we propose a biomimetic approach that integrates microscale extracellular matrix (ECM) coatings on microfabricated flexible subdural microelectrodes. Taking advantage of a high-throughput process employing micro-transfer molding and excimer laser micromachining, we fabricate multi-channel subdural microelectrodes primarily composed of ECM protein material and demonstrate that the electrochemical and mechanical properties match those of standard, uncoated controls. In vivo ECoG recordings in rodent brain confirm that the ECM microelectrode coatings and the protein interface do not alter signal fidelity. Astrogliotic, foreign body reaction to ECM coated devices is reduced, compared to uncoated controls, at 7 and 30 days, after subdural implantation in rat somatosensory cortex. We propose microfabricated, flexible, biomimetic electrodes as a new strategy to reduce inflammation at the device-tissue interface and improve the long-term stability of implantable subdural electrodes.