A CMOS-based neural implantable optrode for optogenetic stimulation and electrical recording

This paper presents a novel integrated optrode for simultaneous optical stimulation and electrical recording for closed -loop optogenetic neuro-prosthetic applications. The design has been implemented in a commercially available 0.35μm CMOS process. The system includes circuits for controlling the optical stimulations; recording local field potentials (LFPs); and onboard diagnostics. The neural interface has two clusters of stimulation and recording sites. Each stimulation site has a bonding point for connecting a micro light emitting diode (μLED) to deliver light to the targeted area of brain tissue. Each recording site is designed to be post-processed with electrode materials to provide monitoring of neural activity. On-chip diagnostic sensing has been included to provide real-time diagnostics for post-implantation and during normal operation

Real-time encoding and compression of neuronal spikes by metal-oxide memristors

Advanced brain-chip interfaces with numerous recording sites bear great potential for investigation of neuroprosthetic applications. The bottleneck towards achieving an efficient bio-electronic link is the real-time processing of neuronal signals, which imposes excessive requirements on bandwidth, energy and computation capacity. Here we present a unique concept where the intrinsic properties of memristive devices are exploited to compress information on neural spikes in real-time. We demonstrate that the inherent voltage thresholds of metal-oxide memristors can be used for discriminating recorded spiking events from background activity and without resorting to computationally heavy off-line processing. We prove that information on spike amplitude and frequency can be transduced and stored in single devices as non-volatile resistive state transitions. Finally, we show that a memristive device array allows for efficient data compression of signals recorded by a multi-electrode array, demonstrating the technology’s potential for building scalable, yet energy-efficient on-node processors for brain-chip interfaces

Self-diagnosis implantable optrode for optogenetic stimulation

PhD ThesisAs a cell type-specific neuromodulation method, optogenetic technique holds remarkable potential for the realisation of advanced neuroprostheses. By genetically expressing light-sensitive proteins such as channelrhodopsin-2 (ChR2) in cell membranes, targeted neurons could be controlled by blue light. This new neuromodulation technique could then be applied into extensive brain networks and be utilised to provide effective therapies for neurological disorders. However, the development of novel optogenetic implants is still a key challenge in the field. The major requirements include small device dimensions, suitable spatial resolution, high safety, and strong controllability. In particular, appropriate implantable electronics are expected to be built into the device, accomplishing a new-generation intelligent optogenetic implant. To date, different microfabrication techniques, such as wave-guided laser/light-emitting diode (LED) structure and μLED-on-optrode structure, have been widely explored to create and miniaturise optogenetic implants. However, although these existing devices meet the requirements to some extent, there is still considerable room for improvement. In this thesis, a Complementary Metal-Oxide-Semiconductor (CMOS)-driven μLED approach is proposed to develop an advanced implantable optrode. This design is based on the μLED-on-optrode structure, where Gallium Nitride (GaN) μLEDs can be directly bonded to provide precise local light delivery and multi-layer stimulation. Moreover, an in-built diagnostic sensing circuitry is designed to monitor optrode integrity and degradation. This self-diagnosis function greatly improves system reliability and safety. Furthermore, in-situ temperature sensors are incorporated to monitor the local thermal effects of light emitters. This ensures both circuitry stability and tissue health. More importantly, external neural recording circuitry is integrated into the implant, which could observe local neural signals in the vicinity of the stimulation sites. Therefore, a CMOS-based multi-sensor optogenetic implant is achieved, and this closed-loop neural interface is capable of performing multichannel optical neural stimulation and electrical neural recording simultaneously. This optrode is expected to represent a promising neural interface for broad neuroprosthesis applications