Resumen de Implant cortical d'alta densitat per a interfícies cervell-màquina basat en materials bidimension
The experimental discovery of graphene in 2004 marked the advent of a new research field based on two-dimensional materials, investigating their properties for applications in electronics, photonics and optoelectronics and, recently, also biomedical technology. Neurotechnology in particular, is a subject which could strongly benefit from these new materials, as their mechanical and chemical nature allow them to form a stable, conformable interface with the brain. The graphene solution-gated field-effect transistor (gSGFET) is one of several emerging sensing devices utilizing thin materials, and has shown great potential for brain-machine interfaces (BMIs), as it is able to record neural activity with high accuracy. Historically electrodes have been favored for such application, as they are easy to fabricate and the recorded signals can be acquired using simple read-out techniques. In recent years, however, the use of sensors with a transistor design was found to be beneficial for specific applications as they also unveil slow oscillatory activity, which is yet mostly unexplored. Moreover, transistors allow to construct sensor arrays with a large number of recording sites, since in contrary to electrodes they do not need to be combined with additional electronic components to enable sophisticated addressing schemes, thus strongly easing the technologic complexity of fabricating these arrays.
High intrinsic sensor noise remains a critical issue in electrophysiology due to the small amplitude of neural signals on the surface of the cortex. The geometric nature of graphene and other two-dimensional materials exposes them to degrading influences from their surroundings and makes it challenging to create high-quality interfaces with such materials. This leads to, for example, augmented low-frequency noise in the gSGFET which contaminates the frequency band of interest for neural recordings. Thus, as a first step towards the development of a high quality neural sensor array, technological improvements which allow to lower such intrinsic device noise are explored in chapter 3. Next, the fabrication and characterization of high-density neural sensor arrays of above 1000 gSGFET sensors on flexible substrate is described. As a rapidly increasing size of the connector footprint with the number of sensors poses restrictions on the count and the density of recording sites achievable on the array, the compatibility of the gSGFET technology with multiplexed readout schemes is of critical importance. Multiplexing enable the combination of multiples streams of information into a single signal and would thereby allow to overcome connectivity limitations of the state-of-the-art BMIs. More concretely, the compatibility of the gSGFET technology with the two most common schemes of multiplexed data readout, namely frequency-division and time-division multiplexing, is presented in chapter 4. Ultimately, a monolithic integration of addressing circuitry into the flexible sensor array is explored in chapter 5, as this would prevent inter-site crosstalk which can severely degrade the fidelity of the recorded signal in large multiplexed sensor arrays. Two-dimension transition-metal-dichalcogenides (e.g. MoS2) are suggested for this purpose, as they combine mechanical flexibility with a wide bandgap necessary for building field-effect transistors with high on/off-ratios. A hybrid gSGFET/MoS2-FET sensor array with multiplexed readout functionality is showcased as a first prototype towards a new generation of BMIs and a roadmap for the technology's scale-up is presented.
