Resumen de Interficies neuronals de gran ample de banda basades en grafé
Brain function is based on highly complex processes, which remain yet to be described and understood in detail. In the last decades, neuroscience has experienced an accelerated development, prompted by novel neurotechnologies that allow monitoring the dynamics of electrical activity in the brain with a higher spatio-temporal resolution and wider coverage area. However, due to the high complexity of neural networks in the brain, which are composed of strongly interconnected neural populations across large brain regions, we are far from monitoring a significant fraction of neurons mediating complex functions.
In order to investigate large-scale brain dynamics with high spatial resolution several technologies have been extensively used, including functional magnetic resonance imaging (fMRI), voltage-sensitive dye imaging or high sensor-count electrophysiological recordings. However, the temporal resolution of fMRI and optical methods is typically limited to few hertz, almost three orders of magnitude below that of action potentials, and are limited to head-fixed conditions. On the other hand, electrophysiological recordings based on micro-electrode arrays provide a high spatio-temporal resolution, allowing to accurately detect fast dynamics from hundreds of individual neurons simultaneously in freely moving animals. However, neuroelectronic sensing interfaces present a trade-off between spatial resolution and coverage area. Moreover, they present a poor sensitivity in the infra-slow frequency band ($<0.5$\,$Hz$), which is related to long-range functional connectivity.
In this thesis, a novel technology based on graphene active sensors is presented, which allows to increase the coverage area and spatial resolution of electrophysiological recordings while preserving a high sensitivity in a wide frequency band, from infra-slow to single electrogenic cell activity. This technological development is divided into three main stages; first, a deeper understanding of the intrinsic noise characteristics and frequency response of these sensors is obtained by building on prior graphene sensor technology. In the second stage, a quasi-commercial system based on epi-cortical graphene sensor arrays and a wireless headstage for chronic implantation in rats is shown. Using this system, the reproducibility of the graphene sensor arrays, their long-term stability and their chronic biocompatibility are demonstrated. Furthermore, preliminary evidence is provided for a wide range of novel electrophysiological patterns owing to their sensitivity in the infra-slow frequency band. Finally, in the last stage of this thesis, the focus is centred on the development of new multiplexing strategies to upscale the number of sensors on the neural probes.
These three main development stages have led to the demonstration of the potential of multiplexed graphene sensor arrays for mapping of large-scale brain dynamics in a wide frequency band in freely moving animals over long periods. The combination of these capabilities makes graphene active sensor arrays a promising technology for high bandwidth brain computer interfaces and a unique tool to investigate the role of infra-slow activity on the coordination of higher frequency brain dynamics.
