Cellular Calcium Activity at Depth Predicted from Surface Potential Recordings using Ultra-high Density Transparent Graphene Arrays

Abstract

Recording brain activity with high spatial and high temporal resolution across deeper layers of cortex has been a long-sought methodology to study how neural information is coded, stored, and processed by neural circuits and how it leads to cognition and behavior. Electrical and optical neural recording technologies have been the key tools in neurophysiology studies toward a comprehensive understanding of the neural dynamics. The advent of optically transparent neural microelectrodes has facilitated multimodal experiments combining simultaneous electrophysiological recordings from the brain surface with optical imaging and stimulation of neural activity. A remaining challenge is to scale down electrode dimensions to single -cell size and increase the density to record neural activity with high spatial resolution across large areas to capture nonlinear neural dynamics at multiple spatial and temporal scales. Here, we developed microfabrication techniques to create transparent graphene microelectrodes with ultra-small openings and a large, completely transparent recording area. We achieved this by using long graphene microwires without any gold extensions in the field of view. To overcome the quantum capacitance limit of graphene and scale down the microelectrode diameter to 20 μm, we used Pt nanoparticles. To prevent open circuit failure due to defects and disconnections in long graphene wires, we employed interlayer doped double layer graphene (id-DLG) and demonstrated cm-scale long transparent graphene wires with microscale width and low resistance. Combining these two advances, we fabricated high-density microelectrode arrays up to 256 channels. We conducted multimodal experiments, combining recordings of cortical potentials with high-density transparent arrays with two-photon calcium imaging from layer 1 (L1) and layer 2/3 (L2/3) of the V1 area of mouse visual cortex. High-density recordings showed that the visual evoked responses are more spatially localized for high-frequency bands, particularly for the multi-unit activity (MUA) band. The MUA power was found to be strongly correlated with the cellular calcium activity. Leveraging this strong correlation, we applied dimensionality reduction techniques and neural networks to demonstrate that single-cell (L2/3) and average (L1 and L2/3) calcium activities can be decoded from surface potentials recorded by high-density transparent graphene arrays. Our high-density transparent graphene electrodes, in combination with multimodal experiments and computational methods, could lead to the development of minimally invasive neural interfaces capable of recording neural activity from deeper layers without requiring depth electrodes that cause damage to the tissue. This could potentially improve brain computer interfaces and enable less invasive treatments for neurological disorders.