Abstract
Optically transparent neural microelectrodes have facilitated simultaneous electrophysiological recordings from the brain surface with the optical imaging and stimulation of neural activity. A remaining challenge is to scale down the electrode dimensions to the single-cell size and increase the density to record neural activity with high spatial resolution across large areas to capture nonlinear neural dynamics. Here we developed transparent graphene microelectrodes with ultrasmall openings and a large, transparent recording area without any gold extensions in the field of view with high-density microelectrode arrays up to 256 channels. We used platinum nanoparticles to overcome the quantum capacitance limit of graphene and to scale down the microelectrode diameter to 20 µm. An interlayer-doped double-layer graphene was introduced to prevent open-circuit failures. We conducted multimodal experiments, combining the recordings of cortical potentials of microelectrode arrays with two-photon calcium imaging of the mouse visual cortex. Our results revealed that visually evoked responses are spatially localized for high-frequency bands, particularly for the multiunit activity band. The multiunit activity power was found to be correlated with cellular calcium activity. Leveraging this, we employed dimensionality reduction techniques and neural networks to demonstrate that single-cell and average calcium activities can be decoded from surface potentials recorded by high-density transparent graphene arrays.
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Data availability
The data that support the findings of this study are available within the paper and its Supplementary Information. Other relevant data are available from the corresponding author upon request. Source data are provided with this paper.
Code availability
The codes for processing the data are available from the corresponding author upon request.
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Acknowledgements
This research was supported by grants from the ONR (N000142012405, N000142312163 and N000141912545), NSF (ECCS-2024776, ECCS-1752241 and ECCS-1734940) and NIH (R21 EY029466, R21 EB026180 and DP2 EB030992) to D.K., grants from NIH (R01 NS091010A and R01 DC014690) to T.K and grants from the NSF (ECCS-2139416) and NIH (1R21EY033676) to E.C. Fabrication of the electrodes was performed at the San Diego Nanotechnology Infrastructure (SDNI) of University of California San Diego, a member of the National Nanotechnology Coordinated Infrastructure, which is supported by the National Science Foundation (grant ECCS-1542148).
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This work was conceived by M.R., J.-H.K. and D.K. Microelectrode array fabrication was performed by J.-H.K and the characterization and analysis of arrays were performed by J.-H.K, C.D.-E., M.N.W., E.C. and D.K. All the animal experiments were performed by C.R., X.L. and M.R. and analysed by M.R. with contributions from A.A., V.G., T.K. and D.K. The paper was written by M.R. and D.K. and edited by all the authors.
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Extended data
Extended Data Fig. 1 Comparison of optical transmittance and normalized impedance of our transparent graphene array with other neural interfaces.
Optical transmittance as a function of normalized impedance for all the electrode technologies listed in Extended Data Table 1.
Extended Data Fig. 2 Comparison of conventional gold electrodes with transparent graphene arrays.
(a) Conventional 64-channels gold array with 20 µm and (b) 6 µm wire widths and smaller gold pads. (c) Fully transparent 64-channels graphene array without surrounding gold wires. (d) Shadows created by opaque gold wires in the field of view during two-photon imaging at 50 µm (left) and 250 µm (right) depth under the electrodes. The scale bars are 100 µm. (e) Signals recorded by gold and graphene arrays shown in b and c during two-photon imaging (at 50 µm depth underneath the electrodes) showing light-induced artifacts in gold but not graphene electrode. (f) Power spectral density of signals recorded by gold and graphene electrodes during two-photon Z-scan from 50 µm to 150 µm underneath the electrodes.
Extended Data Fig. 3 Characterization of defects in SLG and DLG wires.
(a) SLG and DLG wire pinhole images using two-photon microscopy. SLG wire with different width 20 μm, (b) 30 μm, and (c) 40 μm. DLG wire with different width (d) 20 μm, (e) 30 μm, and (f) 40 μm. Scale bars are 20 μm.
Extended Data Fig. 4 Reducing the impedance of electrodes using PtNP deposition.
(a) Measured electrochemical impedance spectroscopy (EIS) and the fitted values using the equivalent circuit model for id-DLG electrode. (b) The Impedance of PtNP/id-DLG with various PtNP deposition time measured at 1 kHz. (c) SEM images of PtNP/id-DLG with various PtNP deposition times. Scale bars are 3 μm and 1 μm in the top and bottom row, respectively. (d) Cyclic voltammetry (CV) measurement result for id-DLG (red) and PtNP/id-DLG (black). (e) The ratio of the graphene wire resistance (RGr) to the electrode impedance (ZElectrode - RGr) for channels with different wire lengths. The gray dots in the graph represent the ratios for individual channels, while the red dots and bars indicate the mean and standard deviation, respectively, for groups of eight channels (n = 8) with similar wire lengths.
Extended Data Fig. 5 Transparent graphene arrays do not affect the signal quality.
(a) The noise level of all channels with different graphene wire lengths. The gray dots in the graph represent the noise level for individual channels, while the red dots and lines represent the mean and standard deviation of each group of eight channels with same graphene wire length. (b) The heatmap of noise level of all channels overlaid with microscope image of the 64-channel array. (c) Pyramidal cells around (blue ROIs) and underneath (red ROI) the electrode (green circle) and (d) their ∆F/F signals show that the PtNP/id-DLG electrode does not obstruct the FoV and affect the two-photon signal quality. Scale bars in c and d indicate 20 µm and 5 z-score, respectively.
Extended Data Fig. 6 Schematic of the decoding model used for single-cell calcium inference.
The main steps of the single-cell calcium inference pipeline are explained in detail. Calcium latent variables are extracted using GPFA (red panel) and predicted by the ECoG powers at different frequency bands (green panel). The predicted calcium latents are then projecting into single-cell space (blue panel).
Extended Data Fig. 7 Decoding spontaneous calcium activity at single-cell resolution.
(a) Representative examples for decoded (orange) vs ground truth (black) ∆F/F of five best-decoded cells in the spontaneous session. The scale bar is 3 z-score. (b) Decoding results for all 114 cells in the spontaneous session presented with their locations outlined in the FoV. The 9 channels inside the FoV are marked with black circles. The scale bars are 100 µm.
Extended Data Fig. 8 The relationship between population coupling and single-cell calcium decoding.
(a) Comparison of population coupling across cells (n = 114) in the spontaneous and evoked sessions using method 1 (Eq. 1 in the Supplementary Information), and (b) method 2 (Eq. 2 in the Supplementary Information). The red (blue) circles indicate highly coupled cells in the spontaneous (evoked) session with low population coupling in the evoked (spontaneous) session. (c) Decoding results as a function of population coupling for the spontaneous and (d) evoked sessions using method 2 (Eq. 2 in the Supplementary Information). The green boxes highlight highly coupled cells with poor decoding results. Yellow boxes highlight cells with high decoding performance, but low population couplings. (e) Decoding results and (f) population couplings of the top 25 decoded cells in the evoked and spontaneous sessions. (g) Decoding results and (h) population couplings of the top N decoded cells (N = 5 to 30) in the evoked and spontaneous sessions. Solid lines and shaded regions indicate the mean and s.e.m., respectively. Population couplings are calculated among the top N decoded cells.
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Ramezani, M., Kim, JH., Liu, X. et al. High-density transparent graphene arrays for predicting cellular calcium activity at depth from surface potential recordings. Nat. Nanotechnol. 19, 504–513 (2024). https://doi.org/10.1038/s41565-023-01576-z
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DOI: https://doi.org/10.1038/s41565-023-01576-z
