Multimodal in vivo brain electrophysiology with integrated glass microelectrodes

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Abstract

Electrophysiology is the most used approach for the collection of functional data in basic and translational neuroscience, but it is typically limited to either intracellular or extracellular recordings. The integration of multiple physiological modalities for the routine acquisition of multimodal data with microelectrodes could be useful for biomedical applications, yet this has been challenging owing to incompatibilities of fabrication methods. Here, we present a suite of glass pipettes with integrated microelectrodes for the simultaneous acquisition of multimodal intracellular and extracellular information in vivo, electrochemistry assessments, and optogenetic perturbations of neural activity. We used the integrated devices to acquire multimodal signals from the CA1 region of the hippocampus in mice and rats, and show that these data can serve as ground-truth validation for the performance of spike-sorting algorithms. The microdevices are applicable for basic and translational neurobiology, and for the development of next-generation brain–machine interfaces.

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Fig. 1: Design, fabrication and assembly of the Patch-Tritrode device.
Fig. 2: Multimodal electrophysiology with the Patch-Tritrode device.
Fig. 3: Design and fabrication of Patch-Silvertrode device.
Fig. 4: Multimodal electrophysiology and optogenetics with the Patch-Silvertrode.
Fig. 5: Design and fabrication of the Patch-Carbontrode.
Fig. 6: Multimodal electrophysiology and electrochemistry with the Patch-Carbontrode.
Fig. 7: Extracellular spike-sorting validation with intracellular ground-truth data.
Fig. 8: Bursts are the principal source of false-negative spike-sorting errors.

Data availability

The authors declare that all data supporting the findings of this study are available within the paper and its Supplementary information. The raw data acquired in this study are available from the corresponding author on reasonable request.

Code availability

The custom routines for Matlab used in this work are available from the corresponding author.

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Acknowledgements

We would like thank A. Pais, D. Lee, V. Reddy, H. Esmailbeigi, B. Bowers, B. Biddle, J. Macklin, R. Patel, W. Sun, B. Barbarits, J. Venton, E. Privman, P. Ahamad and L. Coddington for their valuable contributions to this study. We would also like to thank J. Markara and B. Andrasfalvy for helpful discussions. This work was supported by the Howard Hughes Medical Institute.

Author information

D.L.H., A.K.L., T.D.H. and M.B. conceived the project. T.D.H. supervised the project. M.B. developed and fabricated all multimodal devices. A.K.L. and M.B. aquired data with the Patch-Tritrode. D.L.H. and C.L. analysed the Patch-Tritrode data. D.L.H. and M.B. aquired data with the Patch-Silvertrode. D.L.H. analysed the Patch-Silvertrode data. R.D.S. and M.B. aquired Patch-Carbontrode data. D.L.H. and R.D.S. analysed the Patch-Carbontrode data. D.L.H. and M.B. wrote the manuscript with input from all authors.

Correspondence to David L. Hunt or Mladen Barbic.

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