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Ultraflexible electrode arrays for months-long high-density electrophysiological mapping of thousands of neurons in rodents

Nature Biomedical Engineering volume 7, pages 520–532 (2023)Cite this article

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Abstract

Penetrating flexible electrode arrays can simultaneously record thousands of individual neurons in the brains of live animals. However, it has been challenging to spatially map and longitudinally monitor the dynamics of large three-dimensional neural networks. Here we show that optimized ultraflexible electrode arrays distributed across multiple cortical regions in head-fixed mice and in freely moving rats allow for months-long stable electrophysiological recording of several thousand neurons at densities of about 1,000 neural units per cubic millimetre. The chronic recordings enhanced decoding accuracy during optogenetic stimulation and enabled the detection of strongly coupled neuron pairs at the million-pair and millisecond scales, and thus the inference of patterns of directional information flow. Longitudinal and volumetric measurements of neural couplings may facilitate the study of large-scale neural circuits.

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Fig. 1: Overview of the large-scale modular NET technology.
Fig. 2: Overview of the recording performance.
Fig. 3: Volumetric high-density mapping of the visual cortex in an awake head-fixed mouse.
Fig. 4: Visual decoding using large-scale neural recordings.
Fig. 5: Simultaneous volumetric recording and optogenetic stimulation.
Fig. 6: Large-scale distributed recording in awake head-fixed mice and behaviour decoding.
Fig. 7: Chronic stability of large-scale recordings by NETs, and evaluation of network stability over time.

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Data availability

The main data supporting the results of this study are available within the paper and its Supplementary Information. The datasets generated during the study are too large to be publicly shared. Sample data are available from the corresponding authors on reasonable request.

Code availability

Mountainsort3, which we used for spike sorting, is not maintained anymore, but Mountainsort4 is available at https://github.com/magland/ml_ms4alg. Deeplabcut, for animal-posture extraction, is available at https://github.com/DeepLabCut/DeepLabCut. Facemap, for animal-posture extraction, is available at https://github.com/MouseLand/facemap. Visual stimulus decoder was adapted into Matlab code, but Python code is available from the original author at https://github.com/MouseLand/stringer-et-al-2019. BehaveNet for video latent extraction is available at https://github.com/themattinthehatt/behavenet. The LSTM neural decoder is available at https://github.com/KordingLab/Neural_Decoding. The remaining analyses were done with custom Matlab routines, which are available from the corresponding authors on reasonable request.

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Acknowledgements

We thank M. Karlsson and M. Borius for input about neural recording electronics, C. Kemere for input about motion decoding, V. Yip for assistance with devices fabrication and assembly and A. Li for assistance with tests of the decoding model. This work was funded by the National Institute of Neurological Disorders and Stroke grants R01NS102917 (to C.X.), U01NS115588 (to C.X. and L.F.), R01NS109361(to L.L.) and UF1 NS107667 (to L.F); the National Heart, Lung and Blood Institute grant K25HL140153 (to L.L.); the Welch Foundation Research grant #F-1941-20170325 (to C.X.); and the Howard Hughes Medical Institute (to L.F.)

Author information

Author notes

  1. These authors contributed equally: Zhengtuo Zhao, Hanlin Zhu, Xue Li.

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA

    Zhengtuo Zhao, Hanlin Zhu, Xue Li, Liuyang Sun, Fei He, Lan Luan & Chong Xie

  2. NeuroEngineering Initiative, Rice University, Houston, TX, USA

    Zhengtuo Zhao, Hanlin Zhu, Xue Li, Liuyang Sun, Fei He, Lan Luan & Chong Xie

  3. Howard Hughes Medical Institute, Kavli Institute of Fundamental Neuroscience, and Departments of Physiology and Psychiatry, University of California San Francisco, San Francisco, CA, USA

    Jason E. Chung, Daniel F. Liu & Loren Frank

  4. Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA

    Jason E. Chung

  5. Department of Bioengineering, Rice University, Houston, TX, USA

    Lan Luan & Chong Xie

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  1. Zhengtuo Zhao
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Contributions

C.X. conceived and organized the overall study; Z.Z., H.Z., X.L., L.L. and C.X. designed the experiments, with inputs from all authors; Z.Z. and X.L. designed and fabricated the NET devices, with supervision from C.X.; D.F.L., J.E.C. and L.F., in collaboration with SpikeGadgets LLC, designed the stacking head-mount recording system; Z.Z. and X.L. designed the NET-probe integration with the head-mount recording system, with help from J.E.C. and D.F.L., and supervision from C.X. and L.F.; Z.Z. and X.L. developed and performed surgical procedures, supervised by C.X.; Z.Z., X.L. and H.Z. performed animal neural-recording experiments, with help from L.S. and F.H., and supervision from C.X. and L.L.; H.Z. and Z.Z. developed and implemented data pre-processing, supervised by C.X. and with input from J.E.C. and L.F.; Z.Z. and H.Z. performed data post-analysis, supervised by L.L. and C.X. and with input from L.F.; Z.Z. performed histology, supervised by C.X.; Z.Z., L.L. and C.X. wrote and revised the manuscript, with input from all authors.

Corresponding authors

Correspondence to Lan Luan or Chong Xie.

Ethics declarations

Competing interests

C.X., L.L. and Z.Z. are co-inventors on a patent filed by The University of Texas (WO2019051163A1, 14 March 2019) on the ultraflexible neural electrode technology described in this study. L. F., L.L. and C.X. hold equity ownership in Neuralthread Inc., an entity that is licensing this technology. All other authors declare no competing interests.

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Nature Biomedical Engineering thanks the anonymous reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Immunohistochemistry analysis showing the tissue-NET interface at a high implantation density.

One mouse was implanted in visual cortex with 10 type-I NET modules, at inter-shank spacings of 150 µm and inter-module spacings of 250 µm. Fluorescent (a) and brightfield (b) microscopy show no observable scarring in the implanted regions. Neuron: red; NETs: yellow. (c), We counted numbers of neurons in seven randomly-chosen 200-µm-diameter regions centering around NETs (yellow circled regions as an example) and five 200-µm-diameter randomly-chosen regions away from NETs (cyan circled regions as an example). We found no significant difference between the two groups using unpaired T test, p = 0.275 (d), suggesting no significant neuronal loss induced by dense NET implants. These results are consistent with our prior studies using single or few NETs (10, 13). Scalebars: 250 µm (a and b) and 50 µm (c).

Extended Data Fig. 2 Example recording performances of type-II (A) and –III (B) NET electrode designs.

These two designs offer high electrode density that allows for the recording of individual neurons by multiple channels and therefore perform better in single unit isolation. Color code corresponds to the location of the recording sites. Each dashed box outlines the waveforms of a single unit recorded on the corresponding sites. Scale bars: 100 μV (vertical) and 2 ms (horizontal).

Extended Data Fig. 3 Modular recording system interfacing with NETs.

(a), A ready-to-implant 128-channel NET module connected to a flexible printed circuit (FPC). Left panel shows the NET module and ball grid array (BGA) through which the connection to FPC was made. Right panel shows that individual NET shanks was attached to tungsten microwires for implantation. (b), Photo of a 128-channal stackable headstage connected to NET through an FPC. (c), Photo of a 1024-channel system composed of eight stackable modules. (d), Photo of a free-moving rat carrying a 1024-channel NET array and stackable headstages as shown in c. 3D printed case enclosed all headstages.

Supplementary information

Main Supplementary Information

Supplementary figures, tables and video captions.

Reporting Summary

Supplementary Video 1

Ultraflexibility of the NET arrays.

Supplementary Video 2

Micro-CT scan of a densely implanted NET array.

Supplementary Video 3

Example of 3D reconstruction of local field potentials recorded by a 1,024-channel NET array.

Supplementary Video 4

Example of spiking activity recorded in visual regions responding to drifting grating stimuli.

Supplementary Video 5

Example of spiking activity recorded by a NET array in visual, sensory and motor cortical regions.

Supplementary Video 6

Example of local field potentials recorded in visual, sensory and motor cortical regions by a NET array.

Supplementary Video 7

Animal facial-motion decoding by large-scale neural recordings.

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Zhao, Z., Zhu, H., Li, X. et al. Ultraflexible electrode arrays for months-long high-density electrophysiological mapping of thousands of neurons in rodents. Nat. Biomed. Eng 7, 520–532 (2023). https://doi.org/10.1038/s41551-022-00941-y

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