A non-surgical brain implant enabled through cell-electronics hybrid for focal neuromodulation
Data files
Aug 13, 2025 version files 79.77 GB
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Data.xlsx
9.32 MB
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Fig2b.zip
1.10 MB
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Fig3.zip
2.59 GB
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Fig4.zip
4.21 GB
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Fig5.zip
69.21 GB
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FigE3.zip
1.17 MB
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FigE5.zip
9.15 MB
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FigE6.zip
831.69 MB
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FigE8.zip
1.82 GB
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FigE9.zip
157.35 KB
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FigS10.zip
262.53 KB
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FigS12.zip
1.08 GB
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FigS13.zip
225.61 KB
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README.md
4.26 KB
Abstract
Bioelectronic implants for brain stimulation are used to treat brain disorders but require invasive surgery. To provide a non-invasive alternative, we report non-surgical implants consisting of immune cell–electronics hybrids, an approach we call Circulatronics. The devices can be delivered intravenously and traffic autonomously to regions of inflammation in brain, where they implant and affect neuromodulation, circumventing the need for surgery. To achieve suitable electronics, we designed and built subcellular-sized, wireless, photovoltaic electronic devices (SWEDs) that harvest optical energy with high power conversion efficiency. In mice, we demonstrate non-surgical implantation in inflamed brain region as an example of therapeutic target for several neural diseases, by employing monocytes as cells, covalently attaching them to the SWEDs and administering the resulting hybrids intravenously. We also demonstrate neural stimulation with 30 µm precision around the inflamed region. Thus, by fusing electronic functionality with the biological transport and targeting capabilities of living cells, this technology can form the foundation for autonomously implanting bioelectronics.
Dataset DOI: 10.5061/dryad.pzgmsbd12
Description of the data and file structure
This dataset contains all files required to reproduce the results in the publication “Non-surgical Bioelectronic Implant for Targeted Focal Brain Stimulation.”
Files and variables
File: Data.xlsx
Description: Source data for figures in the main text, extended data, and supplementary figures
Variables
- The following sheets are present in the data.xlsx file - each named and corresponding to the source data for the figures
- Fig. 2d-h
- Fig. 3c, Fig. 3g-i
- Fig. 4f-g
- Fig. 5a-f
- Fig. E1
- Fig. E2
- Fig. E3
- Fig. E5
- Fig. E7
- Fig. E9
- Fig. E10
- Fig. S5
- Fig. S6
- Fig. S9
- Fig. S11
File: Fig2b.zip
Description: Raw SEM images corresponding to the figure
File: FigE3.zip
Description: Raw SEM images corresponding to the figure
File: FigE5.zip
Description: contains raw images for Fig. E5d. Additionally, corresponding processed images can be found in the following sub-folders:
- NCB0184_22_014_crop-MaxIP_crop - processed .tiff images for Fig. E5d
- NCB0184_22_014_crop-MaxIPcrop_noDAPI - processed .tiff images for Fig. E5d
File: FigE9.zip
Description: Raw data/image as well as processed data/image to reproduce the figure
File: FigS10.zip
Description: Raw data in text format, matlab code to analyze the data and a processed image corresponding to the figure
File: FigS13.zip
Description: matlab code used to produce the figure and the associated processed figures generated using the code
File: FigE6.zip
Description: raw data/processed images corresponding to regression analysis (including the raw unprocessed images)
File: FigS12.zip
Description: raw data in .doric fomat (matlab code to process it is present in Fig. E8, or Fig. 4h), corresponding processed .mat files for direct usage and the plots associated with the figure
File: FigE8.zip
Description: raw data for the two control datasets in .doric fomat (and an associated matlab code to process it), corresponding processed .mat files for direct usage and the plots associated with the figure
File: Fig3.zip
Description: Contains data corresponding to sub-figure panels
- Fig. 3a - FIB/SEM raw images to reproduce the figure
- Fig. 3b - raw and processed images to reproduce the figure
- Fig. 3d-f - contains raw images for Fig. 3d, 3e, and 3f. Additionally, processed images can be found in the following sub-folders:
- Fig. 3d
- Fig. 3e
- Fig. 3f
- Fig. 3h - processed figures panels can be found. Additionally, the data corresponding to regression analysis (including the raw unprocessed images) can be found in the following sub-folder
- regressional_analysis
- Fig. 3i - processed figures panels can be found. Raw/unprocessed data can be found in Fig. 3h folder
File: Fig4.zip
Description: Contains data corresponding to sub-figure panels
- Fig. 4b-e - contains folders with raw/processed images for Fig. 4b, 4c, 4d, and 4e
- Fig. 4b - raw and processed images to reproduce the figure
- Fig. 4c - raw and processed images to reproduce the figure
- Fig. 4d - raw and processed images to reproduce the figure
- Fig. 4e - raw and processed images to reproduce the figure
- Fig. 4h - raw data in .doric fomat (and an associated matlab code to process it), corresponding processed .mat file and the plots associated with the figure
File: Fig5.zip
Description: Contains data corresponding to sub-figure panels
- Fig. 5a - processed figures and a sub-folder containing the raw data
- Data - contains the video recordings, matlab scripts to process the data for the experimental and control groups (SY127-131 - 3d control, SY132-136 - 3d expt; SY117-121 - 12d control, SY122-126 - 12d expt)
- Fig. 5b - processed figures. Raw data can be found in Fig. 5a subfolder "Data"
Code/software
The analyses were performed using MATLAB 2023. All codes and functions are provided within the dataset to ensure reproducibility.
