Analysis dataset from: Simultaneous dual-color calcium imaging in freely-behaving mice
Data files
Jun 19, 2025 version files 6.49 GB
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intermediate_ds.zip
6.49 GB
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README.md
5.60 KB
Abstract
Miniaturized fluorescence microscopes (miniscopes) enable imaging of calcium events from a large population of neurons in freely behaving animals. Traditionally, miniscopes have only been able to record from a single fluorescence wavelength. Here, we present a new open-source dual-channel Miniscope that simultaneously records two wavelengths in freely behaving animals. To enable simultaneous acquisition of two fluorescent wavelengths, we incorporated two CMOS sensors into a single Miniscope. To validate our dual-channel Miniscope, we imaged hippocampal CA1 region that co-expressed a dynamic calcium indicator (GCaMP) and a static nuclear signal (tdTomato) while mice ran on a linear track. Our results suggest that, even when neurons were registered across days using tdTomato signals, hippocampal spatial coding changes over time. In conclusion, our novel dual-channel Miniscope enables imaging of two fluorescence wavelengths with minimal crosstalk between the two channels, opening the doors to a multitude of new experimental possibilities.
https://doi.org/10.5061/dryad.fbg79cp5k
Description of the data and file structure
This is the dataset accompanying manuscript "Simultaneous dual-color calcium imaging in freely-behaving mice"
Files and variables
File: intermediate_ds.zip
Description: this is the intermediate data that can be used to reproduce analysis in the manuscript without needing raw data. Refer to this README (also provided below)for how to use them.
Upon extraction, the zip contains following content:
/cross_reg/[green or red]/*: cross-session registration results for green or red channel.cents.pklstores centroids of cells;dist.pklstores pair-wise distance of cells;mappings.pkl,mappings_meta.pklandmappings_meta_fill.pklcontains raw, registered and filled mappings;shiftds.nccontains intermediate registration dataset./drift/*: results related to drifting analysis.fr.featcontains tables of firing rates;metric.feat,metric_agg.featandovlp.csvcontains the raw, aggregated and selected metrics for overlapping cells;pv_corr.featandpv_corr_agg.csvcontains the raw and aggregated population vector correlations;pv_corr_mat.featcontains the raw place cell firing rates across sessions./frame_label/*: contains behavior results.behav.featandbehav_v4.featcontains the frame-by-frame behavior labels for dual-channel and single channel Miniscopes;fm_label.nccontains intergrated frame labels./processed/[green or red]/*: processed calcium data for green or red channel. The files are named as[animal]-[session].nc./register_g2r/*: results of registration between green and red channel.Agn/*,Agn_trans,Ared/: contains spatial footprints of green channel, registered (transformed) green channel, and red channel. Files are named as[animal]-[session].nc.proj_gn_trans: contains projections of raw data onto the registered green spatial footprints. Files are named as[animal]-[session].nccells_im.pkl: contains footprint images for cells.g2r_mapping.csv,g2r_mapping_corr.csv,g2r_mapping_lsm.csvcontains the mapping generated by mutual-minimum, footprint correlation, and linear sum assignment methods.green_mapping_reg.pklandred_mapping_reg.pklcontains the cross-session mappings after registration for green and red channel.green_reg_pactive.csvcontains the activation probability table for green channel.
Content of Additional README
This is the master analysis folder for dual channel imaging experiment.
To reproduce all analysis, make sure you have data folder available.
Then, run all the .py scripts in order (scripts starting with the same number can be run in parallel).
To reproduce individual figures in the manuscript from intermediate results, check details in the section below.
Reproducing individual figures
- Figure 3
- Requires:
intermediate/frame_label/behav.featintermediate/frame_label/behav_v4.feat
- Run:
02.compare_behavior.py
- Output:
- Panel B:
figs/behav_comparison/example.svg - Panel C:
figs/behav_comparison/comparison.svg
- Panel B:
- Requires:
- Figure 4
- Requires:
intermediate/processed/greenintermediate/processed/redlog/sessions.csvintermediate/cross_reg/red/mappings_meta_fill.pklintermediate/cross_reg/green/mappings_meta_fill.pkl
- Run:
04.register_g2r.py
- Output:
- Panel A:
figs/register_g2r/cells/m22-A_example.svg - Panel B:
figs/register_g2r/overlap_ncell.svg - Panel C:
figs/register_g2r/overlap_prop.svg
- Panel A:
- Requires:
- Figure 5
- Requires:
intermediate/processed/greenintermediate/processed/redlog/sessions.csvintermediate/cross_reg/red/mappings_meta_fill.pklintermediate/cross_reg/green/mappings_meta_fill.pkl
- Run:
04.register_g2r.py
- Output:
figs/register_g2r/traces.svg
- Requires:
- Figure 6
- Requires:
data/wavelength/fpbase_spectra_EGFP.csvdata/wavelength/et600-50m.txtdata/wavelength/et525-50m.txt
- Run:
04.register_g2r.py
- Output:
- Panel A:
figs/register_g2r/crosstalk_wavelength.svg - Panel B:
figs/register_g2r/crosstalk_distribution.svg
- Panel A:
- Requires:
- Figure 7
- Requires:
intermediate/processed/greenintermediate/processed/redlog/sessions.csvintermediate/cross_reg/red/mappings_meta_fill.pklintermediate/cross_reg/green/mappings_meta_fill.pkl
- Run:
04.register_g2r.py
- Output:
figs/register_g2r/summary_agg.svg
- Requires:
- Figure 8
- Requires:
log/sessions.csvintermediate/processed/greenintermediate/frame_label/fm_label.ncintermediate/cross_reg/green/mappings_meta_fill.pklintermediate/cross_reg/red/mappings_meta_fill.pklintermediate/register_g2r/green_mapping_reg.pkl
- Run:
05.drift_analysis.py
- Output:
- Panel A:
figs/drift/actMean-place_cells.svg - Panel B:
figs/drift/py_corr-place_cells.svg
- Panel A:
- Requires:
