Mamiya_etal_2023_Proprioceptor_selectivity_topographic_maps_Analysis_code

Analysis code for data presented in Mamiya et al. (2023) "Origins of proprioceptor feature selectivity and topographic maps in the Drosophila leg" Neuron

Brief description of the notebook/class

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Preprocessing_for_all_types_and_piezo_analysis_summary_20220927.ipynb

Jupyter notebook containing the class and parameters for preprocessing all two-photon imaging data.

• Read two-photon imaging data acquired by ScanImage, demultiplex the channels, filter and register images, align two-photon images with high-speed video images.
• Shows analyses examples.

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Tibia_tracking_20220921.ipynb

Jupyter notebook containing the class, functions, and parameters for tracking the tibia in high-speed video images.

• Read high-speed video images, detect tibia in the region of interest, track the tibia angle, and calculate the average tibia angle for each two-photon imaging frame.
• Shows analyses examples.

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Cell_tracking_20200920_v2.ipynb

Jupyter notebook containg the class, functions, and parameters for tracking the cells in the two-photon fast-z-stack images.

• Make z-projected image and use marker based watershed segmentation to segment cells. Then use the centroid of the previous frame's segmenation as a marker for the segment in the next frame. Initialize the cell segmentations from different starting frame and move forward/backwards to make multiple segmentations. Use the segmentations that is robust to the initial frame and movement direction.
• Shows analyses examples.

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Calculating_DRR_and_cell_movements_20220921.ipynb

Jupyter notebook containing the functions and parameters for calculating the DR/R, based on the cell segmentation data and the fluorescence from tdTomato and GCaMP7.

• Based on the cell segmentation data, calculate DR/R and show the activity vs position, activity vs tibia angle, etc.
• Shows analysis examples.