Amin et al., 2020

Code used in Amin et al. 2020 to measure distances between synapses along neurite skeletons

Fetching data from hemibrain server

1. Install neuprint-python from: https://github.com/connectome-neuprint/neuprint-python (On a Mac, you may need to install Command Line Tools.)
2. Run getAPLskelAndSynapses_v1.1.py

python3 getAPLskelAndSynapses_v1.1.py

This will create the files APLskelv1.1.csv (APL's skeleton), APLtoKCv1.1.csv (list of all APL-KC synapses), KCtoAPLv1.1.csv (list of all KC-APL synapses). These are already provided in this repository under the folder 'data'.

Analyzing APL's skeleton and synapses

See the file runAPL.m to see what commands to run to reproduce Figure 8 and related figure supplements from Amin et al.

General explanation of code structure

The class neurSkel is intended to represent the skeleton of any neuron from the hemibrain connectome. The class APLskel extends this class with some APL-specific functions. Most core functions are contained in these classes but much analysis for the paper was done with standalone scripts as detailed in runAPL.m.

Code dependencies

Mapping the connectome APL onto the standard APL of our data requires the class activityMap in https://github.com/aclinlab/calcium-imaging