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Responses of 1st , 2nd, and soon 3rd order Drosophila olfactory neurons

Project description

https://travis-ci.org/tom-f-oconnell/drosolf.svg?branch=master

Installation

pip install drosolf

If you need elevated permissions to install (if the pip install line fails with some sort of permissions error), you can try:

sudo -H pip install drosolf

Examples

To get Hallem and Carlson ORN responses, with the baseline added back in. Returned as a pandas DataFrame with columns of receptor and row indices of odor. The transpose (i.e. orn_responses.T) will have odors as the columns.

from drosolf import orns
orn_responses = orns.orns()

To get simulated projection neuron responses, using the Olsen input gain control model and the ORN responses.

from drosolf import pns
pn_responses = pns.pns()

Get correlation matrices at the ORN and (simulated) PN levels for a list of odors, named as the columns of the previous DataFrames.

from drosolf import corrs
orn_correlations, pn_correlations = corrs.get_corrs(list_of_odors)

Generate plots of the same ORN and PN correlation matrices (uses seaborn).

import matplotlib.pyplot as plt
from drosolf import corrs

corrs.plot_corrs(list_of_odors)
plt.show()

Todo

  • DoOR integration
  • KC model(s)
  • sympy description of transformations applied to ORN data

Project details


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