Layer-and-frequency-specific-task-engagement/Code

Code for Task Engagement Prediction from CSD profiles

The following files contain the code used for CSD estimation from the LFPs from Allen Brain Observatory and the task engagement prediction using Linear Discriminant Analysis.

Jupyter Notebooks

Stim_to_LFP.ipynb

This notebook contains the first steps for Allen data obtention. It saves the desired sessions and the LFPs, and aligns them to the novel stimuli presentations.

get_cortical_layers.ipynb

This notebook upgrades the channel dataframes from the previous notebook by adding the labels on Cortical Layers using the Common Coordinates Framework from Allen Brain Map.

get_CSD.ipynb

This notebook computes the Current Source Densities for all the LFP data

get_power_spectra.ipynb

The same as get_CSD.ipynb but for the obtention of Power Spectra

CSD_Analysis.ipynb

This notebook performs the data discretization and prepares it for task engagement prediction with LDA

Spectral_Analysis.ipynb

The same as get_CSD.ipynb but from Power Spectra

Python Scripts

LFP_functions.py

This script contains several functions used in the notebooks (LFP data alignment, Energy Normalization, CSD estimation, etc.)