Long-term in vivo application of a potassium channel-based optogenetic silencer in the healthy and epileptic mouse hippocampus
Here we provide the electrophysiological datasets and Python scripts, which underlie the data analysis and conclusions in our paper about the novel potassium channel-based optogenetic silencer, PACK, and its application in vivo (Kleis et al., submitted to BMC Biology in 2021). We recorded local field potentials (LFPs) with wire electrodes, which were chronically implanted into the hippocampus of healthy or non-epileptic adult male mice. The LFPs were acquired from freely behaving mice, which were placed into the recording arena for three hours either without illumination (reference recording) or with an optogenetic stimulation (at 0.05 Hz or 0.1 Hz) during the second hour. We had six experimental groups, which are presented in the file named "LFP_nomenclature_and_datasets.xlsx". Further details about the experimental groups and methods are presented in the published article.
The datasets contain LFPs resampled at 500 Hz in .h5 file format. We uploaded LFPs acquired at the contralateral hippocampal electrode ('HCc') of the non-epileptic mice (saline-injected groups). For epileptic mice (kainate-injected groups), data from ipsilateral ('HCi') and contralateral hippocampal electrodes are presented.
The Python codes that were used to analyze the data and generate the figures can be found in three scripts:
Script 1: contains the function for calculating line length. Script 1 was used to generate subfigures in Fig.1, Fig. 4, Fig.S2, Fig. S3, and Fig. S4.
Script 2: contains functions for (1) extracting data snippets before and after light pulses and (2) calculating line length for these snippets. Additionally, examples are provided of how we used the functions (3) to extract LFP snippets and save them as matrices and (4) to calculate and save the line lengths of these snippets. Script 2 was used for Fig. 2.
Script 3: contains functions for spectral analysis, including calculation and plotting of power spectral density (PSD) and plotting of spectrograms. The script contains three examples of how the functions were used to analyze and present data.
Example 1. Plotting individual PSDs and creating a matrix with all PSDs
Example 2. Extracting the power areas of the delta, theta, beta, and gamma oscillations by calculating the area under the curve of PSD plots in respective ranges
Example 3. Plotting spectrograms
The script 3 was used for Fig. 3, Fig. 4, Fig. S2, and Fig S3.
