Microstim Analysis

Microstimulation is a technique that stimulates a small population of neurons by passing a small electrical current through a nearby microelectrode. We from the Larkum lab in Berlin have used microstimulation as a learning paradigm [1,2].

Within this repository you will find the software implementation for analyzing data that was aquired within the microstimulation paradigm. The code, as well as a rundown of its structure, function and implementation are provided.

Usage

The Mouse_Data Class contains all data that is associated with the behavioural experiment. To load experimental data, both folder and file structure has to be formatted.

A detailed description guiding you through the data analysis is provided within the jupyter notebook analysis.ipyn. This file can be found in the code folder. You can test run it yourself using the sample data within the data folder.

In short the code functions as follows

1. Import your raw data, extracted from SPIKE2 as .txt files into the Mouse_Data class.
2. Inspect your data using Mouse_Data.full_data()
3. Analyse using the get_threshold_data() and get_cum_score() functions.
4. Visualize using plot_daily_threshold() and plot_intensity_trials()

Dependencies

The code depends on the following packages

• numpy (v1.21.5)
• pandas (v1.4.2)
• matplotlib (v3.5.1)
• scipy (v1.7.3)

In order to install all dependencies run

pip install requirements.txt

Data aquisition

Software has been written to analyse data from SPIKE2 (CED). Our Microstimulation Setup repository provides the script, the hardware and a detailed instruction on how to get started gathering your own data.

Demo the code

We provide a Jupyter Notebook that walks you through a test dataset to verify functionality. Within this analysis.ipyn notebook you also find instructions on how to use your own data. It is possible to use data gathered from different sources on the condition that filename and file content are standardized.