Spike analysis software
Project description
Spike analysis software
__|________|_____|_|_|___|_____|____||_____|_____|_____|____|_____|___||______ _|_______________________|______|_________|_______|_____|____|__|________|_|__ _____|___|__|_____|_______|____|_________________________|__|_________|_______ ___|_______|_____|______|_____|_______|__|___|________|______|___|____________ __|__|_______|_____|__|___|______|________|______|______|_____|_______THORNS__
- Name:
thorns
- Author:
Marek Rudnicki
- Email:
- URL:
- License:
GNU General Public License v3 or later (GPLv3+)
Description
With thorns you can analyze and display spike trains generated by neurons. It can be useful for both experimental and simulation data using Python. For example, you can easily calculate peristimulus time histogram (PSTH), interspike time histogram (ISIH), vector strength (VS), entrainment and visualize action potentials with raster plot.
waves is a submodule with some useful signal processing and generation functions, e.g. generate ramped tone, amplitude modulation tone, FFT filter, set level (dB_SPL).
I developed the package during my PhD in the group of Werner Hemmert at the TUM. It is oriented towards auditory research, but it could be easily extended.
Usage
Initialize and load spike trains:
import thorns as th from thorns.datasets import load_anf_zilany2014 spike_trains = load_anf_zilany2014()
Calculate vector strength:
th.vector_strength(spike_trains, freq=1000)
Raster plot:
th.plot_raster(spike_trains) th.show()
Generate and plot AM tone:
import thorns.waves as wv sound = wv.amplitude_modulated_tone( fs=48e3, fm=100, fc=1e3, m=0.7, duration=0.1, ) wv.plot_signal(sound, fs=48e3) wv.show()
Requirements
Python (2.7)
Numpy
Scipy
Pandas
Matplotlib
Installation
Quick install:
pip install thorns
Contributors
Jörg Encke
Project details
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