Metadata-Version: 2.1
Name: statesegmentation
Version: 0.0.5
Summary: Detecting neural state transitions underlying event segmentation
Home-page: https://github.com/lgeerligs/statesegmentation
Author: Linda Geerligs, Umut Güçlü
License: MIT
Platform: UNKNOWN
Description-Content-Type: text/markdown
License-File: LICENSE

# statesegmentation

The statesegmentation package contains the implementation of a a greedy search algorithm (GSBS) to
segment a timeseries into states with stable activity patterns.
     
You can find more information about the method here:
Geerligs L., van Gerven M., Güçlü U. (2021) Detecting neural state transitions underlying event segmentation.
Neuroimage. https://doi.org/10.1016/j.neuroimage.2021.118085

The method has since been improved as described here:
Geerligs L., Gözükara D., Oetringer D., Campbell K., van Gerven M., Güçlü U. (2022)
A partially nested cortical hierarchy of neural states underlies event segmentation in the human brain.
BioRxiv. https://doi.org/10.1101/2021.02.05.429165

The package can be installed using: pip install statesegmentation

An example use case can be found in the examples directory.




