This project is a Python-based simulation project investigating how moderate coupling to external sensory stimuli affects the ability of an intrinsic oscillator model to track/process speech.
In the current project, we adapted the STiMCON model by Ten Oever and Martin (2021) (DOI: https://doi.org/10.7554/eLife.68066) which included a fixed intrinsic oscillator unaffected by external inputs. To couple the model with external sensory stimuli, we introduced the Stuart-Landau process which allowed us to quantify the coupling strength with a scalar value K.
The repository consists of scripts belonging to simulations of the Stuart-Landau process, a new Oscillator module (which we used in STiMCON to accommodate the Stuart-Landau process), the adapted STiMCON model, and result generation & plots.
stuart_landau_STiMCON.py:
This script implements the Stuart-Landau process over a predefined time period.
oscillator.py:
This script defines an oscillator with parameters.
STiMCON_core_v4.py
Core script for the STiMCON model which has all the low-level code, adapted from Ten Oever and Martin (2021).
AdaptedSTiMCON_PredictiveFeedback_RhythmicInput.py
Implementing extended STiMCON when presenting isochronous input, and saving the data of feedback activation per word node.
AdaptedSTiMCON_PredictiveFeedback_RandomisedInput.py
Implementing extended STiMCON when presenting non-isochronous input, and saving the data of feedback activation per word node.
AdaptedSTiMCON_VarRhy_AmbiguousInput_Rhythmic.py
Implement extended STiMCON when presented with isochronous input, and save the results of ambiguous input categorisation across
stimulus onset delays, degrees of ambiguity, and stimulus frequency
AdaptedSTiMCON_VarRhy_AmbiguousInput_Randomised.py
Implement extended STiMCON when presented with non-isochronous input, and save the results of ambiguous input categorisation across
stimulus onset delays, degrees of ambiguity, and stimulus frequency
AdaptedSTiMCON_plotting_PredictiveFeedback.py
Analysing and plotting data of feedback activation per word node by implementing extended STiMCON with rhythmic (isochronous) and randomised (non-isochronous) sensory inputs.
AdaptedSTiMCON_plotting_AmbiguousInput.py
Analyse and plot data of ambiguous input categorisation implementing extended STiMCON with isochronous and non-isochronous sensory inputs
All the original scripts of Ten Oever and Martin (2021) used/called in the scripts above can be found: https://github.com/sannetenoever/STiMCON/tree/main.