NeuroTin (EEG analysis)

NeuroTin is a clinical trial under the supervision of principal investigator Prof. Dr. Pascal Senn (HUG, Geneva) and supported by the Wyss Center. NeuroTin aims to compare tinnitus reduction after 3 different therapeutic approaches:

• Cognitive Behavioral Therapy (CBT), the current gold-standard treatment
• Neurofeedback with electroencephalography (EEG)
• Neurofeedback with functional magnetic resonance imaging (fMRI)

This repository contains the python implementation of the Neurofeedback paradigm using electroencephalography. Each session is articulated around 3 main steps: calibration, model, and neurofeedback.

• The calibration uses an auditory stimuli to elicit an N1-P2 evoked response.
• A model applies weights between 0 and 1 to each electrode based on the N1-P2 evoked response.
• Neurofeedback runs alternate between phases of non-regulation (also called rest) lasting 8 seconds, and phases of regulation lasting 16 seconds. During phases of regulation, participants attempt to up-regulate the ratio of alpha-band power over delta-band power displayed in real-time.

The implementation of the neurofeedback paradigm using EEG can be found on this repository.

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Dataset structure

The raw dataset folder structure is defined as:

> Data
> └─ 001
>     └─ Session 1
>     └─ Session 2
>         └─ Calibration
>         └─ Model
>         └─ Online
>         └─ Plots
>         └─ RestingState
>         └─ bads.txt
>         └─ logs.txt
>     └─ ...
>     └─ Session 15
> └─ 002
> └─ ...

4 .csv files are used to log different variables for every participant and session:

• mml_logs.csv: results of the Minimum Masking Level test repeated at every session.
• sound_stimulus_logs.csv: auditory stimulus settings used for calibration.
• model_var_logs.csv: helmet size (54, 56, 58), model normalization variables and bad channels.
• scores_logs.csv: neurofeedback scores displayed.

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Command-line interface

Many analysis function produces either (pre)processed data files or pandas DataFrame. A list of functions accessible via the CLI can be displayed with the command neurotin. Help for those functions can be obtained with the --help flag.