This repository contains the code and documentation for investigating the relationship between the "point of no return" in action initiation and the human sense of agency using real-time Brain-Computer Interfaces (BCI).
This research explores how the timing of the "point of no return" (approximately 200ms before a voluntary action) influences our post-action sense of agency. Using BCI and machine learning techniques, we detect imminent actions in real-time to study how the temporal relationship between intention detection, action execution, and outcome presentation affects the perceived sense of control over actions.
We hypothesize that once the point of no return is crossed (~200ms before action), the brain considers the action as "initiated" in terms of agency attribution, even before physical execution. This temporal marker may significantly shape our post-action sense of agency.
├── data_collection/ # Scripts for the preparatory stage data collection
├── classifier/ # Implementation of the RLDA classifier
├── feature_extraction/ # EEG feature extraction and processing
├── real_time_experiment/ # Main experimental protocol implementation
├── utils/ # Helper functions and utilities
└── thesis/ # Master's thesis documentation
├── thesis.pdf # Full thesis document
└── figures/ # Original thesis figures
The complete research methodology, theoretical background, and experimental results are detailed in the master's thesis document located in the thesis/ directory. The thesis provides comprehensive information about:
- Theoretical foundations of sense of agency
- Previous research on the point of no return
- Detailed experimental design and methodology
- Implementation of the BCI system
- Results from the preparatory stage
- Future research directions
- ENOBIO 20 5G EEG system
- Medical-grade touch-proof adapter
- Custom button-box with speaker for action-outcome tasks
- MATLAB R2019b or later
- PsychToolbox
- Neuroelectrics Instrument Controller (NIC)
- 17 passive electrodes (F3, Fz, F4, FC5, FC1, FC2, FC6, T7, C3, Cz, C4, T8, CP5, CP1, CP2, CP6, Oz)
- Reference: AFz electrode
- Ground: Right mastoid
- Sampling rate: 500 Hz
- Install required dependencies
- Configure the EEG system according to the specified montage
- Run the preparatory stage experiments for classifier training
- Execute the main real-time experiment
The project has completed the preparatory stage, which includes:
- Data collection protocol implementation
- Feature extraction pipeline
- Classifier training framework
- Initial validation with 5 participants
The real-time experimental phase is currently being developed.
If you use this code or build upon this research, please cite:
Ghane, H. (2023). The Point of No Return in Action Cancellation:
Deciphering Its Influence on the Human Sense of Agency via Real-Time
Brain-Computer Interfaces. Master's thesis, Pompeu Fabra University.
For questions or collaboration inquiries, please get in touch with [email protected]