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A Protocol for the Administration of Real-Time fMRI Neurofeedback Training
Published on: August 24, 2017
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Mechanisms of Neurofeedback: A Computation-theoretic Approach
1Department of Psychological Sciences, Birkbeck, University of London, Malet Street, WC1E 7HX London, United Kingdom.
Neuroscience
|June 10, 2017
Summary
Neurofeedback training uses brain oscillation feedback to enhance brain function. A new computational model highlights the striatum
Area of Science:
- Computational Neuroscience
- Neuroscience
- Brain-Computer Interfaces
Background:
- Neurofeedback training involves providing real-time feedback on neural measures.
- Electroencephalography (EEG) neurofeedback focuses on modulating brain oscillations.
- The underlying neural mechanisms of successful neurofeedback remain largely unexplained.
Purpose of the Study:
- To propose and simulate a computational neuroscience theory for EEG neurofeedback.
- To investigate the role of the striatum in modulating EEG frequencies during neurofeedback.
- To explore how methodological factors, like threshold setting, influence neurofeedback success.
Main Methods:
- Development of a computational model simulating peak alpha frequency upregulation.
- Implementation of the model within a computational neuroscience framework.
- Analysis of the model's behavior concerning threshold settings and feedback.
Main Results:
- The simulation successfully learned to increase peak alpha frequency.
- The model demonstrated the significant influence of threshold settings on feedback.
- Analyses suggest neurofeedback operates as a search process utilizing importance sampling.
Conclusions:
- A computational model implicates the striatum in EEG neurofeedback.
- The model offers a proof of concept for understanding and improving neurofeedback.
- Further research can refine this model to address specific neurofeedback protocols.
