Research › Practitioner Perspectives
Neurofeedback Using the Phenotype and Z-Score Modalities
STS Instructor Authored by Thomas Collura
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Article at a glance
Practitioner perspective. This article describes a clinician's own experience, cases or methods. It was not peer reviewed or controlled, so it can be subjective. Read it as practical insight, not as evidence that a treatment works.
- Area
- Practitioner Perspectives
- Authors
- Kerson C, Gunkelman J, Collura T
- Journal
- NeuroConnections (July 2008)
- Year
- 2008
- Protocol
- Comparison of live z-score training and EEG phenotype-based protocol selection
Key findings
- Both authors agree that training should target EEG deviations linked to a complaint, not every deviation
- Z-scores are presented as strongest for training many connectivity measures at once
- Phenotypes are a small set of raw-EEG patterns said to predict medication and neurofeedback response
- Gunkelman cautions that z-score training was then unproven and that the mean is not always the goal
A question-and-answer piece in which two developers explain when each of their approaches fits: Tom Collura for live z-score training and Jay Gunkelman for EEG phenotypes. Cynthia Kerson put the questions to them after a conference discussion. Collura says any QEEG-based training needs a complaint, a matching EEG abnormality and a reason to expect that fixing it will help. He warns that some deviations, such as excess SMR or certain hypocoherences, may be strengths that should not be trained away. He sees z-scores as most useful for training many connectivity measures at once. Gunkelman explains that phenotypes are a small set of EEG patterns, read from the raw EEG, that predict response to medication or neurofeedback. He argues that healthy brains do not sit at the group mean and that training to the mean can remove useful traits. He calls z-score training promising but unproven and advises informed consent where proven methods exist, as in epilepsy. It is an exchange of expert views, not a study.
Read it in NeuroConnections, July 2008 (ISNR archive), p. 24 →