As the technologies advance and the software speed starts to allow derived measures to be used for feedback, the field is being offered many new tools for neurofeedback, including ICA based feedback, LORETA based feedback, and Z-score feedback.
All of these new tools will require clinical validation prior to being able to be considered standard techniques within our field’s armamentarium of efficacious techniques and clinical applications. All of these techniques offer great hope at this time with preliminary results, but careful clinical outcome studies remain to be performed.
In this brief note I will discuss Z-score feedback. This promising technique offers to set normative boundaries around the mean of many features of the EEG, and allow feedback to be controlled by these parameters. This obviously offers great hope to clinical outliers, as their Z-score divergence should be related to their pathology. One difficulty is that database Z-scores also show divergence when an adaptive or counter-balancing feature is used to cope with an abnormal finding. A crutch is not a normal finding, but you can’t walk without it if you have a broken leg.