There is also an attached Session Librarian file.

If you have not set up Session Librarian for Discovery, do the following:

PZMO is an outgrowth of the PZOK approach, and is an aggregate statistic reflecting change in the outlying Z-Scores. PZOK tells how many z-scores are within the target range, as a percentage. We usually use a percentage of between 50% and 80%, which means that a substantial portion of the z-scores are outliers. As a dynamical systems approach, this gives the brain flexibility to “choose” which z-scores to normalize, and which to leave as outliers. PZMO is the aggregate momentum of these outliers. It is a measure of their net motion, and is a dynamic systems concept. Think of the z-scores as having a life of their own, having mass and velocity. PZMO measures the group momentum, and tells you what percentage of the net motion is toward the target range. PZMO is generally below zero, as nothing is moving particularly toward the targets in general. However, when PZMO goes positive, it tells you the net positive movement. A value of 5% for PZMO is significant. It means that in the last instant, there was 5% net motion toward the targets. That is a very big deal. This is therefore a “derivative” measure that tells your client that at that moment, the outliers moved inward. We typically see only a few PZMO reward beeps every few seconds, so it is an added reward. It is like giving the brain a “gold star” when it has particularly good improvement that moment in time. In my view, it has a similar effect on the brain as the derivatives market had on Wall Street. Small changes can have huge effects, and major learning processes become possible.

PZME is a measure of the mean distance of the outliers from the zero point. It is a measure of the global size of the scattering of outliers in the collection of Z-Scores. As it moves lower, the outliers are moving closer to the targets. We mostly use this as a long-term statistic throughout the session, watching for a small change, say from 2.5 to 2.2, over the session.

In brief, PZOK only knows the percentage inside the target range, it does not know about the outliers, except that they must be out there someplace. PZMO tells you the net motion of the outliers at any instant. PZME tells you how far out they are in general. While PZMO is a very fast, derivative measure, PZME is a very slow, aggregate measure. It all feeds into a view of the brain and the z-scores as comprising a dynamic system that can determine its own rules for self-regulation if you give it the right information.

Thus, this approach, which we call “Z-Plus”, gives you more than one type of information. There are various ways to use PZMO, but usually people give a reward when it jumps something above zero, indicating net motion toward the targets.

New_Directions_in_Live_Z-Score_Neurofeedback_11-9-2010.ppt