Floating Z-Scores

The relationship it shows is real. PZOK is the percent of monitored z-scores inside the target limits at a given moment; widening the band raises it, narrowing it lowers it, and PZOKUL is the reward event that turns on once PZOK clears a set threshold. Those mechanics match how %ZOK / Live Z-Score Training is configured.

The wide trend screen mirrors the real readout. Three lines track over time, as on the BrainMaster Z-Score Training tab: blue is PZOK (percent of z-scores OK / inside the window), green is the reward threshold, and red is Percent Reward — the share of recent time the threshold was met. When blue holds above green, red climbs.

Dynamic vs manual protocols. You always set the z-thresholds (the window) yourself. With Dynamic thresholding off, you also fix the reward criterion: narrow the window and watch PZOK fall below that flat criterion — Percent Reward collapses and the client stops being reinforced. Switch dynamic on and the criterion tracks the recent PZOK level (sitting at its 45th percentile), holding Percent Reward near ~55% and following the signal smoothly as it drifts — steady, with no lag or large catch-up gaps. That is the essence of a dynamic-threshold protocol. Either way the stuck and far-outlier metrics can't be captured, so PZOK never quite reaches 100%.

The motion is smoothed on purpose. Each score drifts slowly and the Live PZOK readout is a short (~1 second) rolling average, so the number is readable and the reward lamp does not strobe. Real systems likewise average the feedback signal and apply a sustained-reward criterion rather than reacting to every instantaneous sample. The reward tone, when enabled, is a simplified stand-in for the auditory reward contingency — a middle-C voice tracks the same in-band/out-of-band state as the lamp, and E and G are layered in purely as a graded illustration of PZOK rising further above criterion. It is not a calibrated BrainMaster feedback voice, point-scoring, or MIDI mapping, and the note thresholds are an arbitrary teaching choice, not a clinical parameter.

The distribution is fat-tailed, not tidy. Most metrics drift tightly around zero. A minority (~15%) range wider — the variable outliers — but they drift slowly rather than jumping, the way a deviant metric actually behaves. And a handful (~4%, shown ringed) are chronically stuck near ±4.5 with little variability — the persistently abnormal metrics that training works hardest to recover, which is closer to how a real brain looks than a cloud that bounces everywhere. "Expected PZOK" is computed from this same three-part mixture, so the readout tracks the cloud closely.

What is deliberately omitted. No EEG hardware, no NeuroGuide / Applied-Neuroscience normative database, no artifact rejection (in reality a blink throws z-scores wild and can falsely trip reward), and only 10–100 stand-in metrics (your slider) versus the ~248 a 4-channel montage trains across power, asymmetry, coherence, and phase. Use it for intuition about the window↔reward tradeoff, not for clinical decisions.