Live ZScores Brain Avatar Clinical Considerations Live ZScore

Live Z-Scores Brain Avatar Clinical Considerations

Live Z-Score Training • • • Normative database as a guide Power, connectivity metrics Multiple concurrent variables Operant learning paradigm Age-appropriate norms (c) 2012 Thomas F. Collura

Live Z-score training • Is: – A means for global optimization – An approach to individualized training – Flexible, adjustable targets and ranges – Using population mean as a reference – Able to target variability vs ”stuckness” • Is not: – “one size fits all” – Forcing everyone to train to the same goals – Using the population mean as a requirement (c) 2012 Thomas F. Collura

Live Z-Score Training • • • Absolute Power Relative Power Ratios Asymmetry Coherence Phase (c) 2012 Thomas F. Collura

Brain. Master LZT training • “Multivariate proportional” • Unique characteristics: – Multiple z-scores trained simultaneously – Proportional feedback – Allows brain to maintain coping, compensating mechanisms – Allows outliers to exist – Addresses “stuck” variables, encourages variability, flexibility (c) 2012 Thomas F. Collura

PZOK Control Screen Operant (white): Percentage of z-scores Criterion (green): Percentage required Result (red): Percent of time achieved (c) 2012 Thomas F. Collura

Live Z Scores – 4 channels (248 targets) 26 x 4 + 24 x 6 = 248 (104 power, 144 connectivity) (c) 2012 Thomas F. Collura

Progress of Live Z-Score Training Most deviant scores -> toward normal (c) 2012 Thomas F. Collura

Progress of MVP Variable Searching / Hunting -> consistent improvement (c) 2012 Thomas F. Collura

PZOK Results Severe Autistic – 20 & 40 sessions (c) 2012 Thomas F. Collura

PZOK Results Severe Autistic – 20 and 40 sessions (c) 2012 Thomas F. Collura

Brain. Master Z-Plus Adds new metrics PZMO: aggregate motion of the outliers PZME: mean distance of the outliers Adds additional feedback sensitive to extremes • Rewards positive change • • (c) 2012 Thomas F. Collura

Z-Plus Live Z-Scores “Zbars” (most deviant scores often “stuck”) (c) 2012 Thomas F. Collura

Brain. Avatar • • Live s. LORETA imaging and training Visualize and measure regions of interest 19 -channels: localization 4 -channels: regionalization Instantaneous (30 msec) Video speed brain electrical imaging 5 millimeter resolution 10 -15 millimeter accuracy (c) 2012 Thomas F. Collura

Brain. Avatar – Live s. LORETA • Based upon 20 years research • Maximum-likelihood estimate of brain generators • Reflects pyramidal cell populations • Proven correlation with MRI, CT • 100 x faster than previous implementations (c) 2012 Thomas F. Collura

Brain. Avatar – ROI Neurofeedback • • Regions of Interest (lobes, broadmann, etc) Integrated training of power, connectivity Combine s. LORETA with surface training Combine with traditional training Power Connectivity ISF (Infra-slow fluctuations) Peripheral (HRV, TEMP, SCR, etc) (c) 2012 Thomas F. Collura

Brain. Avatar (c) 2012 Thomas F. Collura

Brain. Avatar Z-Builder • • Creates reference norms from EEG data Power, connectivity Surface (19 -channels) s. LORETA (6239 voxels) Can be used for z-score training Individualized targets Can be used to create own databases (c) 2012 Thomas F. Collura

Brain. Avatar (c) 2012 Thomas F. Collura

Online Information Online published material: • http: //www. brainm. com/kb/entry/362/ Online videos: • http: //www. youtube. com/playlist? list=PLE 84 A 6 CCE 36979 B 66 (c) 2012 Thomas F. Collura