Live Z-Scores Brain Avatar Clinical Considerations

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Presentation transcript:

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: Is not: 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 Power Ratios Asymmetry Coherence Phase (c) 2012 Thomas F. Collura

BrainMaster 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

BrainMaster 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

BrainAvatar Live sLORETA 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

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

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

BrainAvatar (c) 2012 Thomas F. Collura

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

BrainAvatar (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=PLE84A6CCE36979B66 (c) 2012 Thomas F. Collura

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