1. Live Z-Scores Brain Avatar Clinical Considerations

2. 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

3. 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

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

5. 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

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

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

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

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

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

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

12. 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

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

14. 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

15. 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

16. 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

17. BrainAvatar
(c) 2012 Thomas F. Collura

18. 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

19. BrainAvatar
(c) 2012 Thomas F. Collura

20. Online Information Online published material:
Online videos:
(c) 2012 Thomas F. Collura