1. Cognitive fatigue and electroencephalographic energy density
Bioelectric Technology for Human Performance Workshop
NASA Ames Research Center
July 31, 2001
Cognitive fatigue and electroencephalographic energy density by
Leslie D. Montgomery, Ph.D.
Lockheed Martin Engineering & Sciences CO.
Richard W. Montgomery, Ph.D.
San Jose State Foundation

2. Presentation Overview
Background of our work at NASA
Explanation of TEEG Energy Density
Applications of TEEG Energy Density
Suggested research/Open questions

3. Overall Objective
To develop practical, easily applied, measures of cerebral activity that can be used under operational conditions in human factors research:
- Topographic electroencephalography
- Rheoencephalography
- Electrophysiology

4. Background Cerebral blood flow during exposure to microgravity
Internal research project at SRI International
Phase I and II SBIR through NASA Langley Research Center
MSTTP at NASA Ames Research Center
DDF at NASA Ames Research Center
AOS Program element at Ames Research Center

5. International 10 - 20 TEEG electrode assignments

6. Typical TEEG voltage traces

7. Stimulus used during mathematical tests

8. Typical event-related potential (ERP) from one TEEG electrode

9. Typical TEEG voltage values at a given point in time

10. Model TEEG regression equation
V = (a + bX + cY + dXY)3
where: V = voltage at electrode coordinates X, Y
X = side-to-side direction in flattened scalp electrode grid
Y = front-to-back direction in electrode grid
V = (b1 + b2X + b3X b15X2Y3 + b16 X3Y3)

11. Derivation of topographic electro-encephalographic energy density surface

12. R-Square peaks: Mental task error index vs. ERP energy density
Electrode Period (Msec) R-Square Slope T T T
FPZ
FPZ F
FPZ
FPZ P P P P T

13. Typical correlation of group performance with TEEG energy density

14. Locus of peak TEEG energy density during mental arithmetic task

15. Male vs. female performance of mental arithmetic task

16. Normal vs. disabled readers

17. Visual discrimination task format

18. ERP voltage traces of target and non-target stimuli

19. ERP energy density traces of target and non-target stimuli

20. Correlation of TEEG energy density to visual task performance

21. Typical energy and performance profiles during long term mental arithmetic task performance

22. This subject was ill. The general pattern is the same as the end point of longer term tasks.

23. In spite of a surge of energy starting at ERP three, this subject was unable to prevent marked deterioration of performance after that.

24. This subject's energy level seemed to be sufficient to maintain performance until the drop in energy at the eighth ERP.

25. Simulation Model Flow Variables
H = share of available metabolic energy used for homeostasis functions,
M = share of available energy used for a cognitive task (e.g., mental arithmetic),
NH = extent of neglected homeostasis functions (measured in energy units),
NM = extent of neglected mental arithmetic requirements (in energy units),
RH = required energy to meet homeostasis demands
RM = required energy to maintain an adequate mental arithmetic performance.

26. Simulation Model Relationships
1. M is a diversion of a flow otherwise fully available as H:
M = 1 - H.
2. Homeostasis neglect accumulates and its ‘repair cost’ rises exponentially:
NH = (RH-H) ert dt.
3. Mental arithmetic neglect is simply the shortfall, relative to required energy:
NM = RM - M.
4. The H-flow is regulated to balance the neglected functions:
dH / dt = a (NH - NM).

27. Simulation Model Solution
At this level of sophistication only two coefficients are involved:
r = the rate of exponential growth of the importance of the homeostasis neglect.
a = the rate of response to that neglect.
Of course it also is necessary to give values to RH and RM.
In terms of operator notation, this system of equations reduces to the following second-order differential equation with a time-varying parameter:
(D2 + a D + a ert ) H = a RH

28. Simulation of short term task

29. Simulation of medium term task

30. Simulation of long term task

31. Whole head total ERP integrated energy density values

32. Graphical Display Techniques

33. 3 D Representation of Energy Density Metric of Mental Fatigue

34. 3 D Representations of Energy Density for Target/Non-Target Stimuli

35. Impedance Plethysmography for measurement of segmental volume and blood flow

36. Typical impedance electrode configuration

37. Pulsatile resistance changes indicate blood flow changes

38. Metrics used to quantify segmental hemodynamics

39. Correlation of brain blood flow and neural activity during a mental arithmetic task

40. Summary
Impedance techniques can be used to assess an operator’s circulatory responses to long term mental tasks and to evaluate countermeasure concepts
TEEG energy density procedures can be used to investigate neural activity during varied and long term cognitive tasks
An operator’s performance degradation during a cognitive task may be influenced by his allocation of mental resources during the task

41. Suggested Research Continued testing of energy density technique
Combined analysis of ERP and on-going EEG data
Joint measures of cerebral EEG and metabolic activity
Refine cerebral resource allocation model
Inclusion of cerebral blood flow measurements