This thesis seeks to quantify human alpha rhythm in order to obtain better
measures to test theoretical models of neurodynamics, with potential clinical
applications for the method of identification.
An automated algorithm is developed in Chapter 2 to facilitate collection
of objective data from an expanded alpha band (4–14 Hz) in a large number
of subjects. This method avoids subjective bias inherent to traditional visual
identification of the alpha activity, produced multiple peak information (if multiple
peaks exist) that is absent in qEEG measures, and uses information from
multiple electrode sites to eliminate spurious peaks. This method is tested and
validated on 100 subjects.
In addition to traditional measures of alpha activities such as the frequency
and amplitude, further measures were devised to better quantify the alpha
rhythm and its spatial characteristics. Background spectra in the alpha range
are also characterized.
In Chapter 3 the algorithm is applied to a large (1498 subjects) database of
normal healthy subjects of approximately equal number in each sex, as well as
a large span in age (6–86 years), in order to establish typical parameter ranges.
Analysis is done comparing the age and the topological trends that are known
variants in the alpha rhythm. Investigations are also performed to test for
potential sex differences and/or lateralities. Key results are that double alpha
peaks are resolved in a large proportion of the subjects ( 50%), while single
alpha peak cases are likely to be double-peak cases in which the two peaks are
not resolved. Age trends in measures of alpha activity show increase of alpha
frequency from childhood to adolescence, a plateau in adulthood, and a slight
decline in old age; a decrease in alpha amplitude in old age is also observed.
These findings are consistent with previous literature and provide better statistics.
Topological distribution of the alpha activity on the head is also explored,
with little lateral asymmetry observed. No statistically significant differences
between the sexes are found.
The C++ code that was developed and utilized in this thesis is included in
Appendix B. It is provided on disk and is available online.
A study carried out on the same group of subjects to determine age-related
trends of EEG parameters produced by model fitting is included in Appendixes
C, to provide a comparison between the methods and highlights corresponding